Skip to content

GitLab

Commit ec1ba2c0 authored by Sidney233's avatar Sidney233
Browse files

test: Delete previous unit tests and add new end-to-end test.

parent 343eaac1
Hide whitespace changes
Inline Side-by-side
Showing with 0 additions and 21145 deletions
tests/unittest/test_integrations/test_rag/assets/middle.json deleted 100644 → 0
View file @ 343eaac1
{
"pdf_info": [
{
"preproc_blocks": [
{
"type": "text",
"bbox": [
47,
57,
299,
93
],
"lines": [
{
"bbox": [
47,
57,
299,
68
],
"spans": [
{
"bbox": [
49,
57,
298,
68
],
"score": 0.98,
"content": "of the synthetic stereo scene from a single camera perspective",
"type": "text"
}
]
},
{
"bbox": [
47,
71,
299,
80
],
"spans": [
{
"bbox": [
49,
71,
299,
80
],
"score": 0.96,
"content": "along with the ground truth disparity,occlusion map,and",
"type": "text"
}
]
},
{
"bbox": [
47,
82,
123,
93
],
"spans": [
{
"bbox": [
49,
82,
123,
93
],
"score": 0.99,
"content": "discontinuitymap.",
"type": "text"
}
]
}
]
},
{
"type": "image",
"bbox": [
47,
100,
301,
535
],
"blocks": [
{
"bbox": [
51,
100,
292,
484
],
"type": "image_body",
"lines": [
{
"bbox": [
51,
100,
292,
484
],
"spans": [
{
"bbox": [
51,
100,
292,
484
],
"score": 0.9999815225601196,
"type": "image",
"image_path": "b07d74524eac6f46b5505b48b1e10db23f2b45cb2d21d5fec72e967e61255811.jpg"
}
]
}
]
},
{
"bbox": [
47,
488,
301,
535
],
"type": "image_caption",
"lines": [
{
"bbox": [
49,
490,
299,
499
],
"spans": [
{
"bbox": [
49,
490,
299,
499
],
"score": 1.0,
"content": "Figure2:Twosampleframesfromthesyntheticvideose-",
"type": "text"
}
]
},
{
"bbox": [
48,
501,
300,
512
],
"spans": [
{
"bbox": [
48,
501,
300,
512
],
"score": 1.0,
"content": "quence (1st row), along with their corresponding ground truth",
"type": "text"
}
]
},
{
"bbox": [
48,
513,
299,
523
],
"spans": [
{
"bbox": [
48,
513,
299,
523
],
"score": 0.98,
"content": "disparity (2nd row), occlusion map (3rd row), and discontinuity",
"type": "text"
}
]
},
{
"bbox": [
48,
525,
110,
535
],
"spans": [
{
"bbox": [
48,
525,
110,
535
],
"score": 0.99,
"content": "map (4th row).",
"type": "text"
}
]
}
]
}
]
},
{
"type": "text",
"bbox": [
47,
549,
299,
678
],
"lines": [
{
"bbox": [
58,
549,
299,
558
],
"spans": [
{
"bbox": [
58,
549,
298,
558
],
"score": 0.98,
"content": "Theresultsof temporalstereomatching aregiveninFigure",
"type": "text"
}
]
},
{
"bbox": [
47,
561,
299,
570
],
"spans": [
{
"bbox": [
47,
561,
298,
570
],
"score": 0.98,
"content": "3foruniformadditivenoiseconfinedtotherangesof±O",
"type": "text"
}
]
},
{
"bbox": [
47,
573,
299,
582
],
"spans": [
{
"bbox": [
49,
573,
299,
582
],
"score": 0.96,
"content": "±20, and ±40. Each performance plot is given as a function",
"type": "text"
}
]
},
{
"bbox": [
47,
585,
299,
594
],
"spans": [
{
"bbox": [
48,
585,
299,
594
],
"score": 0.95,
"content": "of the feedback coefficient X. As with the majority of temporal",
"type": "text"
}
]
},
{
"bbox": [
47,
597,
299,
606
],
"spans": [
{
"bbox": [
49,
597,
299,
606
],
"score": 0.99,
"content": "stereomatching methods,improvements are negligible when",
"type": "text"
}
]
},
{
"bbox": [
47,
609,
299,
618
],
"spans": [
{
"bbox": [
48,
609,
299,
618
],
"score": 0.97,
"content": "no noise is added to the images [1o], [19]. This is largely due",
"type": "text"
}
]
},
{
"bbox": [
47,
621,
299,
629
],
"spans": [
{
"bbox": [
48,
621,
299,
629
],
"score": 1.0,
"content": "tothefactthatthevideousedtoevaluatethesemethodsis",
"type": "text"
}
]
},
{
"bbox": [
47,
633,
299,
641
],
"spans": [
{
"bbox": [
48,
633,
299,
641
],
"score": 1.0,
"content": "computergeneratedwithverylittlenoisetostartwith,thus",
"type": "text"
}
]
},
{
"bbox": [
47,
644,
299,
654
],
"spans": [
{
"bbox": [
48,
644,
299,
654
],
"score": 0.98,
"content": "the noise suppression achieved with temporal stereo matching",
"type": "text"
}
]
},
{
"bbox": [
47,
657,
299,
666
],
"spans": [
{
"bbox": [
48,
657,
299,
666
],
"score": 0.98,
"content": "showslittletonoimprovementovermethodsthatoperate on",
"type": "text"
}
]
},
{
"bbox": [
47,
669,
113,
678
],
"spans": [
{
"bbox": [
48,
669,
113,
678
],
"score": 1.0,
"content": "pairsofimages.",
"type": "text"
}
]
}
]
},
{
"type": "text",
"bbox": [
47,
680,
299,
725
],
"lines": [
{
"bbox": [
58,
680,
299,
690
],
"spans": [
{
"bbox": [
59,
680,
298,
690
],
"score": 0.97,
"content": "Significantimprovementsin accuracy canbeseenin Figure",
"type": "text"
}
]
},
{
"bbox": [
47,
692,
299,
701
],
"spans": [
{
"bbox": [
48,
692,
298,
701
],
"score": 0.97,
"content": "3 when the noise has ranges of ±20, and ±40.In this scenario",
"type": "text"
}
]
},
{
"bbox": [
47,
703,
299,
714
],
"spans": [
{
"bbox": [
48,
703,
299,
714
],
"score": 0.98,
"content": "the effect of noise in the current frame is reduced by increasing",
"type": "text"
}
]
},
{
"bbox": [
47,
716,
299,
725
],
"spans": [
{
"bbox": [
48,
716,
299,
725
],
"score": 0.96,
"content": "thefeedbackcoefficientX.Thisincreasing ofXhas theeffect",
"type": "text"
}
]
}
]
},
{
"type": "image",
"bbox": [
310,
55,
564,
371
],
"blocks": [
{
"bbox": [
314,
55,
538,
305
],
"type": "image_body",
"lines": [
{
"bbox": [
314,
55,
538,
305
],
"spans": [
{
"bbox": [
314,
55,
538,
305
],
"score": 0.9999905824661255,
"type": "image",
"image_path": "c7539af438972442d0f86aa46409e6684338ddfd1fbfd6bdacf02220853ccb55.jpg"
}
]
}
]
},
{
"bbox": [
310,
311,
564,
371
],
"type": "image_caption",
"lines": [
{
"bbox": [
312,
313,
562,
322
],
"spans": [
{
"bbox": [
312,
313,
562,
322
],
"score": 0.97,
"content": "Figure 3: Performance of temporal matching at different levels",
"type": "text"
}
]
},
{
"bbox": [
312,
325,
561,
334
],
"spans": [
{
"bbox": [
312,
325,
561,
334
],
"score": 0.98,
"content": "of uniformly distributed image noise{±0,±20,±40}.Mean",
"type": "text"
}
]
},
{
"bbox": [
311,
336,
563,
347
],
"spans": [
{
"bbox": [
311,
336,
563,
347
],
"score": 0.99,
"content": "squared error (MSE) of disparities is plotted versus the values",
"type": "text"
}
]
},
{
"bbox": [
311,
348,
561,
358
],
"spans": [
{
"bbox": [
311,
348,
561,
358
],
"score": 0.96,
"content": "of the feedback coefficient X. Dashed lines correspond to the",
"type": "text"
}
]
},
{
"bbox": [
311,
360,
535,
371
],
"spans": [
{
"bbox": [
311,
360,
535,
371
],
"score": 0.96,
"content": "values of MSE obtained without temporal aggregation.",
"type": "text"
}
]
}
]
}
]
},
{
"type": "image",
"bbox": [
310,
418,
563,
666
],
"blocks": [
{
"bbox": [
314,
418,
549,
623
],
"type": "image_body",
"lines": [
{
"bbox": [
314,
418,
549,
623
],
"spans": [
{
"bbox": [
314,
418,
549,
623
],
"score": 0.9999067783355713,
"type": "image",
"image_path": "9ac4db9197801de4a20dbc9ea17bc0c53afb7290dc8b5b45d9e92e830566cb14.jpg"
}
]
}
]
},
{
"bbox": [
310,
630,
563,
666
],
"type": "image_caption",
"lines": [
{
"bbox": [
312,
631,
562,
641
],
"spans": [
{
"bbox": [
312,
631,
562,
641
],
"score": 0.94,
"content": "Figure 4:Optimal values of the feedback coefficient \\ cor-",
"type": "text"
}
]
},
{
"bbox": [
312,
644,
561,
652
],
"spans": [
{
"bbox": [
312,
644,
561,
652
],
"score": 0.97,
"content": "responding to the smallest mean squared error (MSE)of the",
"type": "text"
}
]
},
{
"bbox": [
312,
655,
513,
665
],
"spans": [
{
"bbox": [
312,
655,
513,
665
],
"score": 0.97,
"content": "disparity estimates for a range of noise strengths.",
"type": "text"
}
]
}
]
}
]
},
{
"type": "text",
"bbox": [
311,
692,
563,
725
],
"lines": [
{
"bbox": [
311,
692,
563,
702
],
"spans": [
{
"bbox": [
311,
692,
562,
702
],
"score": 0.95,
"content": "of averaging out noise in the per-pixel costs by selecting",
"type": "text"
}
]
},
{
"bbox": [
311,
704,
563,
713
],
"spans": [
{
"bbox": [
311,
704,
562,
713
],
"score": 0.98,
"content": "matches based more heavily upon the auxiliary cost, which",
"type": "text"
}
]
},
{
"bbox": [
311,
716,
563,
725
],
"spans": [
{
"bbox": [
311,
716,
563,
725
],
"score": 0.97,
"content": "is essentially a much more stable running average of the cost",
"type": "text"
}
]
}
]
}
],
"layout_bboxes": [
{
"layout_bbox": [
47,
55,
301,
726
],
"layout_label": "V",
"sub_layout": []
},
{
"layout_bbox": [
310,
55,
564,
726
],
"layout_label": "V",
"sub_layout": []
}
],
"page_idx": 0,
"page_size": [
612.0,
792.0
],
"_layout_tree": [
{
"layout_bbox": [
0,
55,
612.0,
726
],
"layout_label": "V",
"sub_layout": [
{
"layout_bbox": [
47,
55,
564,
726
],
"layout_label": "H",
"sub_layout": [
{
"layout_bbox": [
47,
55,
301,
726
],
"layout_label": "V",
"sub_layout": []
},
{
"layout_bbox": [
310,
55,
564,
726
],
"layout_label": "V",
"sub_layout": []
}
]
}
]
}
],
"images": [
{
"type": "image",
"bbox": [
47,
100,
301,
535
],
"blocks": [
{
"bbox": [
51,
100,
292,
484
],
"type": "image_body",
"lines": [
{
"bbox": [
51,
100,
292,
484
],
"spans": [
{
"bbox": [
51,
100,
292,
484
],
"score": 0.9999815225601196,
"type": "image",
"image_path": "b07d74524eac6f46b5505b48b1e10db23f2b45cb2d21d5fec72e967e61255811.jpg"
}
]
}
]
},
{
"bbox": [
47,
488,
301,
535
],
"type": "image_caption",
"lines": [
{
"bbox": [
49,
490,
299,
499
],
"spans": [
{
"bbox": [
49,
490,
299,
499
],
"score": 1.0,
"content": "Figure2:Twosampleframesfromthesyntheticvideose-",
"type": "text"
}
]
},
{
"bbox": [
48,
501,
300,
512
],
"spans": [
{
"bbox": [
48,
501,
300,
512
],
"score": 1.0,
"content": "quence (1st row), along with their corresponding ground truth",
"type": "text"
}
]
},
{
"bbox": [
48,
513,
299,
523
],
"spans": [
{
"bbox": [
48,
513,
299,
523
],
"score": 0.98,
"content": "disparity (2nd row), occlusion map (3rd row), and discontinuity",
"type": "text"
}
]
},
{
"bbox": [
48,
525,
110,
535
],
"spans": [
{
"bbox": [
48,
525,
110,
535
],
"score": 0.99,
"content": "map (4th row).",
"type": "text"
}
]
}
]
}
]
},
{
"type": "image",
"bbox": [
310,
55,
564,
371
],
"blocks": [
{
"bbox": [
314,
55,
538,
305
],
"type": "image_body",
"lines": [
{
"bbox": [
314,
55,
538,
305
],
"spans": [
{
"bbox": [
314,
55,
538,
305
],
"score": 0.9999905824661255,
"type": "image",
"image_path": "c7539af438972442d0f86aa46409e6684338ddfd1fbfd6bdacf02220853ccb55.jpg"
}
]
}
]
},
{
"bbox": [
310,
311,
564,
371
],
"type": "image_caption",
"lines": [
{
"bbox": [
312,
313,
562,
322
],
"spans": [
{
"bbox": [
312,
313,
562,
322
],
"score": 0.97,
"content": "Figure 3: Performance of temporal matching at different levels",
"type": "text"
}
]
},
{
"bbox": [
312,
325,
561,
334
],
"spans": [
{
"bbox": [
312,
325,
561,
334
],
"score": 0.98,
"content": "of uniformly distributed image noise{±0,±20,±40}.Mean",
"type": "text"
}
]
},
{
"bbox": [
311,
336,
563,
347
],
"spans": [
{
"bbox": [
311,
336,
563,
347
],
"score": 0.99,
"content": "squared error (MSE) of disparities is plotted versus the values",
"type": "text"
}
]
},
{
"bbox": [
311,
348,
561,
358
],
"spans": [
{
"bbox": [
311,
348,
561,
358
],
"score": 0.96,
"content": "of the feedback coefficient X. Dashed lines correspond to the",
"type": "text"
}
]
},
{
"bbox": [
311,
360,
535,
371
],
"spans": [
{
"bbox": [
311,
360,
535,
371
],
"score": 0.96,
"content": "values of MSE obtained without temporal aggregation.",
"type": "text"
}
]
}
]
}
]
},
{
"type": "image",
"bbox": [
310,
418,
563,
666
],
"blocks": [
{
"bbox": [
314,
418,
549,
623
],
"type": "image_body",
"lines": [
{
"bbox": [
314,
418,
549,
623
],
"spans": [
{
"bbox": [
314,
418,
549,
623
],
"score": 0.9999067783355713,
"type": "image",
"image_path": "9ac4db9197801de4a20dbc9ea17bc0c53afb7290dc8b5b45d9e92e830566cb14.jpg"
}
]
}
]
},
{
"bbox": [
310,
630,
563,
666
],
"type": "image_caption",
"lines": [
{
"bbox": [
312,
631,
562,
641
],
"spans": [
{
"bbox": [
312,
631,
562,
641
],
"score": 0.94,
"content": "Figure 4:Optimal values of the feedback coefficient \\ cor-",
"type": "text"
}
]
},
{
"bbox": [
312,
644,
561,
652
],
"spans": [
{
"bbox": [
312,
644,
561,
652
],
"score": 0.97,
"content": "responding to the smallest mean squared error (MSE)of the",
"type": "text"
}
]
},
{
"bbox": [
312,
655,
513,
665
],
"spans": [
{
"bbox": [
312,
655,
513,
665
],
"score": 0.97,
"content": "disparity estimates for a range of noise strengths.",
"type": "text"
}
]
}
]
}
]
}
],
"tables": [],
"interline_equations": [],
"discarded_blocks": [],
"need_drop": false,
"drop_reason": [],
"para_blocks": [
{
"type": "text",
"bbox": [
47,
57,
299,
93
],
"lines": [
{
"bbox": [
47,
57,
299,
68
],
"spans": [
{
"bbox": [
49,
57,
298,
68
],
"score": 0.98,
"content": "of the synthetic stereo scene from a single camera perspective",
"type": "text"
}
]
},
{
"bbox": [
47,
71,
299,
80
],
"spans": [
{
"bbox": [
49,
71,
299,
80
],
"score": 0.96,
"content": "along with the ground truth disparity,occlusion map,and",
"type": "text"
}
]
},
{
"bbox": [
47,
82,
123,
93
],
"spans": [
{
"bbox": [
49,
82,
123,
93
],
"score": 0.99,
"content": "discontinuitymap.",
"type": "text"
}
]
}
]
},
{
"type": "image",
"bbox": [
47,
100,
301,
535
],
"blocks": [
{
"bbox": [
51,
100,
292,
484
],
"type": "image_body",
"lines": [
{
"bbox": [
51,
100,
292,
484
],
"spans": [
{
"bbox": [
51,
100,
292,
484
],
"score": 0.9999815225601196,
"type": "image",
"image_path": "b07d74524eac6f46b5505b48b1e10db23f2b45cb2d21d5fec72e967e61255811.jpg"
}
]
}
]
},
{
"bbox": [
47,
488,
301,
535
],
"type": "image_caption",
"lines": [
{
"bbox": [
49,
490,
299,
499
],
"spans": [
{
"bbox": [
49,
490,
299,
499
],
"score": 1.0,
"content": "Figure2:Twosampleframesfromthesyntheticvideose-",
"type": "text"
}
]
},
{
"bbox": [
48,
501,
300,
512
],
"spans": [
{
"bbox": [
48,
501,
300,
512
],
"score": 1.0,
"content": "quence (1st row), along with their corresponding ground truth",
"type": "text"
}
]
},
{
"bbox": [
48,
513,
299,
523
],
"spans": [
{
"bbox": [
48,
513,
299,
523
],
"score": 0.98,
"content": "disparity (2nd row), occlusion map (3rd row), and discontinuity",
"type": "text"
}
]
},
{
"bbox": [
48,
525,
110,
535
],
"spans": [
{
"bbox": [
48,
525,
110,
535
],
"score": 0.99,
"content": "map (4th row).",
"type": "text"
}
]
}
]
}
]
},
{
"type": "text",
"bbox": [
47,
549,
299,
678
],
"lines": [
{
"bbox": [
58,
549,
299,
558
],
"spans": [
{
"bbox": [
58,
549,
298,
558
],
"score": 0.98,
"content": "Theresultsof temporalstereomatching aregiveninFigure",
"type": "text"
}
]
},
{
"bbox": [
47,
561,
299,
570
],
"spans": [
{
"bbox": [
47,
561,
298,
570
],
"score": 0.98,
"content": "3foruniformadditivenoiseconfinedtotherangesof±O",
"type": "text"
}
]
},
{
"bbox": [
47,
573,
299,
582
],
"spans": [
{
"bbox": [
49,
573,
299,
582
],
"score": 0.96,
"content": "±20, and ±40. Each performance plot is given as a function",
"type": "text"
}
]
},
{
"bbox": [
47,
585,
299,
594
],
"spans": [
{
"bbox": [
48,
585,
299,
594
],
"score": 0.95,
"content": "of the feedback coefficient X. As with the majority of temporal",
"type": "text"
}
]
},
{
"bbox": [
47,
597,
299,
606
],
"spans": [
{
"bbox": [
49,
597,
299,
606
],
"score": 0.99,
"content": "stereomatching methods,improvements are negligible when",
"type": "text"
}
]
},
{
"bbox": [
47,
609,
299,
618
],
"spans": [
{
"bbox": [
48,
609,
299,
618
],
"score": 0.97,
"content": "no noise is added to the images [1o], [19]. This is largely due",
"type": "text"
}
]
},
{
"bbox": [
47,
621,
299,
629
],
"spans": [
{
"bbox": [
48,
621,
299,
629
],
"score": 1.0,
"content": "tothefactthatthevideousedtoevaluatethesemethodsis",
"type": "text"
}
]
},
{
"bbox": [
47,
633,
299,
641
],
"spans": [
{
"bbox": [
48,
633,
299,
641
],
"score": 1.0,
"content": "computergeneratedwithverylittlenoisetostartwith,thus",
"type": "text"
}
]
},
{
"bbox": [
47,
644,
299,
654
],
"spans": [
{
"bbox": [
48,
644,
299,
654
],
"score": 0.98,
"content": "the noise suppression achieved with temporal stereo matching",
"type": "text"
}
]
},
{
"bbox": [
47,
657,
299,
666
],
"spans": [
{
"bbox": [
48,
657,
299,
666
],
"score": 0.98,
"content": "showslittletonoimprovementovermethodsthatoperate on",
"type": "text"
}
]
},
{
"bbox": [
47,
669,
113,
678
],
"spans": [
{
"bbox": [
48,
669,
113,
678
],
"score": 1.0,
"content": "pairsofimages.",
"type": "text"
}
]
}
]
},
{
"type": "text",
"bbox": [
47,
680,
299,
725
],
"lines": [
{
"bbox": [
58,
680,
299,
690
],
"spans": [
{
"bbox": [
59,
680,
298,
690
],
"score": 0.97,
"content": "Significantimprovementsin accuracy canbeseenin Figure",
"type": "text"
}
]
},
{
"bbox": [
47,
692,
299,
701
],
"spans": [
{
"bbox": [
48,
692,
298,
701
],
"score": 0.97,
"content": "3 when the noise has ranges of ±20, and ±40.In this scenario",
"type": "text"
}
]
},
{
"bbox": [
47,
703,
299,
714
],
"spans": [
{
"bbox": [
48,
703,
299,
714
],
"score": 0.98,
"content": "the effect of noise in the current frame is reduced by increasing",
"type": "text"
}
]
},
{
"bbox": [
47,
716,
299,
725
],
"spans": [
{
"bbox": [
48,
716,
299,
725
],
"score": 0.96,
"content": "thefeedbackcoefficientX.Thisincreasing ofXhas theeffect",
"type": "text"
}
]
}
]
},
{
"type": "image",
"bbox": [
310,
55,
564,
371
],
"blocks": [
{
"bbox": [
314,
55,
538,
305
],
"type": "image_body",
"lines": [
{
"bbox": [
314,
55,
538,
305
],
"spans": [
{
"bbox": [
314,
55,
538,
305
],
"score": 0.9999905824661255,
"type": "image",
"image_path": "c7539af438972442d0f86aa46409e6684338ddfd1fbfd6bdacf02220853ccb55.jpg"
}
]
}
]
},
{
"bbox": [
310,
311,
564,
371
],
"type": "image_caption",
"lines": [
{
"bbox": [
312,
313,
562,
322
],
"spans": [
{
"bbox": [
312,
313,
562,
322
],
"score": 0.97,
"content": "Figure 3: Performance of temporal matching at different levels",
"type": "text"
}
]
},
{
"bbox": [
312,
325,
561,
334
],
"spans": [
{
"bbox": [
312,
325,
561,
334
],
"score": 0.98,
"content": "of uniformly distributed image noise{±0,±20,±40}.Mean",
"type": "text"
}
]
},
{
"bbox": [
311,
336,
563,
347
],
"spans": [
{
"bbox": [
311,
336,
563,
347
],
"score": 0.99,
"content": "squared error (MSE) of disparities is plotted versus the values",
"type": "text"
}
]
},
{
"bbox": [
311,
348,
561,
358
],
"spans": [
{
"bbox": [
311,
348,
561,
358
],
"score": 0.96,
"content": "of the feedback coefficient X. Dashed lines correspond to the",
"type": "text"
}
]
},
{
"bbox": [
311,
360,
535,
371
],
"spans": [
{
"bbox": [
311,
360,
535,
371
],
"score": 0.96,
"content": "values of MSE obtained without temporal aggregation.",
"type": "text"
}
]
}
]
}
]
},
{
"type": "image",
"bbox": [
310,
418,
563,
666
],
"blocks": [
{
"bbox": [
314,
418,
549,
623
],
"type": "image_body",
"lines": [
{
"bbox": [
314,
418,
549,
623
],
"spans": [
{
"bbox": [
314,
418,
549,
623
],
"score": 0.9999067783355713,
"type": "image",
"image_path": "9ac4db9197801de4a20dbc9ea17bc0c53afb7290dc8b5b45d9e92e830566cb14.jpg"
}
]
}
]
},
{
"bbox": [
310,
630,
563,
666
],
"type": "image_caption",
"lines": [
{
"bbox": [
312,
631,
562,
641
],
"spans": [
{
"bbox": [
312,
631,
562,
641
],
"score": 0.94,
"content": "Figure 4:Optimal values of the feedback coefficient \\ cor-",
"type": "text"
}
]
},
{
"bbox": [
312,
644,
561,
652
],
"spans": [
{
"bbox": [
312,
644,
561,
652
],
"score": 0.97,
"content": "responding to the smallest mean squared error (MSE)of the",
"type": "text"
}
]
},
{
"bbox": [
312,
655,
513,
665
],
"spans": [
{
"bbox": [
312,
655,
513,
665
],
"score": 0.97,
"content": "disparity estimates for a range of noise strengths.",
"type": "text"
}
]
}
]
}
]
},
{
"type": "text",
"bbox": [
311,
692,
563,
725
],
"lines": [
{
"bbox": [
311,
692,
563,
702
],
"spans": [
{
"bbox": [
311,
692,
562,
702
],
"score": 0.95,
"content": "of averaging out noise in the per-pixel costs by selecting",
"type": "text"
}
]
},
{
"bbox": [
311,
704,
563,
713
],
"spans": [
{
"bbox": [
311,
704,
562,
713
],
"score": 0.98,
"content": "matches based more heavily upon the auxiliary cost, which",
"type": "text"
}
]
},
{
"bbox": [
311,
716,
563,
725
],
"spans": [
{
"bbox": [
311,
716,
563,
725
],
"score": 0.97,
"content": "is essentially a much more stable running average of the cost",
"type": "text"
}
]
}
]
}
]
}
],
"_parse_type": "ocr",
"_version_name": "0.7.0b1"
}
tests/unittest/test_integrations/test_rag/test_api.py deleted 100644 → 0
View file @ 343eaac1
import json
import os
import shutil
import tempfile
from magic_pdf.integrations.rag.api import DataReader, RagDocumentReader
from magic_pdf.integrations.rag.type import CategoryType
from magic_pdf.integrations.rag.utils import \
convert_middle_json_to_layout_elements
def test_rag_document_reader():
# setup
unitest_dir = '/tmp/magic_pdf/unittest/integrations/rag'
os.makedirs(unitest_dir, exist_ok=True)
temp_output_dir = tempfile.mkdtemp(dir=unitest_dir)
os.makedirs(temp_output_dir, exist_ok=True)
# test
with open('tests/unittest/test_integrations/test_rag/assets/middle.json') as f:
json_data = json.load(f)
res = convert_middle_json_to_layout_elements(json_data, temp_output_dir)
doc = RagDocumentReader(res)
assert len(list(iter(doc))) == 1
page = list(iter(doc))[0]
assert len(list(iter(page))) >= 10
assert len(page.get_rel_map()) >= 3
item = list(iter(page))[0]
assert item.category_type == CategoryType.text
# teardown
shutil.rmtree(temp_output_dir)
def test_data_reader():
# setup
unitest_dir = '/tmp/magic_pdf/unittest/integrations/rag'
os.makedirs(unitest_dir, exist_ok=True)
temp_output_dir = tempfile.mkdtemp(dir=unitest_dir)
os.makedirs(temp_output_dir, exist_ok=True)
# test
data_reader = DataReader('tests/unittest/test_integrations/test_rag/assets', 'ocr',
temp_output_dir)
assert data_reader.get_documents_count() == 2
for idx in range(data_reader.get_documents_count()):
document = data_reader.get_document_result(idx)
assert document is not None
# teardown
shutil.rmtree(temp_output_dir)
tests/unittest/test_integrations/test_rag/test_utils.py deleted 100644 → 0
View file @ 343eaac1
import json
import os
import shutil
import tempfile
from magic_pdf.integrations.rag.type import CategoryType
from magic_pdf.integrations.rag.utils import (
convert_middle_json_to_layout_elements, inference)
def test_convert_middle_json_to_layout_elements():
# setup
unitest_dir = '/tmp/magic_pdf/unittest/integrations/rag'
os.makedirs(unitest_dir, exist_ok=True)
temp_output_dir = tempfile.mkdtemp(dir=unitest_dir)
os.makedirs(temp_output_dir, exist_ok=True)
# test
with open('tests/unittest/test_integrations/test_rag/assets/middle.json') as f:
json_data = json.load(f)
res = convert_middle_json_to_layout_elements(json_data, temp_output_dir)
assert len(res) == 1
assert len(res[0].layout_dets) > 0
assert res[0].layout_dets[0].anno_id == 0
assert res[0].layout_dets[0].category_type == CategoryType.text
assert len(res[0].extra.element_relation) >= 2
# teardown
shutil.rmtree(temp_output_dir)
def test_inference():
asset_dir = 'tests/unittest/test_integrations/test_rag/assets'
# setup
unitest_dir = '/tmp/magic_pdf/unittest/integrations/rag'
os.makedirs(unitest_dir, exist_ok=True)
temp_output_dir = tempfile.mkdtemp(dir=unitest_dir)
os.makedirs(temp_output_dir, exist_ok=True)
# test
res = inference(
asset_dir + '/one_page_with_table_image.pdf',
temp_output_dir,
'ocr',
)
assert res is not None
assert len(res) == 1
assert len(res[0].layout_dets) > 0
assert res[0].layout_dets[0].anno_id == 0
assert res[0].layout_dets[0].category_type == CategoryType.text
assert len(res[0].extra.element_relation) >= 2
# teardown
shutil.rmtree(temp_output_dir)
tests/unittest/test_metascan_classify/test_classify.py.bak deleted 100644 → 0
View file @ 343eaac1
import os
import pytest
from magic_pdf.filter.pdf_classify_by_type import classify_by_area, classify_by_text_len, classify_by_avg_words, \
classify_by_img_num, classify_by_text_layout, classify_by_img_narrow_strips
from magic_pdf.filter.pdf_meta_scan import get_pdf_page_size_pts, get_pdf_textlen_per_page, get_imgs_per_page
from test_commons import get_docs_from_test_pdf, get_test_json_data
# 获取当前目录
current_directory = os.path.dirname(os.path.abspath(__file__))
'''
根据图片尺寸占页面面积的比例，判断是否为扫描版
'''
@pytest.mark.parametrize("book_name, expected_bool_classify_by_area",
[
("the_eye/the_eye_cdn_00391653", True), # 特殊文字版1.每页存储所有图片，特点是图片占页面比例不大，每页展示可能为0也可能不止1张
("scihub/scihub_08400000/libgen.scimag08489000-08489999.zip_10.1016/0370-1573(90)90070-i", False), # 特殊扫描版2，每页存储的扫描页图片数量递增，特点是图占比大，每页展示1张
("zlib/zlib_17216416", False), # 特殊扫描版3，有的页面是一整张大图，有的页面是通过一条条小图拼起来的，检测图片占比之前需要先按规则把小图拼成大图
("the_eye/the_eye_wtl_00023799", False), # 特殊扫描版4，每一页都是一张张小图拼出来的，检测图片占比之前需要先按规则把小图拼成大图
("the_eye/the_eye_cdn_00328381", False), # 特殊扫描版5，每一页都是一张张小图拼出来的，存在多个小图多次重复使用情况，检测图片占比之前需要先按规则把小图拼成大图
("scihub/scihub_25800000/libgen.scimag25889000-25889999.zip_10.2307/4153991", False), # 特殊扫描版6，只有三页，其中两页是扫描版
("scanned_detection/llm-raw-scihub-o.O-0584-8539%2891%2980165-f", False), # 特殊扫描版7，只有一页且由小图拼成大图
("scanned_detection/llm-raw-scihub-o.O-bf01427123", False), # 特殊扫描版8，只有3页且全是大图扫描版
("scihub/scihub_41200000/libgen.scimag41253000-41253999.zip_10.1080/00222938709460256", False), # 特殊扫描版12，头两页文字版且有一页没图片，后面扫描版11页
("scihub/scihub_37000000/libgen.scimag37068000-37068999.zip_10.1080/0015587X.1936.9718622", False) # 特殊扫描版13，头两页文字版且有一页没图片，后面扫描版3页
])
def test_classify_by_area(book_name, expected_bool_classify_by_area):
test_data = get_test_json_data(current_directory, "test_metascan_classify_data.json")
docs = get_docs_from_test_pdf(book_name)
median_width, median_height = get_pdf_page_size_pts(docs)
page_width = int(median_width)
page_height = int(median_height)
img_sz_list = test_data[book_name]["expected_image_info"]
total_page = len(docs)
text_len_list = get_pdf_textlen_per_page(docs)
bool_classify_by_area = classify_by_area(total_page, page_width, page_height, img_sz_list, text_len_list)
# assert bool_classify_by_area == expected_bool_classify_by_area
'''
广义上的文字版检测，任何一页大于100字，都认为为文字版
'''
@pytest.mark.parametrize("book_name, expected_bool_classify_by_text_len",
[
("scihub/scihub_67200000/libgen.scimag67237000-67237999.zip_10.1515/crpm-2017-0020", True), # 文字版，少于50页
("scihub/scihub_83300000/libgen.scimag83306000-83306999.zip_10.1007/978-3-658-30153-8", True), # 文字版，多于50页
("zhongwenzaixian/zhongwenzaixian_65771414", False), # 完全无字的宣传册
])
def test_classify_by_text_len(book_name, expected_bool_classify_by_text_len):
docs = get_docs_from_test_pdf(book_name)
text_len_list = get_pdf_textlen_per_page(docs)
total_page = len(docs)
bool_classify_by_text_len = classify_by_text_len(text_len_list, total_page)
# assert bool_classify_by_text_len == expected_bool_classify_by_text_len
'''
狭义上的文字版检测，需要平均每页字数大于200字
'''
@pytest.mark.parametrize("book_name, expected_bool_classify_by_avg_words",
[
("zlib/zlib_21207669", False), # 扫描版，书末尾几页有大纲文字
("zlib/zlib_19012845", False), # 扫描版，好几本扫描书的集合，每本书末尾有一页文字页
("scihub/scihub_67200000/libgen.scimag67237000-67237999.zip_10.1515/crpm-2017-0020", True),# 正常文字版
("zhongwenzaixian/zhongwenzaixian_65771414", False), # 宣传册
("zhongwenzaixian/zhongwenzaixian_351879", False), # 图解书/无字or少字
("zhongwenzaixian/zhongwenzaixian_61357496_pdfvector", False), # 书法集
("zhongwenzaixian/zhongwenzaixian_63684541", False), # 设计图
("zhongwenzaixian/zhongwenzaixian_61525978", False), # 绘本
("zhongwenzaixian/zhongwenzaixian_63679729", False), # 摄影集
])
def test_classify_by_avg_words(book_name, expected_bool_classify_by_avg_words):
docs = get_docs_from_test_pdf(book_name)
text_len_list = get_pdf_textlen_per_page(docs)
bool_classify_by_avg_words = classify_by_avg_words(text_len_list)
# assert bool_classify_by_avg_words == expected_bool_classify_by_avg_words
'''
这个规则只针对特殊扫描版1，因为扫描版1的图片信息都由于junk_list的原因被舍弃了，只能通过图片数量来判断
'''
@pytest.mark.parametrize("book_name, expected_bool_classify_by_img_num",
[
("zlib/zlib_21370453", False), # 特殊扫描版1，每页都有所有扫描页图片，特点是图占比大，每页展示1至n张
("zlib/zlib_22115997", False), # 特殊扫描版2，类似特1，但是每页数量不完全相等
("zlib/zlib_21814957", False), # 特殊扫描版3，类似特1，但是每页数量不完全相等
("zlib/zlib_21814955", False), # 特殊扫描版4，类似特1，但是每页数量不完全相等
])
def test_classify_by_img_num(book_name, expected_bool_classify_by_img_num):
test_data = get_test_json_data(current_directory, "test_metascan_classify_data.json")
docs = get_docs_from_test_pdf(book_name)
img_num_list = get_imgs_per_page(docs)
img_sz_list = test_data[book_name]["expected_image_info"]
bool_classify_by_img_num = classify_by_img_num(img_sz_list, img_num_list)
# assert bool_classify_by_img_num == expected_bool_classify_by_img_num
'''
排除纵向排版的pdf
'''
@pytest.mark.parametrize("book_name, expected_bool_classify_by_text_layout",
[
("vertical_detection/三国演义_繁体竖排版", False), # 竖排版本1
("vertical_detection/净空法师_大乘无量寿", False), # 竖排版本2
("vertical_detection/om3006239", True), # 横排版本1
("vertical_detection/isit.2006.261791", True), # 横排版本2
])
def test_classify_by_text_layout(book_name, expected_bool_classify_by_text_layout):
test_data = get_test_json_data(current_directory, "test_metascan_classify_data.json")
text_layout_per_page = test_data[book_name]["expected_text_layout"]
bool_classify_by_text_layout = classify_by_text_layout(text_layout_per_page)
# assert bool_classify_by_text_layout == expected_bool_classify_by_text_layout
'''
通过检测页面是否由多个窄长条图像组成，来过滤特殊的扫描版
这个规则只对窄长条组成的pdf进行识别，而不会识别常规的大图扫描pdf
'''
@pytest.mark.parametrize("book_name, expected_bool_classify_by_img_narrow_strips",
[
("scihub/scihub_25900000/libgen.scimag25991000-25991999.zip_10.2307/40066695", False), # 特殊扫描版
("the_eye/the_eye_wtl_00023799", False), # 特殊扫描版4，每一页都是一张张小图拼出来的，检测图片占比之前需要先按规则把小图拼成大图
("the_eye/the_eye_cdn_00328381", False), # 特殊扫描版5，每一页都是一张张小图拼出来的，存在多个小图多次重复使用情况，检测图片占比之前需要先按规则把小图拼成大图
("scanned_detection/llm-raw-scihub-o.O-0584-8539%2891%2980165-f", False), # 特殊扫描版7，只有一页且由小图拼成大图
("scihub/scihub_25800000/libgen.scimag25889000-25889999.zip_10.2307/4153991", True), # 特殊扫描版6，只有三页，其中两页是扫描版
("scanned_detection/llm-raw-scihub-o.O-bf01427123", True), # 特殊扫描版8，只有3页且全是大图扫描版
("scihub/scihub_53700000/libgen.scimag53724000-53724999.zip_10.1097/00129191-200509000-00018", True), # 特殊文本版，有一长条，但是只有一条
])
def test_classify_by_img_narrow_strips(book_name, expected_bool_classify_by_img_narrow_strips):
test_data = get_test_json_data(current_directory, "test_metascan_classify_data.json")
img_sz_list = test_data[book_name]["expected_image_info"]
docs = get_docs_from_test_pdf(book_name)
median_width, median_height = get_pdf_page_size_pts(docs)
page_width = int(median_width)
page_height = int(median_height)
bool_classify_by_img_narrow_strips = classify_by_img_narrow_strips(page_width, page_height, img_sz_list)
# assert bool_classify_by_img_narrow_strips == expected_bool_classify_by_img_narrow_strips
\ No newline at end of file
tests/unittest/test_metascan_classify/test_commons.py.bak deleted 100644 → 0
View file @ 343eaac1
import io
import json
import os
import fitz
import boto3
from botocore.config import Config
from magic_pdf.libs.config_reader import get_s3_config_dict
from magic_pdf.libs.commons import join_path, json_dump_path, read_file, parse_bucket_key
from loguru import logger
test_pdf_dir_path = "s3://llm-pdf-text/unittest/pdf/"
def get_test_pdf_json(book_name):
json_path = join_path(json_dump_path, book_name + ".json")
s3_config = get_s3_config_dict(json_path)
file_content = read_file(json_path, s3_config)
json_str = file_content.decode('utf-8')
json_object = json.loads(json_str)
return json_object
def read_test_file(book_name):
test_pdf_path = join_path(test_pdf_dir_path, book_name + ".pdf")
s3_config = get_s3_config_dict(test_pdf_path)
try:
file_content = read_file(test_pdf_path, s3_config)
return file_content
except Exception as e:
if "NoSuchKey" in str(e):
logger.warning("File not found in test_pdf_path. Downloading from orig_s3_pdf_path.")
try:
json_object = get_test_pdf_json(book_name)
orig_s3_pdf_path = json_object.get('file_location')
s3_config = get_s3_config_dict(orig_s3_pdf_path)
file_content = read_file(orig_s3_pdf_path, s3_config)
s3_client = get_s3_client(test_pdf_path)
bucket_name, bucket_key = parse_bucket_key(test_pdf_path)
file_obj = io.BytesIO(file_content)
s3_client.upload_fileobj(file_obj, bucket_name, bucket_key)
return file_content
except Exception as e:
logger.exception(e)
else:
logger.exception(e)
def get_docs_from_test_pdf(book_name):
file_content = read_test_file(book_name)
return fitz.open("pdf", file_content)
def get_test_json_data(directory_path, json_file_name):
with open(os.path.join(directory_path, json_file_name), "r", encoding='utf-8') as f:
test_data = json.load(f)
return test_data
def get_s3_client(path):
s3_config = get_s3_config_dict(path)
try:
return boto3.client(
"s3",
aws_access_key_id=s3_config["ak"],
aws_secret_access_key=s3_config["sk"],
endpoint_url=s3_config["endpoint"],
config=Config(s3={"addressing_style": "path"}, retries={"max_attempts": 8, "mode": "standard"}),
)
except:
# older boto3 do not support retries.mode param.
return boto3.client(
"s3",
aws_access_key_id=s3_config["ak"],
aws_secret_access_key=s3_config["sk"],
endpoint_url=s3_config["endpoint"],
config=Config(s3={"addressing_style": "path"}, retries={"max_attempts": 8}),
)
tests/unittest/test_metascan_classify/test_meta_scan.py.bak deleted 100644 → 0
View file @ 343eaac1
import os
import pytest
from magic_pdf.filter.pdf_meta_scan import get_pdf_page_size_pts, get_image_info, get_pdf_text_layout_per_page, get_language
from test_commons import get_docs_from_test_pdf, get_test_json_data
# 获取当前目录
current_directory = os.path.dirname(os.path.abspath(__file__))
'''
获取pdf的宽与高，宽和高各用一个list，分别取中位数
'''
@pytest.mark.parametrize("book_name, expected_width, expected_height",
[
("zlib/zlib_17058115", 795, 1002), # pdf中最大页与最小页差异极大个例
("the_eye/the_eye_wtl_00023799", 616, 785) # 采样的前50页存在中位数大小页面横竖旋转情况
])
def test_get_pdf_page_size_pts(book_name, expected_width, expected_height):
docs = get_docs_from_test_pdf(book_name)
median_width, median_height = get_pdf_page_size_pts(docs)
# assert int(median_width) == expected_width
# assert int(median_height) == expected_height
'''
获取pdf前50页的图片信息，为了提速，对特殊扫描版1的情况做了过滤，其余情况都正常取图片信息
'''
@pytest.mark.parametrize("book_name",
[
"zlib/zlib_21370453", # 特殊扫描版1，每页都有所有扫描页图片，特点是图占比大，每页展示1至n张
"the_eye/the_eye_cdn_00391653", # 特殊文字版1.每页存储所有图片，特点是图片占页面比例不大，每页展示可能为0也可能不止1张，这种pdf需要拿前10页抽样检测img大小和个数，如果符合需要清空junklist
"scihub/scihub_08400000/libgen.scimag08489000-08489999.zip_10.1016/0370-1573(90)90070-i", # 扫描版2，每页存储的扫描页图片数量递增，特点是图占比大，每页展示1张，需要清空junklist跑前50页图片信息用于分类判断
"zlib/zlib_17216416", # 特殊扫描版3，有的页面是一整张大图，有的页面是通过一条条小图拼起来的
"the_eye/the_eye_wtl_00023799", # 特殊扫描版4，每一页都是一张张小图拼出来的
"the_eye/the_eye_cdn_00328381", # 特殊扫描版5，每一页都是一张张小图拼出来的，但是存在多个小图多次重复使用情况
"scihub/scihub_25800000/libgen.scimag25889000-25889999.zip_10.2307/4153991", # 特殊扫描版6，只有3页且其中两页是扫描页
"scanned_detection/llm-raw-scihub-o.O-0584-8539%2891%2980165-f", # 特殊扫描版7，只有一页，且是一张张小图拼出来的
"scanned_detection/llm-raw-scihub-o.O-bf01427123", # 特殊扫描版8，只有3页且全是大图扫描版
"zlib/zlib_22115997", # 特殊扫描版9，类似特1，但是每页数量不完全相等
"zlib/zlib_21814957", # 特殊扫描版10，类似特1，但是每页数量不完全相等
"zlib/zlib_21814955", # 特殊扫描版11，类似特1，但是每页数量不完全相等
"scihub/scihub_41200000/libgen.scimag41253000-41253999.zip_10.1080/00222938709460256", # 特殊扫描版12，头两页文字版且有一页没图片，后面扫描版11页
"scihub/scihub_37000000/libgen.scimag37068000-37068999.zip_10.1080/0015587X.1936.9718622" # 特殊扫描版13，头两页文字版且有一页没图片，后面扫描版3页
])
def test_get_image_info(book_name):
test_data = get_test_json_data(current_directory, "test_metascan_classify_data.json")
docs = get_docs_from_test_pdf(book_name)
page_width_pts, page_height_pts = get_pdf_page_size_pts(docs)
image_info, junk_img_bojids = get_image_info(docs, page_width_pts, page_height_pts)
# assert image_info == test_data[book_name]["expected_image_info"]
# assert junk_img_bojids == test_data[book_name]["expected_junk_img_bojids"]
'''
获取pdf前50页的文本布局信息，输出list，每个元素为一个页面的横竖排信息
'''
@pytest.mark.parametrize("book_name",
[
"vertical_detection/三国演义_繁体竖排版", # 竖排版本1
"vertical_detection/净空法师_大乘无量寿", # 竖排版本2
"vertical_detection/om3006239", # 横排版本1
"vertical_detection/isit.2006.261791" # 横排版本2
])
def test_get_text_layout_info(book_name):
test_data = get_test_json_data(current_directory, "test_metascan_classify_data.json")
docs = get_docs_from_test_pdf(book_name)
text_layout_info = get_pdf_text_layout_per_page(docs)
# assert text_layout_info == test_data[book_name]["expected_text_layout"]
'''
获取pdf的语言信息
'''
@pytest.mark.parametrize("book_name, expected_language",
[
("scihub/scihub_05000000/libgen.scimag05023000-05023999.zip_10.1034/j.1601-0825.2003.02933.x", "en"), # 英文论文
])
def test_get_text_language_info(book_name, expected_language):
docs = get_docs_from_test_pdf(book_name)
text_language = get_language(docs)
# assert text_language == expected_language
tests/unittest/test_metascan_classify/test_metascan_classify_data.json deleted 100644 → 0
View file @ 343eaac1
{
"zlib/zlib_21370453": {
"expected_image_info": [[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []],
"expected_junk_img_bojids": [3259, 3268, 3358, 3359, 3360, 3361, 3362, 3363, 3364, 3365, 3366, 3367, 3269, 3368, 3369, 3370, 3371, 3372, 3373, 3374, 3375, 3376, 3377, 3270, 3378, 3379, 3380, 3381, 3382, 3383, 3384, 3385, 3386, 3387, 3271, 3388, 3389, 3390, 3391, 3392, 3393, 3394, 3395, 3396, 3397, 3272, 3398, 3399, 3400, 3401, 3402, 3403, 3404, 3405, 3406, 3407, 3273, 3408, 3409, 3410, 3411, 3412, 3413, 3414, 3415, 3416, 3417, 3274, 3418, 3419, 3420, 3421, 3422, 3423, 3424, 3425, 3426, 3427, 3275, 3428, 3429, 3430, 3431, 3432, 3433, 3434, 3435, 3436, 3437, 3276, 3438, 3439, 3440, 3441, 3442, 3443, 3444, 3445, 3446, 3447, 3277, 3448, 3449, 3450, 3451, 3452, 3453, 3454, 3455, 3456, 3457, 3260, 3278, 3458, 3459, 3460, 3461, 3462, 3463, 3464, 3465, 3466, 3467, 3279, 3468, 3469, 3470, 3471, 3472, 3473, 3474, 3475, 3476, 3477, 3280, 3478, 3479, 3480, 3481, 3482, 3483, 3484, 3485, 3486, 3487, 3281, 3488, 3489, 3490, 3491, 3492, 3493, 3494, 3495, 3496, 3497, 3282, 3498, 3499, 3500, 3501, 3502, 3503, 3504, 3505, 3506, 3507, 3283, 3508, 3509, 3510, 3511, 3512, 3513, 3514, 3515, 3516, 3517, 3284, 3518, 3519, 3520, 3521, 3522, 3523, 3524, 3525, 3526, 3527, 3285, 3528, 3529, 3530, 3531, 3532, 3533, 3534, 3535, 3536, 3537, 3286, 3538, 3539, 3540, 3541, 3542, 3543, 3544, 3545, 3546, 3547, 3287, 3548, 3549, 3550, 3551, 3552, 3553, 3554, 3555, 3556, 3557, 3261, 3288, 3558, 3559, 3560, 3289, 3290, 3291, 3292, 3293, 3294, 3295, 3296, 3297, 3262, 3298, 3299, 3300, 3301, 3302, 3303, 3304, 3305, 3306, 3307, 3263, 3308, 3309, 3310, 3311, 3312, 3313, 3314, 3315, 3316, 3317, 3264, 3318, 3319, 3320, 3321, 3322, 3323, 3324, 3325, 3326, 3327, 3265, 3328, 3329, 3330, 3331, 3332, 3333, 3334, 3335, 3336, 3337, 3266, 3338, 3339, 3340, 3341, 3342, 3343, 3344, 3345, 3346, 3347, 3267, 3348, 3349, 3350, 3351, 3352, 3353, 3354, 3355, 3356, 3357, 3561, 3563, 3565, 3567, 3569, 3571, 3573, 3575, 3577, 3579, 3581, 3583, 3585, 3587, 3589, 3591, 3593, 3595, 3597, 3599, 3601, 3603, 3605, 3607, 3609, 3611, 3613, 3615, 3617, 3619, 3621, 3623, 3625, 3627, 3629, 3631, 3633, 3635, 3637, 3639, 3641, 3643, 3645, 3647, 3649, 3651, 3653, 3655, 3657, 3659, 3661, 3663, 3665, 3667, 3669, 3671, 3673, 3675, 3677, 3679, 3681, 3683, 3685, 3687, 3689, 3691, 3693, 3695, 3697, 3699, 3701, 3703, 3705, 3707, 3709, 3711, 3713, 3715, 3717, 3719, 3721, 3723, 3725, 3727, 3729, 3731, 3733, 3735, 3737, 3739, 3741, 3743, 3745, 3747, 3749, 3751, 3753, 3755, 3757, 3759, 3761, 3763, 3765, 3767, 3769, 3771, 3773, 3775, 3777, 3779, 3781, 3783, 3785, 3787, 3789, 3791, 3793, 3795, 3797, 3799, 3801, 3803, 3805, 3807, 3809, 3811, 3813, 3815, 3817, 3819, 3821, 3823, 3825, 3827, 3829, 3831, 3833, 3835, 3837, 3839, 3841, 3843, 3845, 3847, 3849, 3851, 3853, 3855, 3857, 3859, 3861, 3863, 3865, 3867, 3869, 3871, 3873, 3875, 3877, 3879, 3881, 3883, 3885, 3887, 3889, 3891, 3893, 3895, 3897, 3899, 3901, 3903, 3905, 3907, 3909, 3911, 3913, 3915, 3917, 3919, 3921, 3923, 3925, 3927, 3929, 3931, 3933, 3935, 3937, 3939, 3941, 3943, 3945, 3947, 3949, 3951, 3953, 3955, 3957, 3959, 3961, 3963, 3965, 3967, 3969, 3971, 3973, 3975, 3977, 3979, 3981, 3983, 3985, 3987, 3989, 3991, 3993, 3995, 3997, 3999, 4001, 4003, 4005, 4007, 4009, 4011, 4013, 4015, 4017, 4019, 4021, 4023, 4025, 4027, 4029, 4031, 4033, 4035, 4037, 4039, 4041, 4043, 4045, 4047, 4049, 4051, 4053, 4055, 4057, 4059, 4061, 4063, 4065, 4067, 4069, 4071, 4073, 4075, 4077, 4079, 4081, 4083, 4085, 4087, 4089, 4091, 4093, 4095, 4097, 4099, 4101, 4103, 4105, 4107, 4109, 4111, 4113, 4115, 4117, 4119, 4121, 4123, 4125, 4127, 4129]
},
"the_eye/the_eye_cdn_00391653" : {
"expected_image_info": [[[54, 233, 558, 670, 3]], [[442, 104, 535, 268, 7]], [], [], [], [], [], [], [], [[324, 128, 557, 476, 25]], [[54, 129, 288, 313, 29], [54, 476, 287, 630, 30], [324, 266, 557, 403, 31]], [[54, 54, 287, 374, 37], [324, 53, 557, 288, 38]], [[324, 66, 557, 447, 43]], [[54, 78, 288, 306, 47], [54, 331, 287, 648, 48], [324, 179, 557, 300, 49], [324, 387, 557, 580, 50]], [[54, 254, 557, 672, 57]], [[54, 53, 287, 211, 61], [54, 386, 287, 688, 62]], [[63, 54, 548, 360, 67]], [[62, 54, 549, 489, 71]], [[324, 53, 557, 399, 75]], [[54, 117, 557, 323, 79]], [[68, 60, 275, 272, 83], [60, 347, 280, 617, 84], [340, 354, 541, 633, 85]], [], [[54, 442, 557, 687, 93]], [[49, 66, 282, 439, 97], [324, 441, 558, 658, 98]], [[54, 241, 287, 315, 103], [66, 516, 545, 690, 104]], [[54, 53, 557, 655, 109]], [[54, 50, 557, 689, 113]], [[324, 79, 557, 656, 117]], [[109, 54, 502, 685, 121]], [[54, 379, 288, 642, 125]], [], [[156, 49, 455, 617, 131]], [[54, 40, 557, 679, 135]], [[54, 166, 557, 665, 139]], [[67, 45, 544, 691, 143]], [[54, 43, 557, 694, 147]], [[54, 53, 557, 372, 151]], [], [], [], [], [[54, 153, 557, 659, 163]], [[54, 53, 287, 223, 167], [324, 273, 557, 422, 168], [324, 430, 557, 554, 169]], [[324, 466, 557, 641, 175]], [[49, 279, 283, 390, 179], [324, 54, 558, 568, 180]], [[54, 66, 287, 477, 185]], [[54, 87, 557, 459, 189]], [[173, 47, 438, 693, 193]], [[54, 79, 557, 571, 197]], [[54, 54, 557, 679, 201]]],
"expected_junk_img_bojids": []
},
"scihub/scihub_08400000/libgen.scimag08489000-08489999.zip_10.1016/0370-1573(90)90070-i" : {
"expected_image_info": [[[-10, -10, 590, 729, 1273]], [[-10, -10, 590, 729, 1277]], [[-10, -10, 590, 729, 807]], [[-10, -10, 590, 729, 809]], [[-10, -10, 590, 729, 811]], [[-10, -10, 590, 729, 813]], [[-10, -10, 590, 729, 815]], [[-10, -10, 590, 729, 817]], [[-10, -10, 590, 729, 819]], [[-10, -10, 590, 729, 821]], [[-10, -10, 590, 729, 823]], [[-10, -10, 590, 729, 825]], [[-10, -10, 590, 729, 827]], [[-10, -10, 590, 729, 829]], [[-10, -10, 590, 729, 831]], [[-10, -10, 590, 729, 833]], [[-10, -10, 590, 729, 835]], [[-10, -10, 590, 729, 837]], [[-10, -10, 590, 729, 839]], [[-10, -10, 590, 729, 841]], [[-10, -10, 590, 729, 843]], [[-10, -10, 590, 729, 845]], [[-10, -10, 590, 729, 847]], [[-10, -10, 590, 729, 849]], [[-10, -10, 590, 729, 851]], [[-10, -10, 590, 729, 853]], [[-10, -10, 590, 729, 855]], [[-10, -10, 590, 729, 857]], [[-10, -10, 590, 729, 859]], [[-10, -10, 590, 729, 861]], [[-10, -10, 590, 729, 863]], [[-10, -10, 590, 729, 865]], [[-10, -10, 590, 729, 867]], [[-10, -10, 590, 729, 869]], [[-10, -10, 590, 729, 871]], [[-10, -10, 590, 729, 873]], [[-10, -10, 590, 729, 875]], [[-10, -10, 590, 729, 877]], [[-10, -10, 590, 729, 879]], [[-10, -10, 590, 729, 881]], [[-10, -10, 590, 729, 883]], [[-10, -10, 590, 729, 885]], [[-10, -10, 590, 729, 887]], [[-10, -10, 590, 729, 889]], [[-10, -10, 590, 729, 891]], [[-10, -10, 590, 729, 893]], [[-10, -10, 590, 729, 895]], [[-10, -10, 590, 729, 897]], [[-10, -10, 590, 729, 899]], [[-10, -10, 590, 729, 901]]],
"expected_junk_img_bojids": []
},
"zlib/zlib_17216416" : {
"expected_image_info": [[[0, 0, 531, 720, 36742]], [[0, 0, 529, 28, 59], [0, 28, 529, 57, 61], [0, 57, 529, 86, 63], [0, 86, 529, 115, 65], [0, 114, 529, 143, 67], [0, 143, 529, 172, 69], [0, 172, 529, 201, 71], [0, 201, 529, 230, 73], [0, 230, 529, 259, 75], [0, 259, 529, 287, 77], [0, 287, 529, 316, 79], [0, 345, 529, 374, 83], [0, 403, 529, 431, 87], [0, 431, 529, 460, 89], [0, 547, 529, 575, 97], [0, 575, 529, 604, 99], [0, 604, 529, 633, 101], [0, 633, 529, 662, 103], [0, 662, 529, 691, 105], [0, 691, 529, 719, 107], [0, 719, 529, 737, 109]], [[0, 0, 519, 28, 131], [0, 28, 519, 57, 133], [0, 57, 519, 86, 135], [0, 86, 519, 115, 137], [0, 115, 519, 144, 139], [0, 143, 519, 172, 141], [0, 172, 519, 201, 143], [0, 201, 519, 230, 145], [0, 230, 519, 259, 147], [0, 288, 519, 316, 151], [0, 316, 519, 345, 153], [0, 345, 519, 374, 155], [0, 374, 519, 403, 157], [0, 403, 519, 432, 159], [0, 460, 519, 489, 163], [0, 489, 519, 518, 165], [0, 518, 519, 547, 167], [0, 547, 519, 576, 169], [0, 576, 519, 604, 171], [0, 604, 519, 633, 173], [0, 633, 519, 662, 175], [0, 662, 519, 691, 177], [0, 691, 519, 720, 179]], [[0, 0, 528, 28, 201], [0, 28, 528, 57, 203], [0, 57, 528, 86, 205], [0, 85, 528, 114, 207], [0, 114, 528, 143, 209], [0, 143, 528, 172, 211], [0, 172, 528, 201, 213], [0, 201, 528, 230, 215], [0, 229, 528, 258, 217], [0, 258, 528, 287, 219], [0, 287, 528, 316, 221], [0, 316, 528, 345, 223], [0, 345, 528, 374, 225], [0, 374, 528, 402, 227], [0, 402, 528, 431, 229], [0, 431, 528, 460, 231], [0, 460, 528, 489, 233], [0, 489, 528, 518, 235], [0, 518, 528, 546, 237], [0, 546, 528, 575, 239], [0, 575, 528, 604, 241], [0, 604, 528, 633, 243], [0, 633, 528, 662, 245], [0, 662, 528, 690, 247], [0, 690, 528, 719, 249], [0, 719, 528, 737, 251]], [[0, 0, 528, 29, 273], [0, 57, 528, 86, 277], [0, 86, 528, 115, 279], [0, 115, 528, 144, 281], [0, 144, 528, 173, 283], [0, 173, 528, 202, 285], [0, 201, 528, 230, 287], [0, 230, 528, 259, 289], [0, 259, 528, 288, 291], [0, 288, 528, 317, 293], [0, 317, 528, 346, 295], [0, 346, 528, 374, 297], [0, 374, 528, 403, 299], [0, 403, 528, 432, 301], [0, 432, 528, 461, 303], [0, 576, 528, 605, 313], [0, 662, 528, 691, 319], [0, 691, 528, 720, 321], [0, 720, 528, 736, 323]], [[0, 0, 529, 29, 345], [0, 29, 529, 58, 347], [0, 57, 529, 86, 349], [0, 86, 529, 115, 351], [0, 115, 529, 144, 353], [0, 144, 529, 173, 355], [0, 173, 529, 202, 357], [0, 201, 529, 230, 359], [0, 230, 529, 259, 361], [0, 259, 529, 288, 363], [0, 288, 529, 317, 365], [0, 317, 529, 346, 367], [0, 346, 529, 374, 369], [0, 374, 529, 403, 371], [0, 403, 529, 432, 373], [0, 432, 529, 461, 375], [0, 461, 529, 490, 377], [0, 490, 529, 518, 379], [0, 518, 529, 547, 381], [0, 547, 529, 576, 383], [0, 576, 529, 605, 385], [0, 605, 529, 634, 387], [0, 634, 529, 662, 389], [0, 662, 529, 691, 391], [0, 691, 529, 720, 393], [0, 720, 529, 740, 395]], [[0, 0, 519, 29, 417], [0, 29, 519, 58, 419], [0, 58, 519, 88, 421], [0, 88, 519, 117, 423], [0, 117, 519, 147, 425], [0, 147, 519, 176, 427], [0, 176, 519, 205, 429], [0, 205, 519, 235, 431], [0, 235, 519, 264, 433], [0, 264, 519, 294, 435], [0, 294, 519, 323, 437], [0, 323, 519, 352, 439], [0, 352, 519, 382, 441], [0, 382, 519, 411, 443], [0, 411, 519, 441, 445], [0, 441, 519, 470, 447], [0, 470, 519, 499, 449], [0, 499, 519, 529, 451], [0, 529, 519, 558, 453], [0, 558, 519, 588, 455], [0, 588, 519, 617, 457], [0, 646, 519, 676, 461], [0, 705, 519, 734, 465]], [[0, 0, 529, 28, 487], [0, 28, 529, 57, 489], [0, 57, 529, 86, 491], [0, 86, 529, 115, 493], [0, 115, 529, 144, 495], [0, 143, 529, 172, 497], [0, 172, 529, 201, 499], [0, 201, 529, 230, 501], [0, 230, 529, 259, 503], [0, 259, 529, 288, 505], [0, 288, 529, 316, 507], [0, 316, 529, 345, 509], [0, 345, 529, 374, 511], [0, 374, 529, 403, 513], [0, 403, 529, 432, 515], [0, 432, 529, 460, 517], [0, 460, 529, 489, 519], [0, 489, 529, 518, 521], [0, 518, 529, 547, 523], [0, 547, 529, 576, 525], [0, 576, 529, 604, 527], [0, 604, 529, 633, 529], [0, 633, 529, 662, 531], [0, 662, 529, 691, 533], [0, 691, 529, 720, 535], [0, 720, 529, 739, 537]], [[0, 0, 519, 29, 559], [0, 29, 519, 58, 561], [0, 57, 519, 86, 563], [0, 86, 519, 115, 565], [0, 115, 519, 144, 567], [0, 144, 519, 173, 569], [0, 173, 519, 202, 571], [0, 201, 519, 230, 573], [0, 230, 519, 259, 575], [0, 259, 519, 288, 577], [0, 288, 519, 317, 579], [0, 317, 519, 346, 581], [0, 346, 519, 374, 583], [0, 374, 519, 403, 585], [0, 403, 519, 432, 587], [0, 432, 519, 461, 589], [0, 461, 519, 490, 591], [0, 490, 519, 518, 593], [0, 518, 519, 547, 595], [0, 547, 519, 576, 597], [0, 576, 519, 605, 599], [0, 605, 519, 634, 601], [0, 634, 519, 662, 603], [0, 691, 519, 720, 607]], [[0, 0, 519, 28, 629], [0, 28, 519, 57, 631], [0, 57, 519, 86, 633], [0, 86, 519, 115, 635], [0, 114, 519, 143, 637], [0, 143, 519, 172, 639], [0, 172, 519, 201, 641], [0, 201, 519, 230, 643], [0, 230, 519, 259, 645], [0, 259, 519, 287, 647], [0, 287, 519, 316, 649], [0, 316, 519, 345, 651], [0, 345, 519, 374, 653], [0, 374, 519, 403, 655], [0, 403, 519, 431, 657], [0, 431, 519, 460, 659], [0, 460, 519, 489, 661], [0, 489, 519, 518, 663], [0, 518, 519, 547, 665], [0, 547, 519, 575, 667], [0, 575, 519, 604, 669], [0, 604, 519, 633, 671], [0, 633, 519, 662, 673], [0, 662, 519, 691, 675], [0, 691, 519, 719, 677]], [[0, 0, 519, 29, 699], [0, 29, 519, 58, 701], [0, 58, 519, 88, 703], [0, 88, 519, 117, 705], [0, 117, 519, 147, 707], [0, 147, 519, 176, 709], [0, 176, 519, 205, 711], [0, 205, 519, 235, 713], [0, 235, 519, 264, 715], [0, 264, 519, 294, 717], [0, 294, 519, 323, 719], [0, 323, 519, 352, 721], [0, 352, 519, 382, 723], [0, 382, 519, 411, 725], [0, 411, 519, 441, 727], [0, 441, 519, 470, 729], [0, 470, 519, 499, 731], [0, 499, 519, 529, 733], [0, 529, 519, 558, 735], [0, 558, 519, 588, 737], [0, 588, 519, 617, 739], [0, 617, 519, 646, 741], [0, 646, 519, 676, 743], [0, 705, 519, 734, 747]], [[0, 0, 519, 28, 769], [0, 28, 519, 57, 771], [0, 57, 519, 86, 773], [0, 86, 519, 115, 775], [0, 114, 519, 143, 777], [0, 143, 519, 172, 779], [0, 172, 519, 201, 781], [0, 201, 519, 230, 783], [0, 230, 519, 259, 785], [0, 259, 519, 287, 787], [0, 287, 519, 316, 789], [0, 316, 519, 345, 791], [0, 345, 519, 374, 793], [0, 374, 519, 403, 795], [0, 403, 519, 431, 797], [0, 431, 519, 460, 799], [0, 460, 519, 489, 801], [0, 489, 519, 518, 803], [0, 518, 519, 547, 805], [0, 547, 519, 575, 807], [0, 575, 519, 604, 809], [0, 604, 519, 633, 811], [0, 633, 519, 662, 813], [0, 691, 519, 719, 817]], [[0, 0, 523, 28, 839], [0, 28, 523, 57, 841], [0, 57, 523, 86, 843], [0, 86, 523, 115, 845], [0, 115, 523, 144, 847], [0, 143, 523, 172, 849], [0, 172, 523, 201, 851], [0, 201, 523, 230, 853], [0, 230, 523, 259, 855], [0, 259, 523, 288, 857], [0, 288, 523, 316, 859], [0, 316, 523, 345, 861], [0, 345, 523, 374, 863], [0, 374, 523, 403, 865], [0, 403, 523, 432, 867], [0, 432, 523, 460, 869], [0, 460, 523, 489, 871], [0, 489, 523, 518, 873], [0, 518, 523, 547, 875], [0, 547, 523, 576, 877], [0, 576, 523, 604, 879], [0, 604, 523, 633, 881], [0, 633, 523, 662, 883], [0, 662, 523, 691, 885], [0, 720, 523, 734, 889]], [[0, 0, 525, 28, 911], [0, 57, 525, 86, 915], [0, 85, 525, 114, 917], [0, 114, 525, 143, 919], [0, 143, 525, 172, 921], [0, 172, 525, 201, 923], [0, 201, 525, 230, 925], [0, 229, 525, 258, 927], [0, 258, 525, 287, 929], [0, 287, 525, 316, 931], [0, 316, 525, 345, 933], [0, 345, 525, 374, 935], [0, 374, 525, 402, 937], [0, 431, 525, 460, 941], [0, 460, 525, 489, 943], [0, 489, 525, 518, 945], [0, 518, 525, 546, 947], [0, 546, 525, 575, 949], [0, 575, 525, 604, 951], [0, 662, 525, 690, 957], [0, 719, 525, 735, 961]], [[0, 0, 519, 28, 983], [0, 28, 519, 57, 985], [0, 57, 519, 86, 987], [0, 86, 519, 115, 989], [0, 115, 519, 144, 991], [0, 143, 519, 172, 993], [0, 172, 519, 201, 995], [0, 201, 519, 230, 997], [0, 230, 519, 259, 999], [0, 259, 519, 288, 1001], [0, 288, 519, 316, 1003], [0, 316, 519, 345, 1005], [0, 345, 519, 374, 1007], [0, 374, 519, 403, 1009], [0, 403, 519, 432, 1011], [0, 432, 519, 460, 1013], [0, 460, 519, 489, 1015], [0, 489, 519, 518, 1017], [0, 518, 519, 547, 1019], [0, 576, 519, 604, 1023], [0, 633, 519, 662, 1027], [0, 691, 519, 720, 1031]], [[0, 0, 525, 29, 1053], [0, 57, 525, 86, 1057], [0, 173, 525, 202, 1065], [0, 201, 525, 230, 1067], [0, 230, 525, 259, 1069], [0, 259, 525, 288, 1071], [0, 288, 525, 317, 1073], [0, 317, 525, 346, 1075], [0, 346, 525, 374, 1077], [0, 374, 525, 403, 1079], [0, 403, 525, 432, 1081], [0, 432, 525, 461, 1083], [0, 461, 525, 490, 1085], [0, 490, 525, 518, 1087], [0, 518, 525, 547, 1089], [0, 547, 525, 576, 1091], [0, 576, 525, 605, 1093], [0, 605, 525, 634, 1095], [0, 634, 525, 662, 1097], [0, 662, 525, 691, 1099], [0, 691, 525, 720, 1101], [0, 720, 525, 736, 1103]], [[0, 0, 519, 28, 1125], [0, 28, 519, 57, 1127], [0, 57, 519, 86, 1129], [0, 86, 519, 115, 1131], [0, 114, 519, 143, 1133], [0, 143, 519, 172, 1135], [0, 172, 519, 201, 1137], [0, 201, 519, 230, 1139], [0, 230, 519, 259, 1141], [0, 259, 519, 287, 1143], [0, 287, 519, 316, 1145], [0, 316, 519, 345, 1147], [0, 345, 519, 374, 1149], [0, 374, 519, 403, 1151], [0, 403, 519, 431, 1153], [0, 431, 519, 460, 1155], [0, 460, 519, 489, 1157], [0, 489, 519, 518, 1159], [0, 518, 519, 547, 1161], [0, 547, 519, 575, 1163], [0, 575, 519, 604, 1165], [0, 604, 519, 633, 1167], [0, 633, 519, 662, 1169], [0, 662, 519, 691, 1171], [0, 691, 519, 719, 1173]], [[0, 0, 525, 29, 1233], [0, 57, 525, 86, 1237], [0, 86, 525, 115, 1239], [0, 115, 525, 144, 1241], [0, 144, 525, 173, 1243], [0, 172, 525, 201, 1245], [0, 201, 525, 230, 1247], [0, 230, 525, 259, 1249], [0, 259, 525, 288, 1251], [0, 288, 525, 317, 1253], [0, 317, 525, 345, 1255], [0, 345, 525, 374, 1257], [0, 374, 525, 403, 1259], [0, 403, 525, 432, 1261], [0, 432, 525, 461, 1263], [0, 461, 525, 489, 1265], [0, 489, 525, 518, 1267], [0, 518, 525, 547, 1269], [0, 547, 525, 576, 1271], [0, 576, 525, 605, 1273], [0, 605, 525, 633, 1275], [0, 633, 525, 662, 1277], [0, 662, 525, 691, 1279], [0, 720, 525, 736, 1283]], [[0, 0, 523, 29, 1305], [0, 57, 523, 86, 1309], [0, 86, 523, 115, 1311], [0, 115, 523, 144, 1313], [0, 144, 523, 173, 1315], [0, 173, 523, 202, 1317], [0, 201, 523, 230, 1319], [0, 230, 523, 259, 1321], [0, 259, 523, 288, 1323], [0, 288, 523, 317, 1325], [0, 317, 523, 346, 1327], [0, 346, 523, 374, 1329], [0, 374, 523, 403, 1331], [0, 403, 523, 432, 1333], [0, 432, 523, 461, 1335], [0, 461, 523, 490, 1337], [0, 490, 523, 518, 1339], [0, 518, 523, 547, 1341], [0, 547, 523, 576, 1343], [0, 576, 523, 605, 1345], [0, 605, 523, 634, 1347], [0, 634, 523, 662, 1349], [0, 662, 523, 691, 1351], [0, 720, 523, 736, 1355]], [[0, 0, 528, 28, 1377], [0, 57, 528, 86, 1381], [0, 85, 528, 114, 1383], [0, 114, 528, 143, 1385], [0, 143, 528, 172, 1387], [0, 172, 528, 201, 1389], [0, 201, 528, 230, 1391], [0, 229, 528, 258, 1393], [0, 258, 528, 287, 1395], [0, 287, 528, 316, 1397], [0, 316, 528, 345, 1399], [0, 345, 528, 374, 1401], [0, 374, 528, 402, 1403], [0, 402, 528, 431, 1405], [0, 431, 528, 460, 1407], [0, 460, 528, 489, 1409], [0, 489, 528, 518, 1411], [0, 518, 528, 546, 1413], [0, 546, 528, 575, 1415], [0, 575, 528, 604, 1417], [0, 604, 528, 633, 1419], [0, 633, 528, 662, 1421], [0, 662, 528, 690, 1423], [0, 719, 528, 737, 1427]], [[0, 0, 519, 28, 1449], [0, 28, 519, 57, 1451], [0, 57, 519, 86, 1453], [0, 86, 519, 115, 1455], [0, 114, 519, 143, 1457], [0, 143, 519, 172, 1459], [0, 172, 519, 201, 1461], [0, 201, 519, 230, 1463], [0, 230, 519, 259, 1465], [0, 259, 519, 287, 1467], [0, 287, 519, 316, 1469], [0, 316, 519, 345, 1471], [0, 345, 519, 374, 1473], [0, 374, 519, 403, 1475], [0, 403, 519, 431, 1477], [0, 431, 519, 460, 1479], [0, 460, 519, 489, 1481], [0, 489, 519, 518, 1483], [0, 518, 519, 547, 1485], [0, 547, 519, 575, 1487], [0, 575, 519, 604, 1489], [0, 604, 519, 633, 1491], [0, 633, 519, 662, 1493], [0, 662, 519, 691, 1495], [0, 691, 519, 719, 1497]], [[0, 0, 529, 28, 1519], [0, 57, 529, 86, 1523], [0, 86, 529, 115, 1525], [0, 115, 529, 144, 1527], [0, 143, 529, 172, 1529], [0, 172, 529, 201, 1531], [0, 201, 529, 230, 1533], [0, 230, 529, 259, 1535], [0, 259, 529, 288, 1537], [0, 288, 529, 316, 1539], [0, 316, 529, 345, 1541], [0, 345, 529, 374, 1543], [0, 374, 529, 403, 1545], [0, 403, 529, 432, 1547], [0, 432, 529, 460, 1549], [0, 460, 529, 489, 1551], [0, 489, 529, 518, 1553], [0, 518, 529, 547, 1555], [0, 547, 529, 576, 1557], [0, 576, 529, 604, 1559], [0, 604, 529, 633, 1561], [0, 633, 529, 662, 1563], [0, 662, 529, 691, 1565], [0, 720, 529, 738, 1569]], [[0, 0, 525, 28, 1591], [0, 57, 525, 86, 1595], [0, 86, 525, 115, 1597], [0, 114, 525, 143, 1599], [0, 143, 525, 172, 1601], [0, 172, 525, 201, 1603], [0, 201, 525, 230, 1605], [0, 230, 525, 259, 1607], [0, 259, 525, 287, 1609], [0, 287, 525, 316, 1611], [0, 316, 525, 345, 1613], [0, 345, 525, 374, 1615], [0, 374, 525, 403, 1617], [0, 403, 525, 431, 1619], [0, 431, 525, 460, 1621], [0, 460, 525, 489, 1623], [0, 489, 525, 518, 1625], [0, 518, 525, 547, 1627], [0, 547, 525, 575, 1629], [0, 575, 525, 604, 1631], [0, 604, 525, 633, 1633], [0, 633, 525, 662, 1635], [0, 662, 525, 691, 1637], [0, 719, 525, 736, 1641]], [[0, 0, 528, 28, 1663], [0, 57, 528, 86, 1667], [0, 85, 528, 114, 1669], [0, 114, 528, 143, 1671], [0, 143, 528, 172, 1673], [0, 172, 528, 201, 1675], [0, 201, 528, 230, 1677], [0, 229, 528, 258, 1679], [0, 258, 528, 287, 1681], [0, 287, 528, 316, 1683], [0, 316, 528, 345, 1685], [0, 345, 528, 374, 1687], [0, 374, 528, 402, 1689], [0, 402, 528, 431, 1691], [0, 431, 528, 460, 1693], [0, 460, 528, 489, 1695], [0, 489, 528, 518, 1697], [0, 518, 528, 546, 1699], [0, 546, 528, 575, 1701], [0, 575, 528, 604, 1703], [0, 604, 528, 633, 1705], [0, 633, 528, 662, 1707], [0, 662, 528, 690, 1709], [0, 719, 528, 737, 1713]], [[0, 0, 519, 28, 1735], [0, 28, 519, 57, 1737], [0, 57, 519, 86, 1739], [0, 86, 519, 115, 1741], [0, 114, 519, 143, 1743], [0, 143, 519, 172, 1745], [0, 172, 519, 201, 1747], [0, 201, 519, 230, 1749], [0, 230, 519, 259, 1751], [0, 259, 519, 287, 1753], [0, 287, 519, 316, 1755], [0, 316, 519, 345, 1757], [0, 345, 519, 374, 1759], [0, 374, 519, 403, 1761], [0, 403, 519, 431, 1763], [0, 431, 519, 460, 1765], [0, 460, 519, 489, 1767], [0, 489, 519, 518, 1769], [0, 518, 519, 547, 1771], [0, 547, 519, 575, 1773], [0, 575, 519, 604, 1775], [0, 604, 519, 633, 1777], [0, 633, 519, 662, 1779], [0, 662, 519, 691, 1781], [0, 691, 519, 719, 1783]], [[0, 0, 525, 29, 1805], [0, 57, 525, 86, 1809], [0, 86, 525, 115, 1811], [0, 115, 525, 144, 1813], [0, 144, 525, 173, 1815], [0, 173, 525, 202, 1817], [0, 201, 525, 230, 1819], [0, 230, 525, 259, 1821], [0, 259, 525, 288, 1823], [0, 288, 525, 317, 1825], [0, 317, 525, 346, 1827], [0, 346, 525, 374, 1829], [0, 374, 525, 403, 1831], [0, 403, 525, 432, 1833], [0, 432, 525, 461, 1835], [0, 461, 525, 490, 1837], [0, 490, 525, 518, 1839], [0, 518, 525, 547, 1841], [0, 547, 525, 576, 1843], [0, 576, 525, 605, 1845], [0, 605, 525, 634, 1847], [0, 634, 525, 662, 1849], [0, 662, 525, 691, 1851], [0, 720, 525, 736, 1855]], [[0, 0, 519, 28, 1877], [0, 28, 519, 57, 1879], [0, 57, 519, 86, 1881], [0, 86, 519, 115, 1883], [0, 115, 519, 144, 1885], [0, 143, 519, 172, 1887], [0, 172, 519, 201, 1889], [0, 201, 519, 230, 1891], [0, 230, 519, 259, 1893], [0, 259, 519, 288, 1895], [0, 288, 519, 316, 1897], [0, 316, 519, 345, 1899], [0, 345, 519, 374, 1901], [0, 374, 519, 403, 1903], [0, 403, 519, 432, 1905], [0, 432, 519, 460, 1907], [0, 460, 519, 489, 1909], [0, 489, 519, 518, 1911], [0, 518, 519, 547, 1913], [0, 547, 519, 576, 1915], [0, 576, 519, 604, 1917], [0, 604, 519, 633, 1919], [0, 633, 519, 662, 1921], [0, 662, 519, 691, 1923], [0, 691, 519, 720, 1925]], [[0, 0, 525, 29, 1947], [0, 57, 525, 86, 1951], [0, 86, 525, 115, 1953], [0, 115, 525, 144, 1955], [0, 144, 525, 173, 1957], [0, 173, 525, 202, 1959], [0, 201, 525, 230, 1961], [0, 230, 525, 259, 1963], [0, 259, 525, 288, 1965], [0, 288, 525, 317, 1967], [0, 317, 525, 346, 1969], [0, 346, 525, 374, 1971], [0, 374, 525, 403, 1973], [0, 403, 525, 432, 1975], [0, 432, 525, 461, 1977], [0, 461, 525, 490, 1979], [0, 490, 525, 518, 1981], [0, 518, 525, 547, 1983], [0, 547, 525, 576, 1985], [0, 576, 525, 605, 1987], [0, 605, 525, 634, 1989], [0, 634, 525, 662, 1991], [0, 662, 525, 691, 1993], [0, 720, 525, 736, 1997]], [[0, 0, 519, 28, 2019], [0, 28, 519, 57, 2021], [0, 57, 519, 86, 2023], [0, 86, 519, 115, 2025], [0, 115, 519, 144, 2027], [0, 143, 519, 172, 2029], [0, 172, 519, 201, 2031], [0, 201, 519, 230, 2033], [0, 230, 519, 259, 2035], [0, 259, 519, 288, 2037], [0, 288, 519, 316, 2039], [0, 316, 519, 345, 2041], [0, 345, 519, 374, 2043], [0, 374, 519, 403, 2045], [0, 403, 519, 432, 2047], [0, 432, 519, 460, 2049], [0, 460, 519, 489, 2051], [0, 489, 519, 518, 2053], [0, 518, 519, 547, 2055], [0, 547, 519, 576, 2057], [0, 576, 519, 604, 2059], [0, 604, 519, 633, 2061], [0, 633, 519, 662, 2063], [0, 662, 519, 691, 2065], [0, 691, 519, 720, 2067]], [[0, 0, 525, 28, 2089], [0, 57, 525, 86, 2093], [0, 85, 525, 114, 2095], [0, 114, 525, 143, 2097], [0, 143, 525, 172, 2099], [0, 172, 525, 201, 2101], [0, 201, 525, 230, 2103], [0, 229, 525, 258, 2105], [0, 258, 525, 287, 2107], [0, 287, 525, 316, 2109], [0, 316, 525, 345, 2111], [0, 345, 525, 374, 2113], [0, 374, 525, 402, 2115], [0, 402, 525, 431, 2117], [0, 431, 525, 460, 2119], [0, 460, 525, 489, 2121], [0, 489, 525, 518, 2123], [0, 518, 525, 546, 2125], [0, 546, 525, 575, 2127], [0, 575, 525, 604, 2129], [0, 604, 525, 633, 2131], [0, 633, 525, 662, 2133], [0, 662, 525, 690, 2135], [0, 719, 525, 735, 2139]], [[0, 0, 519, 28, 2197], [0, 28, 519, 57, 2199], [0, 57, 519, 86, 2201], [0, 85, 519, 114, 2203], [0, 114, 519, 143, 2205], [0, 143, 519, 172, 2207], [0, 172, 519, 201, 2209], [0, 201, 519, 230, 2211], [0, 229, 519, 258, 2213], [0, 258, 519, 287, 2215], [0, 287, 519, 316, 2217], [0, 316, 519, 345, 2219], [0, 345, 519, 374, 2221], [0, 374, 519, 402, 2223], [0, 402, 519, 431, 2225], [0, 431, 519, 460, 2227], [0, 460, 519, 489, 2229], [0, 489, 519, 518, 2231], [0, 518, 519, 546, 2233], [0, 546, 519, 575, 2235], [0, 575, 519, 604, 2237], [0, 604, 519, 633, 2239], [0, 633, 519, 662, 2241], [0, 662, 519, 690, 2243], [0, 690, 519, 719, 2245]], [[0, 0, 527, 29, 2305], [0, 57, 527, 86, 2309], [0, 86, 527, 115, 2311], [0, 115, 527, 144, 2313], [0, 144, 527, 173, 2315], [0, 172, 527, 201, 2317], [0, 201, 527, 230, 2319], [0, 230, 527, 259, 2321], [0, 259, 527, 288, 2323], [0, 288, 527, 317, 2325], [0, 317, 527, 345, 2327], [0, 345, 527, 374, 2329], [0, 374, 527, 403, 2331], [0, 403, 527, 432, 2333], [0, 432, 527, 461, 2335], [0, 461, 527, 489, 2337], [0, 489, 527, 518, 2339], [0, 518, 527, 547, 2341], [0, 547, 527, 576, 2343], [0, 576, 527, 605, 2345], [0, 605, 527, 633, 2347], [0, 633, 527, 662, 2349], [0, 662, 527, 691, 2351], [0, 720, 527, 738, 2355]], [[0, 0, 519, 28, 2377], [0, 28, 519, 57, 2379], [0, 57, 519, 86, 2381], [0, 85, 519, 114, 2383], [0, 114, 519, 143, 2385], [0, 143, 519, 172, 2387], [0, 172, 519, 201, 2389], [0, 201, 519, 230, 2391], [0, 229, 519, 258, 2393], [0, 258, 519, 287, 2395], [0, 287, 519, 316, 2397], [0, 316, 519, 345, 2399], [0, 345, 519, 374, 2401], [0, 374, 519, 402, 2403], [0, 402, 519, 431, 2405], [0, 431, 519, 460, 2407], [0, 460, 519, 489, 2409], [0, 489, 519, 518, 2411], [0, 518, 519, 546, 2413], [0, 546, 519, 575, 2415], [0, 575, 519, 604, 2417], [0, 604, 519, 633, 2419], [0, 633, 519, 662, 2421], [0, 662, 519, 690, 2423], [0, 690, 519, 719, 2425]], [[0, 0, 525, 29, 2447], [0, 29, 525, 58, 2449], [0, 57, 525, 86, 2451], [0, 86, 525, 115, 2453], [0, 115, 525, 144, 2455], [0, 144, 525, 173, 2457], [0, 173, 525, 202, 2459], [0, 201, 525, 230, 2461], [0, 230, 525, 259, 2463], [0, 259, 525, 288, 2465], [0, 288, 525, 317, 2467], [0, 317, 525, 346, 2469], [0, 346, 525, 374, 2471], [0, 374, 525, 403, 2473], [0, 403, 525, 432, 2475], [0, 432, 525, 461, 2477], [0, 461, 525, 490, 2479], [0, 490, 525, 518, 2481], [0, 518, 525, 547, 2483], [0, 547, 525, 576, 2485], [0, 576, 525, 605, 2487], [0, 605, 525, 634, 2489], [0, 634, 525, 662, 2491], [0, 662, 525, 691, 2493], [0, 720, 525, 736, 2497]], [[0, 0, 519, 28, 2519], [0, 28, 519, 57, 2521], [0, 57, 519, 86, 2523], [0, 85, 519, 114, 2525], [0, 114, 519, 143, 2527], [0, 143, 519, 172, 2529], [0, 172, 519, 201, 2531], [0, 201, 519, 230, 2533], [0, 229, 519, 258, 2535], [0, 258, 519, 287, 2537], [0, 287, 519, 316, 2539], [0, 316, 519, 345, 2541], [0, 345, 519, 374, 2543], [0, 374, 519, 402, 2545], [0, 402, 519, 431, 2547], [0, 431, 519, 460, 2549], [0, 460, 519, 489, 2551], [0, 489, 519, 518, 2553], [0, 518, 519, 546, 2555], [0, 546, 519, 575, 2557], [0, 575, 519, 604, 2559], [0, 604, 519, 633, 2561], [0, 633, 519, 662, 2563], [0, 662, 519, 690, 2565], [0, 690, 519, 719, 2567]], [[0, 0, 527, 28, 2589], [0, 57, 527, 86, 2593], [0, 86, 527, 115, 2595], [0, 115, 527, 144, 2597], [0, 143, 527, 172, 2599], [0, 172, 527, 201, 2601], [0, 201, 527, 230, 2603], [0, 230, 527, 259, 2605], [0, 259, 527, 288, 2607], [0, 288, 527, 316, 2609], [0, 316, 527, 345, 2611], [0, 345, 527, 374, 2613], [0, 374, 527, 403, 2615], [0, 403, 527, 432, 2617], [0, 432, 527, 460, 2619], [0, 460, 527, 489, 2621], [0, 489, 527, 518, 2623], [0, 518, 527, 547, 2625], [0, 547, 527, 576, 2627], [0, 576, 527, 604, 2629], [0, 604, 527, 633, 2631], [0, 633, 527, 662, 2633], [0, 662, 527, 691, 2635], [0, 720, 527, 738, 2639]], [[0, 0, 519, 28, 2661], [0, 57, 519, 86, 2665], [0, 86, 519, 115, 2667], [0, 115, 519, 144, 2669], [0, 143, 519, 172, 2671], [0, 172, 519, 201, 2673], [0, 201, 519, 230, 2675], [0, 230, 519, 259, 2677], [0, 259, 519, 288, 2679], [0, 288, 519, 316, 2681], [0, 316, 519, 345, 2683], [0, 345, 519, 374, 2685], [0, 374, 519, 403, 2687], [0, 403, 519, 432, 2689], [0, 432, 519, 460, 2691], [0, 460, 519, 489, 2693], [0, 489, 519, 518, 2695], [0, 518, 519, 547, 2697], [0, 547, 519, 576, 2699], [0, 576, 519, 604, 2701], [0, 604, 519, 633, 2703], [0, 633, 519, 662, 2705], [0, 662, 519, 691, 2707], [0, 691, 519, 720, 2709]], [[0, 0, 525, 29, 2731], [0, 29, 525, 58, 2733], [0, 57, 525, 86, 2735], [0, 86, 525, 115, 2737], [0, 115, 525, 144, 2739], [0, 144, 525, 173, 2741], [0, 173, 525, 202, 2743], [0, 201, 525, 230, 2745], [0, 230, 525, 259, 2747], [0, 259, 525, 288, 2749], [0, 288, 525, 317, 2751], [0, 317, 525, 346, 2753], [0, 346, 525, 374, 2755], [0, 374, 525, 403, 2757], [0, 403, 525, 432, 2759], [0, 432, 525, 461, 2761], [0, 576, 525, 605, 2771], [0, 662, 525, 691, 2777], [0, 720, 525, 736, 2781]], [[0, 0, 519, 28, 2803], [0, 28, 519, 57, 2805], [0, 57, 519, 86, 2807], [0, 85, 519, 114, 2809], [0, 114, 519, 143, 2811], [0, 143, 519, 172, 2813], [0, 172, 519, 201, 2815], [0, 201, 519, 230, 2817], [0, 229, 519, 258, 2819], [0, 258, 519, 287, 2821], [0, 287, 519, 316, 2823], [0, 316, 519, 345, 2825], [0, 345, 519, 374, 2827], [0, 374, 519, 402, 2829], [0, 402, 519, 431, 2831], [0, 431, 519, 460, 2833], [0, 460, 519, 489, 2835], [0, 489, 519, 518, 2837], [0, 518, 519, 546, 2839], [0, 546, 519, 575, 2841], [0, 575, 519, 604, 2843], [0, 604, 519, 633, 2845], [0, 633, 519, 662, 2847], [0, 690, 519, 719, 2851]], [[0, 0, 529, 29, 2873], [0, 57, 529, 86, 2877], [0, 201, 529, 230, 2887], [0, 230, 529, 259, 2889], [0, 259, 529, 288, 2891], [0, 288, 529, 317, 2893], [0, 317, 529, 345, 2895], [0, 345, 529, 374, 2897], [0, 374, 529, 403, 2899], [0, 403, 529, 432, 2901], [0, 432, 529, 461, 2903], [0, 461, 529, 489, 2905], [0, 489, 529, 518, 2907], [0, 518, 529, 547, 2909], [0, 547, 529, 576, 2911], [0, 576, 529, 605, 2913], [0, 605, 529, 633, 2915], [0, 633, 529, 662, 2917], [0, 662, 529, 691, 2919], [0, 691, 529, 720, 2921], [0, 720, 529, 740, 2923]], [[0, 0, 528, 29, 2945], [0, 57, 528, 86, 2949], [0, 86, 528, 115, 2951], [0, 115, 528, 144, 2953], [0, 144, 528, 173, 2955], [0, 173, 528, 202, 2957], [0, 201, 528, 230, 2959], [0, 230, 528, 259, 2961], [0, 259, 528, 288, 2963], [0, 288, 528, 317, 2965], [0, 317, 528, 346, 2967], [0, 346, 528, 374, 2969], [0, 374, 528, 403, 2971], [0, 403, 528, 432, 2973], [0, 432, 528, 461, 2975], [0, 461, 528, 490, 2977], [0, 490, 528, 518, 2979], [0, 518, 528, 547, 2981], [0, 547, 528, 576, 2983], [0, 576, 528, 605, 2985], [0, 605, 528, 634, 2987], [0, 634, 528, 662, 2989], [0, 662, 528, 691, 2991], [0, 720, 528, 736, 2995]], [[0, 0, 519, 29, 3017], [0, 58, 519, 88, 3021], [0, 88, 519, 117, 3023], [0, 117, 519, 147, 3025], [0, 147, 519, 176, 3027], [0, 176, 519, 205, 3029], [0, 205, 519, 235, 3031], [0, 235, 519, 264, 3033], [0, 264, 519, 294, 3035], [0, 294, 519, 323, 3037], [0, 323, 519, 352, 3039], [0, 352, 519, 382, 3041], [0, 382, 519, 411, 3043], [0, 411, 519, 441, 3045], [0, 441, 519, 470, 3047], [0, 470, 519, 499, 3049], [0, 499, 519, 529, 3051], [0, 529, 519, 558, 3053], [0, 558, 519, 588, 3055], [0, 588, 519, 617, 3057], [0, 617, 519, 646, 3059], [0, 646, 519, 676, 3061], [0, 676, 519, 705, 3063], [0, 705, 519, 734, 3065]], [[0, 0, 519, 29, 3087], [0, 29, 519, 58, 3089], [0, 57, 519, 86, 3091], [0, 86, 519, 115, 3093], [0, 115, 519, 144, 3095], [0, 144, 519, 173, 3097], [0, 173, 519, 202, 3099], [0, 201, 519, 230, 3101], [0, 230, 519, 259, 3103], [0, 259, 519, 288, 3105], [0, 288, 519, 317, 3107], [0, 317, 519, 346, 3109], [0, 346, 519, 374, 3111], [0, 374, 519, 403, 3113], [0, 403, 519, 432, 3115], [0, 432, 519, 461, 3117], [0, 461, 519, 490, 3119], [0, 490, 519, 518, 3121], [0, 518, 519, 547, 3123], [0, 547, 519, 576, 3125], [0, 576, 519, 605, 3127], [0, 605, 519, 634, 3129], [0, 634, 519, 662, 3131], [0, 662, 519, 691, 3133], [0, 691, 519, 720, 3135]], [[0, 0, 529, 29, 3157], [0, 57, 529, 86, 3161], [0, 86, 529, 115, 3163], [0, 115, 529, 144, 3165], [0, 144, 529, 173, 3167], [0, 172, 529, 201, 3169], [0, 201, 529, 230, 3171], [0, 230, 529, 259, 3173], [0, 259, 529, 288, 3175], [0, 288, 529, 317, 3177], [0, 317, 529, 345, 3179], [0, 345, 529, 374, 3181], [0, 374, 529, 403, 3183], [0, 403, 529, 432, 3185], [0, 432, 529, 461, 3187], [0, 461, 529, 489, 3189], [0, 489, 529, 518, 3191], [0, 518, 529, 547, 3193], [0, 547, 529, 576, 3195], [0, 576, 529, 605, 3197], [0, 605, 529, 633, 3199], [0, 633, 529, 662, 3201], [0, 662, 529, 691, 3203], [0, 720, 529, 740, 3207]], [[0, 0, 525, 29, 3229], [0, 29, 525, 58, 3231], [0, 57, 525, 86, 3233], [0, 86, 525, 115, 3235], [0, 115, 525, 144, 3237], [0, 144, 525, 173, 3239], [0, 173, 525, 202, 3241], [0, 201, 525, 230, 3243], [0, 230, 525, 259, 3245], [0, 259, 525, 288, 3247], [0, 288, 525, 317, 3249], [0, 317, 525, 346, 3251], [0, 346, 525, 374, 3253], [0, 374, 525, 403, 3255], [0, 403, 525, 432, 3257], [0, 432, 525, 461, 3259], [0, 461, 525, 490, 3261], [0, 490, 525, 518, 3263], [0, 518, 525, 547, 3265], [0, 547, 525, 576, 3267], [0, 576, 525, 605, 3269], [0, 605, 525, 634, 3271], [0, 634, 525, 662, 3273], [0, 662, 525, 691, 3275], [0, 720, 525, 736, 3279]], [[0, 0, 523, 28, 3301], [0, 56, 523, 85, 3305], [0, 85, 523, 113, 3307], [0, 113, 523, 142, 3309], [0, 142, 523, 170, 3311], [0, 170, 523, 199, 3313], [0, 199, 523, 227, 3315], [0, 227, 523, 256, 3317], [0, 256, 523, 284, 3319], [0, 284, 523, 313, 3321], [0, 313, 523, 341, 3323], [0, 341, 523, 370, 3325], [0, 370, 523, 398, 3327], [0, 398, 523, 427, 3329], [0, 427, 523, 455, 3331], [0, 455, 523, 484, 3333], [0, 484, 523, 512, 3335], [0, 512, 523, 541, 3337], [0, 541, 523, 569, 3339], [0, 569, 523, 598, 3341], [0, 598, 523, 626, 3343], [0, 626, 523, 655, 3345], [0, 655, 523, 683, 3347]], [[0, 0, 519, 29, 3371], [0, 58, 519, 88, 3375], [0, 88, 519, 117, 3377], [0, 117, 519, 147, 3379], [0, 147, 519, 176, 3381], [0, 176, 519, 205, 3383], [0, 205, 519, 235, 3385], [0, 235, 519, 264, 3387], [0, 264, 519, 294, 3389], [0, 294, 519, 323, 3391], [0, 323, 519, 352, 3393], [0, 352, 519, 382, 3395], [0, 382, 519, 411, 3397], [0, 411, 519, 441, 3399], [0, 441, 519, 470, 3401], [0, 470, 519, 499, 3403], [0, 499, 519, 529, 3405], [0, 529, 519, 558, 3407], [0, 558, 519, 588, 3409], [0, 588, 519, 617, 3411], [0, 617, 519, 646, 3413], [0, 646, 519, 676, 3415], [0, 676, 519, 705, 3417], [0, 705, 519, 734, 3419]], [[0, 0, 527, 28, 3441], [0, 28, 527, 57, 3443], [0, 57, 527, 86, 3445], [0, 86, 527, 115, 3447], [0, 114, 527, 143, 3449], [0, 143, 527, 172, 3451], [0, 172, 527, 201, 3453], [0, 201, 527, 230, 3455], [0, 230, 527, 259, 3457], [0, 259, 527, 287, 3459], [0, 287, 527, 316, 3461], [0, 316, 527, 345, 3463], [0, 345, 527, 374, 3465], [0, 374, 527, 403, 3467], [0, 403, 527, 431, 3469], [0, 431, 527, 460, 3471], [0, 460, 527, 489, 3473], [0, 489, 527, 518, 3475], [0, 518, 527, 547, 3477], [0, 547, 527, 575, 3479], [0, 575, 527, 604, 3481], [0, 604, 527, 633, 3483], [0, 633, 527, 662, 3485], [0, 662, 527, 691, 3487], [0, 691, 527, 719, 3489], [0, 719, 527, 737, 3491]], [[0, 0, 519, 29, 3513], [0, 29, 519, 58, 3515], [0, 58, 519, 88, 3517], [0, 88, 519, 117, 3519], [0, 117, 519, 147, 3521], [0, 147, 519, 176, 3523], [0, 176, 519, 205, 3525], [0, 205, 519, 235, 3527], [0, 235, 519, 264, 3529], [0, 264, 519, 294, 3531], [0, 294, 519, 323, 3533], [0, 323, 519, 352, 3535], [0, 352, 519, 382, 3537], [0, 382, 519, 411, 3539], [0, 411, 519, 441, 3541], [0, 441, 519, 470, 3543], [0, 470, 519, 499, 3545], [0, 499, 519, 529, 3547], [0, 529, 519, 558, 3549], [0, 558, 519, 588, 3551], [0, 588, 519, 617, 3553], [0, 617, 519, 646, 3555], [0, 646, 519, 676, 3557], [0, 676, 519, 705, 3559], [0, 705, 519, 734, 3561]], [[0, 0, 527, 29, 3583], [0, 29, 527, 58, 3585], [0, 57, 527, 86, 3587], [0, 86, 527, 115, 3589], [0, 115, 527, 144, 3591], [0, 144, 527, 173, 3593], [0, 173, 527, 202, 3595], [0, 201, 527, 230, 3597], [0, 230, 527, 259, 3599], [0, 259, 527, 288, 3601], [0, 288, 527, 317, 3603], [0, 317, 527, 346, 3605], [0, 346, 527, 374, 3607], [0, 374, 527, 403, 3609], [0, 403, 527, 432, 3611], [0, 432, 527, 461, 3613], [0, 461, 527, 490, 3615], [0, 490, 527, 518, 3617], [0, 518, 527, 547, 3619], [0, 576, 527, 605, 3623], [0, 605, 527, 634, 3625], [0, 634, 527, 662, 3627], [0, 662, 527, 691, 3629], [0, 720, 527, 738, 3633]]],
"expected_junk_img_bojids": []
},
"the_eye/the_eye_wtl_00023799" : {
"expected_image_info": [[[0, 0, 610, 55, 6500], [0, 55, 610, 110, 6502], [0, 110, 610, 166, 6504], [0, 166, 610, 221, 6506], [0, 221, 610, 276, 6508], [0, 276, 610, 332, 6510], [0, 332, 610, 387, 6512], [0, 387, 610, 443, 6514], [0, 443, 610, 498, 6516], [0, 498, 610, 554, 6518], [0, 554, 610, 609, 6520], [0, 609, 610, 664, 6522], [0, 664, 610, 720, 6524], [0, 720, 610, 775, 6526], [0, 775, 610, 783, 6528]], [[0, 0, 616, 54, 37], [0, 54, 616, 108, 39], [0, 108, 616, 163, 41], [0, 163, 616, 217, 43], [0, 217, 616, 272, 45], [0, 272, 616, 326, 47], [0, 326, 616, 381, 49], [0, 381, 616, 435, 51], [0, 435, 616, 490, 53], [0, 490, 616, 544, 55], [0, 544, 616, 599, 57], [0, 599, 616, 653, 59], [0, 653, 616, 708, 61], [0, 708, 616, 762, 63], [0, 762, 616, 790, 65]], [[0, 0, 619, 54, 102], [0, 54, 619, 109, 104], [0, 109, 619, 163, 106], [0, 163, 619, 218, 108], [0, 218, 619, 272, 110], [0, 272, 619, 327, 112], [0, 327, 619, 381, 114], [0, 381, 619, 435, 116], [0, 435, 619, 490, 118], [0, 490, 619, 544, 120], [0, 544, 619, 599, 122], [0, 599, 619, 653, 124], [0, 653, 619, 708, 126], [0, 708, 619, 762, 128], [0, 762, 619, 791, 130]], [[0, 0, 616, 54, 167], [0, 54, 616, 108, 169], [0, 108, 616, 163, 171], [0, 163, 616, 217, 173], [0, 217, 616, 272, 175], [0, 272, 616, 326, 177], [0, 326, 616, 381, 179], [0, 381, 616, 435, 181], [0, 435, 616, 490, 183], [0, 490, 616, 544, 185], [0, 544, 616, 599, 187], [0, 599, 616, 653, 189], [0, 653, 616, 708, 191], [0, 708, 616, 762, 193], [0, 762, 616, 787, 195]], [[0, 0, 610, 55, 232], [0, 55, 610, 111, 234], [0, 111, 610, 166, 236], [0, 166, 610, 222, 238], [0, 222, 610, 278, 240], [0, 278, 610, 333, 242], [0, 333, 610, 389, 244], [0, 389, 610, 445, 246], [0, 445, 610, 501, 248], [0, 501, 610, 556, 250], [0, 556, 610, 612, 252], [0, 612, 610, 668, 254], [0, 668, 610, 723, 256], [0, 723, 610, 779, 258], [0, 779, 610, 786, 260]], [[0, 0, 610, 55, 297], [0, 55, 610, 111, 299], [0, 111, 610, 166, 301], [0, 166, 610, 221, 303], [0, 221, 610, 277, 305], [0, 277, 610, 332, 307], [0, 332, 610, 388, 309], [0, 388, 610, 443, 311], [0, 443, 610, 499, 313], [0, 499, 610, 554, 315], [0, 554, 610, 610, 317], [0, 610, 610, 665, 319], [0, 665, 610, 720, 321], [0, 720, 610, 776, 323], [0, 776, 610, 783, 325]], [[0, 0, 789, 42, 362], [0, 42, 789, 85, 364], [0, 85, 789, 127, 366], [0, 127, 789, 170, 368], [0, 170, 789, 213, 370], [0, 213, 789, 256, 372], [0, 256, 789, 298, 374], [0, 298, 789, 341, 376], [0, 341, 789, 384, 378], [0, 384, 789, 427, 380], [0, 427, 789, 469, 382], [0, 469, 789, 512, 384], [0, 512, 789, 555, 386], [0, 555, 789, 597, 388], [0, 597, 789, 619, 390]], [[0, 0, 610, 55, 427], [0, 55, 610, 110, 429], [0, 110, 610, 166, 431], [0, 166, 610, 221, 433], [0, 221, 610, 276, 435], [0, 276, 610, 332, 437], [0, 332, 610, 387, 439], [0, 387, 610, 443, 441], [0, 443, 610, 498, 443], [0, 498, 610, 554, 445], [0, 554, 610, 609, 447], [0, 609, 610, 664, 449], [0, 664, 610, 720, 451], [0, 720, 610, 775, 453], [0, 775, 610, 783, 455]], [[0, 0, 619, 54, 492], [0, 54, 619, 108, 494], [0, 108, 619, 163, 496], [0, 163, 619, 217, 498], [0, 217, 619, 272, 500], [0, 272, 619, 326, 502], [0, 326, 619, 381, 504], [0, 381, 619, 435, 506], [0, 435, 619, 490, 508], [0, 490, 619, 544, 510], [0, 544, 619, 599, 512], [0, 599, 619, 653, 514], [0, 653, 619, 708, 516], [0, 708, 619, 762, 518], [0, 762, 619, 790, 520]], [[0, 0, 610, 55, 557], [0, 55, 610, 111, 559], [0, 111, 610, 166, 561], [0, 166, 610, 222, 563], [0, 222, 610, 277, 565], [0, 277, 610, 333, 567], [0, 333, 610, 388, 569], [0, 388, 610, 443, 571], [0, 443, 610, 499, 573], [0, 499, 610, 554, 575], [0, 554, 610, 610, 577], [0, 610, 610, 665, 579], [0, 665, 610, 721, 581], [0, 721, 610, 776, 583], [0, 776, 610, 783, 585]], [[0, 0, 610, 55, 622], [0, 55, 610, 110, 624], [0, 110, 610, 166, 626], [0, 166, 610, 221, 628], [0, 221, 610, 276, 630], [0, 276, 610, 332, 632], [0, 332, 610, 387, 634], [0, 387, 610, 443, 636], [0, 443, 610, 498, 638], [0, 498, 610, 554, 640], [0, 554, 610, 609, 642], [0, 609, 610, 664, 644], [0, 664, 610, 720, 646], [0, 720, 610, 775, 648], [0, 775, 610, 783, 650]], [[0, 0, 610, 55, 687], [0, 55, 610, 111, 689], [0, 111, 610, 166, 691], [0, 166, 610, 222, 693], [0, 222, 610, 278, 695], [0, 278, 610, 333, 697], [0, 333, 610, 389, 699], [0, 389, 610, 445, 701], [0, 445, 610, 501, 703], [0, 501, 610, 556, 705], [0, 556, 610, 612, 707], [0, 612, 610, 668, 709], [0, 668, 610, 723, 711], [0, 723, 610, 779, 713], [0, 779, 610, 786, 715]], [[0, 0, 610, 55, 752], [0, 55, 610, 111, 754], [0, 111, 610, 166, 756], [0, 166, 610, 222, 758], [0, 222, 610, 278, 760], [0, 278, 610, 333, 762], [0, 333, 610, 389, 764], [0, 389, 610, 445, 766], [0, 445, 610, 501, 768], [0, 501, 610, 556, 770], [0, 556, 610, 612, 772], [0, 612, 610, 668, 774], [0, 668, 610, 723, 776], [0, 723, 610, 779, 778], [0, 779, 610, 786, 780]], [[0, 0, 610, 55, 817], [0, 55, 610, 111, 819], [0, 111, 610, 166, 821], [0, 166, 610, 221, 823], [0, 221, 610, 277, 825], [0, 277, 610, 332, 827], [0, 332, 610, 388, 829], [0, 388, 610, 443, 831], [0, 443, 610, 499, 833], [0, 499, 610, 554, 835], [0, 554, 610, 610, 837], [0, 610, 610, 665, 839], [0, 665, 610, 720, 841], [0, 720, 610, 776, 843], [0, 776, 610, 783, 845]], [[0, 0, 610, 55, 882], [0, 55, 610, 111, 884], [0, 111, 610, 166, 886], [0, 166, 610, 222, 888], [0, 222, 610, 277, 890], [0, 277, 610, 333, 892], [0, 333, 610, 388, 894], [0, 388, 610, 443, 896], [0, 443, 610, 499, 898], [0, 499, 610, 554, 900], [0, 554, 610, 610, 902], [0, 610, 610, 665, 904], [0, 665, 610, 721, 906], [0, 721, 610, 776, 908], [0, 776, 610, 783, 910]], [[0, 0, 610, 55, 947], [0, 55, 610, 111, 949], [0, 111, 610, 166, 951], [0, 166, 610, 222, 953], [0, 222, 610, 277, 955], [0, 277, 610, 333, 957], [0, 333, 610, 388, 959], [0, 388, 610, 443, 961], [0, 443, 610, 499, 963], [0, 499, 610, 554, 965], [0, 554, 610, 610, 967], [0, 610, 610, 665, 969], [0, 665, 610, 721, 971], [0, 721, 610, 776, 973], [0, 776, 610, 783, 975]], [[0, 0, 610, 55, 1012], [0, 55, 610, 110, 1014], [0, 110, 610, 166, 1016], [0, 166, 610, 221, 1018], [0, 221, 610, 276, 1020], [0, 276, 610, 332, 1022], [0, 332, 610, 387, 1024], [0, 387, 610, 443, 1026], [0, 443, 610, 498, 1028], [0, 498, 610, 554, 1030], [0, 554, 610, 609, 1032], [0, 609, 610, 664, 1034], [0, 664, 610, 720, 1036], [0, 720, 610, 775, 1038], [0, 775, 610, 783, 1040]], [[0, 0, 610, 55, 1077], [0, 55, 610, 111, 1079], [0, 111, 610, 166, 1081], [0, 166, 610, 222, 1083], [0, 222, 610, 278, 1085], [0, 278, 610, 333, 1087], [0, 333, 610, 389, 1089], [0, 389, 610, 445, 1091], [0, 445, 610, 501, 1093], [0, 501, 610, 556, 1095], [0, 556, 610, 612, 1097], [0, 612, 610, 668, 1099], [0, 668, 610, 723, 1101], [0, 723, 610, 779, 1103], [0, 779, 610, 786, 1105]], [[0, 0, 610, 55, 1142], [0, 55, 610, 110, 1144], [0, 110, 610, 166, 1146], [0, 166, 610, 221, 1148], [0, 221, 610, 276, 1150], [0, 276, 610, 332, 1152], [0, 332, 610, 387, 1154], [0, 387, 610, 443, 1156], [0, 443, 610, 498, 1158], [0, 498, 610, 554, 1160], [0, 554, 610, 609, 1162], [0, 609, 610, 664, 1164], [0, 664, 610, 720, 1166], [0, 720, 610, 775, 1168], [0, 775, 610, 783, 1170]], [[0, 0, 622, 54, 1207], [0, 54, 622, 108, 1209], [0, 108, 622, 163, 1211], [0, 163, 622, 217, 1213], [0, 217, 622, 272, 1215], [0, 272, 622, 326, 1217], [0, 326, 622, 381, 1219], [0, 381, 622, 435, 1221], [0, 435, 622, 490, 1223], [0, 490, 622, 544, 1225], [0, 544, 622, 599, 1227], [0, 599, 622, 653, 1229], [0, 653, 622, 708, 1231], [0, 708, 622, 762, 1233], [0, 762, 622, 793, 1235]], [[0, 0, 619, 54, 1272], [0, 54, 619, 109, 1274], [0, 109, 619, 163, 1276], [0, 163, 619, 218, 1278], [0, 218, 619, 272, 1280], [0, 272, 619, 327, 1282], [0, 327, 619, 381, 1284], [0, 381, 619, 435, 1286], [0, 435, 619, 490, 1288], [0, 490, 619, 544, 1290], [0, 544, 619, 599, 1292], [0, 599, 619, 653, 1294], [0, 653, 619, 708, 1296], [0, 708, 619, 762, 1298], [0, 762, 619, 791, 1300]], [[0, 0, 610, 55, 1337], [0, 55, 610, 111, 1339], [0, 111, 610, 166, 1341], [0, 166, 610, 222, 1343], [0, 222, 610, 278, 1345], [0, 278, 610, 333, 1347], [0, 333, 610, 389, 1349], [0, 389, 610, 445, 1351], [0, 445, 610, 501, 1353], [0, 501, 610, 556, 1355], [0, 556, 610, 612, 1357], [0, 612, 610, 668, 1359], [0, 668, 610, 723, 1361], [0, 723, 610, 779, 1363], [0, 779, 610, 786, 1365]], [[0, 0, 616, 54, 1402], [0, 54, 616, 108, 1404], [0, 108, 616, 163, 1406], [0, 163, 616, 217, 1408], [0, 217, 616, 272, 1410], [0, 272, 616, 326, 1412], [0, 326, 616, 381, 1414], [0, 381, 616, 435, 1416], [0, 435, 616, 490, 1418], [0, 490, 616, 544, 1420], [0, 544, 616, 599, 1422], [0, 599, 616, 653, 1424], [0, 653, 616, 708, 1426], [0, 708, 616, 762, 1428], [0, 762, 616, 790, 1430]], [[0, 0, 616, 54, 1467], [0, 54, 616, 109, 1469], [0, 109, 616, 163, 1471], [0, 163, 616, 218, 1473], [0, 218, 616, 272, 1475], [0, 272, 616, 327, 1477], [0, 327, 616, 381, 1479], [0, 381, 616, 436, 1481], [0, 436, 616, 490, 1483], [0, 490, 616, 545, 1485], [0, 545, 616, 599, 1487], [0, 599, 616, 653, 1489], [0, 653, 616, 708, 1491], [0, 708, 616, 762, 1493], [0, 762, 616, 791, 1495]], [[0, 0, 610, 55, 1532], [0, 55, 610, 111, 1534], [0, 111, 610, 166, 1536], [0, 166, 610, 221, 1538], [0, 221, 610, 277, 1540], [0, 277, 610, 332, 1542], [0, 332, 610, 388, 1544], [0, 388, 610, 443, 1546], [0, 443, 610, 499, 1548], [0, 499, 610, 554, 1550], [0, 554, 610, 610, 1552], [0, 610, 610, 665, 1554], [0, 665, 610, 720, 1556], [0, 720, 610, 776, 1558], [0, 776, 610, 783, 1560]], [[0, 0, 616, 54, 1597], [0, 54, 616, 108, 1599], [0, 108, 616, 163, 1601], [0, 163, 616, 217, 1603], [0, 217, 616, 272, 1605], [0, 272, 616, 326, 1607], [0, 326, 616, 381, 1609], [0, 381, 616, 435, 1611], [0, 435, 616, 490, 1613], [0, 490, 616, 544, 1615], [0, 544, 616, 599, 1617], [0, 599, 616, 653, 1619], [0, 653, 616, 708, 1621], [0, 708, 616, 762, 1623], [0, 762, 616, 787, 1625]], [[0, 0, 619, 54, 1662], [0, 54, 619, 109, 1664], [0, 109, 619, 163, 1666], [0, 163, 619, 218, 1668], [0, 218, 619, 272, 1670], [0, 272, 619, 327, 1672], [0, 327, 619, 381, 1674], [0, 381, 619, 435, 1676], [0, 435, 619, 490, 1678], [0, 490, 619, 544, 1680], [0, 544, 619, 599, 1682], [0, 599, 619, 653, 1684], [0, 653, 619, 708, 1686], [0, 708, 619, 762, 1688], [0, 762, 619, 791, 1690]], [[0, 0, 610, 56, 1727], [0, 56, 610, 111, 1729], [0, 111, 610, 167, 1731], [0, 167, 610, 223, 1733], [0, 223, 610, 278, 1735], [0, 278, 610, 334, 1737], [0, 334, 610, 390, 1739], [0, 390, 610, 445, 1741], [0, 445, 610, 501, 1743], [0, 501, 610, 557, 1745], [0, 557, 610, 612, 1747], [0, 612, 610, 668, 1749], [0, 668, 610, 724, 1751], [0, 724, 610, 780, 1753], [0, 780, 610, 787, 1755]], [[0, 0, 622, 54, 1792], [0, 54, 622, 109, 1794], [0, 108, 622, 163, 1796], [0, 163, 622, 217, 1798], [0, 217, 622, 272, 1800], [0, 272, 622, 326, 1802], [0, 326, 622, 381, 1804], [0, 381, 622, 435, 1806], [0, 435, 622, 490, 1808], [0, 490, 622, 544, 1810], [0, 544, 622, 599, 1812], [0, 599, 622, 653, 1814], [0, 653, 622, 708, 1816], [0, 708, 622, 762, 1818], [0, 762, 622, 793, 1820]], [[0, 0, 791, 42, 1857], [0, 42, 791, 85, 1859], [0, 85, 791, 127, 1861], [0, 127, 791, 170, 1863], [0, 170, 791, 213, 1865], [0, 213, 791, 255, 1867], [0, 255, 791, 298, 1869], [0, 298, 791, 341, 1871], [0, 341, 791, 384, 1873], [0, 384, 791, 426, 1875], [0, 426, 791, 469, 1877], [0, 469, 791, 512, 1879], [0, 512, 791, 554, 1881], [0, 597, 791, 622, 1885]], [[0, 0, 610, 55, 1922], [0, 55, 610, 111, 1924], [0, 111, 610, 166, 1926], [0, 166, 610, 222, 1928], [0, 222, 610, 277, 1930], [0, 277, 610, 333, 1932], [0, 333, 610, 388, 1934], [0, 388, 610, 443, 1936], [0, 443, 610, 499, 1938], [0, 499, 610, 554, 1940], [0, 554, 610, 610, 1942], [0, 610, 610, 665, 1944], [0, 665, 610, 721, 1946], [0, 721, 610, 776, 1948], [0, 776, 610, 783, 1950]], [[0, 0, 610, 55, 1987], [0, 55, 610, 110, 1989], [0, 110, 610, 166, 1991], [0, 166, 610, 221, 1993], [0, 221, 610, 276, 1995], [0, 276, 610, 332, 1997], [0, 332, 610, 387, 1999], [0, 387, 610, 443, 2001], [0, 443, 610, 498, 2003], [0, 498, 610, 554, 2005], [0, 554, 610, 609, 2007], [0, 609, 610, 664, 2009], [0, 664, 610, 720, 2011], [0, 720, 610, 775, 2013], [0, 775, 610, 783, 2015]], [[0, 0, 610, 55, 2052], [0, 55, 610, 111, 2054], [0, 111, 610, 166, 2056], [0, 166, 610, 221, 2058], [0, 221, 610, 277, 2060], [0, 277, 610, 332, 2062], [0, 332, 610, 388, 2064], [0, 388, 610, 443, 2066], [0, 443, 610, 499, 2068], [0, 499, 610, 554, 2070], [0, 554, 610, 610, 2072], [0, 610, 610, 665, 2074], [0, 665, 610, 720, 2076], [0, 720, 610, 776, 2078], [0, 776, 610, 783, 2080]], [[0, 0, 618, 54, 2117], [0, 54, 618, 109, 2119], [0, 109, 618, 163, 2121], [0, 163, 618, 218, 2123], [0, 218, 618, 272, 2125], [0, 272, 618, 327, 2127], [0, 327, 618, 381, 2129], [0, 381, 618, 436, 2131], [0, 436, 618, 490, 2133], [0, 490, 618, 545, 2135], [0, 545, 618, 599, 2137], [0, 599, 618, 654, 2139], [0, 654, 618, 708, 2141], [0, 708, 618, 763, 2143], [0, 763, 618, 791, 2145]], [[0, 0, 619, 54, 2182], [0, 54, 619, 108, 2184], [0, 108, 619, 163, 2186], [0, 163, 619, 217, 2188], [0, 217, 619, 272, 2190], [0, 272, 619, 326, 2192], [0, 326, 619, 381, 2194], [0, 381, 619, 435, 2196], [0, 435, 619, 489, 2198], [0, 489, 619, 544, 2200], [0, 544, 619, 598, 2202], [0, 598, 619, 653, 2204], [0, 653, 619, 707, 2206], [0, 707, 619, 762, 2208], [0, 762, 619, 790, 2210]], [[0, 0, 616, 54, 2247], [0, 53, 616, 108, 2249], [0, 108, 616, 162, 2251], [0, 162, 616, 217, 2253], [0, 217, 616, 271, 2255], [0, 271, 616, 326, 2257], [0, 326, 616, 380, 2259], [0, 380, 616, 435, 2261], [0, 435, 616, 489, 2263], [0, 489, 616, 544, 2265], [0, 544, 616, 598, 2267], [0, 598, 616, 653, 2269], [0, 653, 616, 707, 2271], [0, 707, 616, 762, 2273], [0, 762, 616, 790, 2275]], [[0, 0, 610, 55, 2312], [0, 55, 610, 111, 2314], [0, 111, 610, 166, 2316], [0, 166, 610, 222, 2318], [0, 222, 610, 277, 2320], [0, 277, 610, 333, 2322], [0, 333, 610, 388, 2324], [0, 388, 610, 443, 2326], [0, 443, 610, 499, 2328], [0, 499, 610, 554, 2330], [0, 554, 610, 610, 2332], [0, 610, 610, 665, 2334], [0, 665, 610, 721, 2336], [0, 721, 610, 776, 2338], [0, 776, 610, 783, 2340]], [[0, 0, 627, 53, 2377], [0, 53, 627, 106, 2379], [0, 106, 627, 160, 2381], [0, 160, 627, 213, 2383], [0, 213, 627, 266, 2385], [0, 266, 627, 320, 2387], [0, 320, 627, 373, 2389], [0, 373, 627, 426, 2391], [0, 426, 627, 479, 2393], [0, 479, 627, 533, 2395], [0, 533, 627, 586, 2397], [0, 586, 627, 639, 2399], [0, 639, 627, 693, 2401], [0, 693, 627, 746, 2403], [0, 746, 627, 795, 2405]], [[0, 0, 610, 55, 2442], [0, 55, 610, 111, 2444], [0, 111, 610, 166, 2446], [0, 166, 610, 221, 2448], [0, 221, 610, 277, 2450], [0, 277, 610, 332, 2452], [0, 332, 610, 388, 2454], [0, 388, 610, 443, 2456], [0, 443, 610, 499, 2458], [0, 499, 610, 554, 2460], [0, 554, 610, 610, 2462], [0, 610, 610, 665, 2464], [0, 665, 610, 720, 2466], [0, 720, 610, 776, 2468], [0, 776, 610, 783, 2470]], [[0, 0, 610, 55, 2507], [0, 55, 610, 110, 2509], [0, 110, 610, 166, 2511], [0, 166, 610, 221, 2513], [0, 221, 610, 276, 2515], [0, 276, 610, 332, 2517], [0, 332, 610, 387, 2519], [0, 387, 610, 443, 2521], [0, 443, 610, 498, 2523], [0, 498, 610, 554, 2525], [0, 554, 610, 609, 2527], [0, 609, 610, 664, 2529], [0, 664, 610, 720, 2531], [0, 720, 610, 775, 2533], [0, 775, 610, 783, 2535]], [[0, 0, 616, 54, 2572], [0, 54, 616, 108, 2574], [0, 108, 616, 163, 2576], [0, 163, 616, 217, 2578], [0, 217, 616, 272, 2580], [0, 272, 616, 326, 2582], [0, 326, 616, 381, 2584], [0, 381, 616, 435, 2586], [0, 435, 616, 489, 2588], [0, 489, 616, 544, 2590], [0, 544, 616, 598, 2592], [0, 598, 616, 653, 2594], [0, 653, 616, 707, 2596], [0, 707, 616, 762, 2598], [0, 762, 616, 790, 2600]], [[0, 0, 616, 54, 2637], [0, 54, 616, 109, 2639], [0, 109, 616, 163, 2641], [0, 163, 616, 218, 2643], [0, 218, 616, 272, 2645], [0, 272, 616, 327, 2647], [0, 327, 616, 381, 2649], [0, 381, 616, 435, 2651], [0, 435, 616, 490, 2653], [0, 490, 616, 544, 2655], [0, 544, 616, 599, 2657], [0, 599, 616, 653, 2659], [0, 653, 616, 708, 2661], [0, 708, 616, 762, 2663], [0, 762, 616, 791, 2665]], [[0, 0, 619, 54, 2702], [0, 54, 619, 109, 2704], [0, 109, 619, 163, 2706], [0, 163, 619, 218, 2708], [0, 218, 619, 272, 2710], [0, 272, 619, 327, 2712], [0, 327, 619, 381, 2714], [0, 381, 619, 435, 2716], [0, 435, 619, 490, 2718], [0, 490, 619, 544, 2720], [0, 544, 619, 599, 2722], [0, 599, 619, 653, 2724], [0, 653, 619, 708, 2726], [0, 708, 619, 762, 2728], [0, 762, 619, 791, 2730]], [[0, 0, 616, 54, 2767], [0, 54, 616, 109, 2769], [0, 109, 616, 163, 2771], [0, 163, 616, 218, 2773], [0, 218, 616, 272, 2775], [0, 272, 616, 327, 2777], [0, 327, 616, 381, 2779], [0, 381, 616, 435, 2781], [0, 435, 616, 490, 2783], [0, 490, 616, 544, 2785], [0, 544, 616, 599, 2787], [0, 599, 616, 653, 2789], [0, 653, 616, 708, 2791], [0, 708, 616, 762, 2793], [0, 762, 616, 791, 2795]], [[0, 0, 610, 55, 2832], [0, 55, 610, 111, 2834], [0, 111, 610, 166, 2836], [0, 166, 610, 222, 2838], [0, 222, 610, 278, 2840], [0, 278, 610, 333, 2842], [0, 333, 610, 389, 2844], [0, 389, 610, 445, 2846], [0, 445, 610, 501, 2848], [0, 501, 610, 556, 2850], [0, 556, 610, 612, 2852], [0, 612, 610, 668, 2854], [0, 668, 610, 723, 2856], [0, 723, 610, 779, 2858], [0, 779, 610, 786, 2860]], [[0, 0, 622, 54, 2897], [0, 54, 622, 109, 2899], [0, 108, 622, 163, 2901], [0, 163, 622, 217, 2903], [0, 217, 622, 272, 2905], [0, 272, 622, 326, 2907], [0, 326, 622, 381, 2909], [0, 381, 622, 435, 2911], [0, 435, 622, 490, 2913], [0, 490, 622, 544, 2915], [0, 544, 622, 599, 2917], [0, 599, 622, 653, 2919], [0, 653, 622, 708, 2921], [0, 708, 622, 762, 2923], [0, 762, 622, 793, 2925]], [[0, 0, 624, 53, 2962], [0, 53, 624, 107, 2964], [0, 107, 624, 160, 2966], [0, 160, 624, 214, 2968], [0, 214, 624, 267, 2970], [0, 267, 624, 321, 2972], [0, 321, 624, 374, 2974], [0, 374, 624, 428, 2976], [0, 428, 624, 481, 2978], [0, 481, 624, 535, 2980], [0, 535, 624, 588, 2982], [0, 588, 624, 642, 2984], [0, 642, 624, 695, 2986], [0, 695, 624, 749, 2988], [0, 749, 624, 798, 2990]], [[0, 0, 619, 54, 3027], [0, 54, 619, 108, 3029], [0, 108, 619, 163, 3031], [0, 163, 619, 217, 3033], [0, 217, 619, 272, 3035], [0, 272, 619, 326, 3037], [0, 326, 619, 381, 3039], [0, 381, 619, 435, 3041], [0, 435, 619, 489, 3043], [0, 489, 619, 544, 3045], [0, 544, 619, 598, 3047], [0, 598, 619, 653, 3049], [0, 653, 619, 707, 3051], [0, 707, 619, 762, 3053], [0, 762, 619, 790, 3055]], [[0, 0, 619, 54, 3092], [0, 54, 619, 109, 3094], [0, 109, 619, 163, 3096], [0, 163, 619, 218, 3098], [0, 218, 619, 272, 3100], [0, 272, 619, 327, 3102], [0, 327, 619, 381, 3104], [0, 381, 619, 435, 3106], [0, 435, 619, 490, 3108], [0, 490, 619, 544, 3110], [0, 544, 619, 599, 3112], [0, 599, 619, 653, 3114], [0, 653, 619, 708, 3116], [0, 708, 619, 762, 3118], [0, 762, 619, 791, 3120]], [[0, 0, 610, 55, 3157], [0, 55, 610, 111, 3159], [0, 111, 610, 166, 3161], [0, 166, 610, 221, 3163], [0, 221, 610, 277, 3165], [0, 277, 610, 332, 3167], [0, 332, 610, 388, 3169], [0, 388, 610, 443, 3171], [0, 443, 610, 499, 3173], [0, 499, 610, 554, 3175], [0, 554, 610, 610, 3177], [0, 610, 610, 665, 3179], [0, 665, 610, 720, 3181], [0, 720, 610, 776, 3183], [0, 776, 610, 783, 3185]]],
"expected_junk_img_bojids": []
},
"vertical_detection/三国演义_繁体竖排版" : {
"expected_text_layout": [
"vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical"
]
},
"vertical_detection/净空法师_大乘无量寿" : {
"expected_text_layout" : [
"vertical", "unknow", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical", "vertical"
]
},
"vertical_detection/om3006239" : {
"expected_text_layout" : [
"horizontal", "horizontal", "horizontal", "horizontal", "horizontal", "horizontal", "horizontal", "horizontal", "horizontal", "horizontal"
]
},
"vertical_detection/isit.2006.261791" : {
"expected_text_layout" : [
"horizontal", "horizontal", "horizontal", "horizontal", "horizontal"
]
},
"the_eye/the_eye_cdn_00328381" : {
"expected_image_info": [[[0, 0, 405, 36, 11428], [0, 73, 405, 110, 11429], [0, 147, 405, 184, 11430], [0, 184, 405, 222, 11431], [0, 222, 405, 258, 11432], [0, 258, 405, 295, 11433], [0, 295, 405, 333, 11434], [0, 333, 405, 369, 11435], [0, 369, 405, 406, 11436], [0, 406, 405, 444, 11437], [0, 444, 405, 480, 11438], [0, 517, 405, 555, 11439]], [[0, 0, 402, 37, 9852], [0, 555, 402, 592, 4], [0, 592, 402, 628, 5]], [[0, 0, 396, 38, 9854], [0, 38, 396, 76, 10], [0, 76, 396, 114, 11], [0, 114, 396, 152, 12], [0, 152, 396, 191, 13], [0, 191, 396, 229, 14], [0, 229, 396, 267, 15], [0, 267, 396, 305, 16], [0, 305, 396, 344, 17], [0, 344, 396, 382, 18], [0, 382, 396, 420, 19], [0, 420, 396, 458, 20], [0, 458, 396, 497, 21], [0, 497, 396, 535, 22], [0, 535, 396, 573, 23], [0, 573, 396, 611, 24], [0, 650, 396, 671, 9853]], [[0, 0, 396, 38, 9854], [0, 38, 396, 76, 29], [0, 76, 396, 114, 30], [0, 114, 396, 153, 31], [0, 153, 396, 191, 32], [0, 191, 396, 229, 33], [0, 229, 396, 267, 34], [0, 267, 396, 306, 35], [0, 497, 396, 535, 36], [0, 573, 396, 612, 37], [0, 612, 396, 650, 38], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 9854], [0, 38, 396, 76, 43], [0, 76, 396, 114, 44], [0, 114, 396, 153, 45], [0, 153, 396, 191, 46], [0, 191, 396, 229, 47], [0, 229, 396, 267, 48], [0, 267, 396, 306, 49], [0, 306, 396, 344, 50], [0, 344, 396, 382, 51], [0, 382, 396, 420, 52], [0, 420, 396, 459, 53], [0, 459, 396, 497, 54], [0, 497, 396, 535, 55], [0, 535, 396, 573, 56], [0, 573, 396, 612, 57], [0, 612, 396, 650, 58], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 63], [0, 38, 396, 76, 64], [0, 76, 396, 114, 65], [0, 114, 396, 152, 66], [0, 152, 396, 191, 67], [0, 191, 396, 229, 68], [0, 229, 396, 267, 69], [0, 267, 396, 305, 70], [0, 305, 396, 344, 71], [0, 344, 396, 382, 72], [0, 382, 396, 420, 73], [0, 420, 396, 458, 74], [0, 458, 396, 497, 75], [0, 497, 396, 535, 76], [0, 535, 396, 573, 9854], [0, 611, 396, 650, 77], [0, 650, 396, 671, 9853]], [[0, 0, 402, 36, 9852], [0, 73, 402, 110, 82], [0, 110, 402, 147, 83], [0, 147, 402, 184, 84], [0, 184, 402, 222, 85], [0, 222, 402, 258, 86], [0, 258, 402, 295, 87], [0, 295, 402, 333, 88], [0, 333, 402, 369, 89], [0, 369, 402, 406, 90], [0, 406, 402, 444, 91], [0, 444, 402, 480, 92], [0, 480, 402, 517, 93], [0, 517, 402, 555, 94], [0, 555, 402, 591, 95], [0, 591, 402, 628, 96]], [[0, 0, 396, 38, 101], [0, 38, 396, 76, 102], [0, 76, 396, 114, 103], [0, 114, 396, 152, 104], [0, 152, 396, 191, 105], [0, 191, 396, 229, 106], [0, 229, 396, 267, 107], [0, 267, 396, 305, 108], [0, 305, 396, 344, 109], [0, 344, 396, 382, 110], [0, 382, 396, 420, 111], [0, 420, 396, 458, 112], [0, 458, 396, 497, 113], [0, 497, 396, 535, 114], [0, 535, 396, 573, 115], [0, 573, 396, 611, 116], [0, 611, 396, 650, 117], [0, 650, 396, 671, 9853]], [[0, 0, 396, 38, 122], [0, 38, 396, 76, 123], [0, 76, 396, 114, 124], [0, 114, 396, 152, 125], [0, 152, 396, 191, 126], [0, 191, 396, 229, 127], [0, 229, 396, 267, 128], [0, 267, 396, 305, 129], [0, 305, 396, 344, 130], [0, 344, 396, 382, 131], [0, 382, 396, 420, 132], [0, 420, 396, 458, 133], [0, 458, 396, 497, 134], [0, 497, 396, 535, 135], [0, 535, 396, 573, 136], [0, 573, 396, 611, 137], [0, 611, 396, 650, 138], [0, 650, 396, 671, 9853]], [[0, 0, 396, 38, 143], [0, 38, 396, 76, 144], [0, 76, 396, 114, 145], [0, 114, 396, 153, 146], [0, 153, 396, 191, 147], [0, 191, 396, 229, 148], [0, 229, 396, 267, 149], [0, 267, 396, 306, 150], [0, 306, 396, 344, 151], [0, 344, 396, 382, 152], [0, 382, 396, 420, 153], [0, 420, 396, 459, 154], [0, 459, 396, 497, 155], [0, 497, 396, 535, 156], [0, 535, 396, 573, 157], [0, 573, 396, 612, 158], [0, 612, 396, 650, 159], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 164], [0, 38, 396, 76, 165], [0, 76, 396, 115, 166], [0, 115, 396, 153, 167], [0, 153, 396, 191, 168], [0, 191, 396, 229, 169], [0, 229, 396, 268, 170], [0, 268, 396, 306, 171], [0, 306, 396, 344, 172], [0, 344, 396, 382, 173], [0, 382, 396, 421, 174], [0, 421, 396, 459, 175], [0, 459, 396, 497, 176], [0, 497, 396, 535, 177], [0, 535, 396, 574, 178], [0, 574, 396, 612, 179], [0, 612, 396, 650, 180], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 185], [0, 38, 396, 76, 186], [0, 76, 396, 114, 187], [0, 114, 396, 153, 188], [0, 153, 396, 191, 189], [0, 191, 396, 229, 190], [0, 229, 396, 267, 191], [0, 267, 396, 306, 192], [0, 306, 396, 344, 193], [0, 344, 396, 382, 194], [0, 382, 396, 420, 195], [0, 420, 396, 459, 196], [0, 459, 396, 497, 197], [0, 497, 396, 535, 198], [0, 535, 396, 573, 199], [0, 573, 396, 612, 200], [0, 612, 396, 650, 201], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 206], [0, 38, 396, 76, 207], [0, 76, 396, 114, 208], [0, 114, 396, 153, 209], [0, 153, 396, 191, 210], [0, 191, 396, 229, 211], [0, 229, 396, 267, 212], [0, 267, 396, 306, 213], [0, 306, 396, 344, 214], [0, 344, 396, 382, 215], [0, 382, 396, 420, 216], [0, 420, 396, 459, 217], [0, 459, 396, 497, 218], [0, 497, 396, 535, 219], [0, 535, 396, 573, 220], [0, 573, 396, 612, 221], [0, 612, 396, 650, 222], [0, 650, 396, 672, 223]], [[0, 0, 396, 38, 228], [0, 38, 396, 76, 229], [0, 76, 396, 114, 230], [0, 114, 396, 153, 231], [0, 153, 396, 191, 232], [0, 191, 396, 229, 233], [0, 229, 396, 267, 234], [0, 267, 396, 306, 235], [0, 306, 396, 344, 236], [0, 344, 396, 382, 237], [0, 382, 396, 420, 238], [0, 420, 396, 459, 239], [0, 459, 396, 497, 240], [0, 497, 396, 535, 241], [0, 535, 396, 573, 242], [0, 573, 396, 612, 243], [0, 612, 396, 650, 244], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 249], [0, 38, 396, 76, 250], [0, 76, 396, 115, 251], [0, 115, 396, 153, 252], [0, 153, 396, 191, 253], [0, 191, 396, 229, 254], [0, 229, 396, 268, 255], [0, 268, 396, 306, 256], [0, 306, 396, 344, 257], [0, 344, 396, 382, 258], [0, 382, 396, 421, 259], [0, 421, 396, 459, 260], [0, 459, 396, 497, 261], [0, 497, 396, 535, 262], [0, 535, 396, 574, 263], [0, 574, 396, 612, 264], [0, 612, 396, 650, 265], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 270], [0, 38, 396, 76, 271], [0, 76, 396, 114, 272], [0, 114, 396, 153, 273], [0, 153, 396, 191, 274], [0, 191, 396, 229, 275], [0, 229, 396, 267, 276], [0, 267, 396, 306, 277], [0, 306, 396, 344, 278], [0, 344, 396, 382, 279], [0, 382, 396, 420, 280], [0, 420, 396, 459, 281], [0, 459, 396, 497, 282], [0, 497, 396, 535, 283], [0, 535, 396, 573, 284], [0, 573, 396, 612, 285], [0, 612, 396, 650, 286], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 291], [0, 38, 396, 76, 292], [0, 76, 396, 114, 293], [0, 114, 396, 152, 294], [0, 152, 396, 191, 295], [0, 191, 396, 229, 296], [0, 229, 396, 267, 297], [0, 267, 396, 305, 298], [0, 305, 396, 344, 299], [0, 344, 396, 382, 300], [0, 382, 396, 420, 301], [0, 420, 396, 458, 302], [0, 458, 396, 497, 303], [0, 497, 396, 535, 304], [0, 535, 396, 573, 305], [0, 573, 396, 611, 306], [0, 611, 396, 650, 307], [0, 650, 396, 671, 9853]], [[0, 0, 402, 36, 312], [0, 36, 402, 73, 313], [0, 73, 402, 110, 314], [0, 110, 402, 147, 315], [0, 147, 402, 184, 316], [0, 184, 402, 222, 317], [0, 222, 402, 258, 318], [0, 258, 402, 295, 319], [0, 295, 402, 333, 320], [0, 333, 402, 369, 321], [0, 369, 402, 406, 322], [0, 406, 402, 444, 323], [0, 444, 402, 480, 324], [0, 480, 402, 517, 325], [0, 517, 402, 555, 326], [0, 555, 402, 591, 327], [0, 591, 402, 628, 328], [0, 628, 402, 666, 9852]], [[0, 0, 405, 36, 11428], [0, 36, 405, 73, 333], [0, 73, 405, 110, 334], [0, 110, 405, 147, 335], [0, 147, 405, 184, 336], [0, 184, 405, 222, 337], [0, 222, 405, 258, 338], [0, 258, 405, 295, 339], [0, 295, 405, 333, 340], [0, 333, 405, 369, 341], [0, 369, 405, 406, 342], [0, 406, 405, 444, 343], [0, 444, 405, 480, 344], [0, 480, 405, 517, 345], [0, 517, 405, 555, 346], [0, 555, 405, 591, 347], [0, 591, 405, 628, 348]], [[0, 0, 396, 38, 353], [0, 38, 396, 76, 354], [0, 76, 396, 114, 355], [0, 114, 396, 153, 356], [0, 153, 396, 191, 357], [0, 191, 396, 229, 358], [0, 229, 396, 267, 359], [0, 267, 396, 306, 360], [0, 306, 396, 344, 361], [0, 344, 396, 382, 362], [0, 382, 396, 420, 363], [0, 420, 396, 459, 364], [0, 459, 396, 497, 365], [0, 497, 396, 535, 366], [0, 535, 396, 573, 367], [0, 573, 396, 612, 368], [0, 612, 396, 650, 369], [0, 650, 396, 672, 9853]], [[0, 0, 405, 36, 11428], [0, 36, 405, 73, 374], [0, 73, 405, 110, 375], [0, 110, 405, 147, 376], [0, 147, 405, 184, 377], [0, 184, 405, 222, 378], [0, 222, 405, 258, 379], [0, 258, 405, 295, 380], [0, 295, 405, 333, 381], [0, 333, 405, 369, 382], [0, 369, 405, 406, 383], [0, 406, 405, 444, 384], [0, 444, 405, 480, 385], [0, 480, 405, 517, 386], [0, 517, 405, 555, 387], [0, 555, 405, 591, 388], [0, 591, 405, 628, 389]], [[0, 0, 402, 36, 394], [0, 36, 402, 73, 395], [0, 73, 402, 110, 396], [0, 110, 402, 147, 397], [0, 147, 402, 184, 398], [0, 184, 402, 222, 399], [0, 222, 402, 258, 400], [0, 258, 402, 295, 401], [0, 295, 402, 333, 402], [0, 333, 402, 369, 403], [0, 369, 402, 406, 404], [0, 406, 402, 444, 405], [0, 444, 402, 480, 406], [0, 480, 402, 517, 407], [0, 517, 402, 555, 408], [0, 555, 402, 591, 409], [0, 591, 402, 628, 410], [0, 628, 402, 666, 9852]], [[0, 0, 405, 36, 415], [0, 36, 405, 73, 416], [0, 73, 405, 110, 417], [0, 110, 405, 147, 418], [0, 147, 405, 184, 419], [0, 184, 405, 222, 420], [0, 222, 405, 258, 421], [0, 258, 405, 295, 422], [0, 295, 405, 333, 423], [0, 333, 405, 369, 424], [0, 369, 405, 406, 425], [0, 406, 405, 444, 426], [0, 444, 405, 480, 427], [0, 480, 405, 517, 428], [0, 517, 405, 555, 429], [0, 555, 405, 591, 430], [0, 591, 405, 628, 431], [0, 628, 405, 666, 11428]], [[0, 0, 396, 38, 436], [0, 38, 396, 76, 437], [0, 76, 396, 115, 438], [0, 115, 396, 153, 439], [0, 153, 396, 191, 440], [0, 191, 396, 229, 441], [0, 229, 396, 268, 442], [0, 268, 396, 306, 443], [0, 306, 396, 344, 444], [0, 344, 396, 382, 445], [0, 382, 396, 421, 446], [0, 421, 396, 459, 447], [0, 459, 396, 497, 448], [0, 497, 396, 535, 449], [0, 535, 396, 574, 450], [0, 574, 396, 612, 451], [0, 612, 396, 650, 452], [0, 650, 396, 672, 9853]], [[0, 0, 402, 36, 457], [0, 36, 402, 73, 458], [0, 73, 402, 110, 459], [0, 110, 402, 147, 460], [0, 147, 402, 184, 461], [0, 184, 402, 222, 462], [0, 222, 402, 258, 463], [0, 258, 402, 295, 464], [0, 295, 402, 333, 465], [0, 333, 402, 369, 466], [0, 369, 402, 406, 467], [0, 406, 402, 444, 468], [0, 444, 402, 480, 469], [0, 480, 402, 517, 470], [0, 517, 402, 555, 471], [0, 555, 402, 591, 472], [0, 591, 402, 628, 473], [0, 628, 402, 666, 9852]], [[0, 0, 405, 36, 478], [0, 36, 405, 73, 479], [0, 73, 405, 110, 480], [0, 110, 405, 147, 481], [0, 147, 405, 185, 482], [0, 185, 405, 221, 483], [0, 221, 405, 259, 484], [0, 259, 405, 296, 485], [0, 296, 405, 333, 486], [0, 333, 405, 370, 487], [0, 370, 405, 407, 488], [0, 407, 405, 444, 489], [0, 444, 405, 481, 490], [0, 481, 405, 518, 491], [0, 518, 405, 555, 492], [0, 555, 405, 593, 493], [0, 593, 405, 629, 494], [0, 629, 405, 667, 11428]], [[0, 0, 405, 36, 499], [0, 36, 405, 73, 500], [0, 73, 405, 110, 501], [0, 110, 405, 147, 502], [0, 147, 405, 184, 503], [0, 184, 405, 222, 504], [0, 222, 405, 258, 505], [0, 258, 405, 295, 506], [0, 295, 405, 333, 507], [0, 333, 405, 369, 508], [0, 369, 405, 406, 509], [0, 406, 405, 444, 510], [0, 444, 405, 480, 511], [0, 480, 405, 517, 512], [0, 517, 405, 555, 513], [0, 555, 405, 591, 514], [0, 591, 405, 628, 515], [0, 628, 405, 666, 11428]], [[0, 0, 402, 36, 520], [0, 36, 402, 73, 521], [0, 73, 402, 110, 522], [0, 110, 402, 147, 523], [0, 147, 402, 184, 524], [0, 184, 402, 222, 525], [0, 222, 402, 258, 526], [0, 258, 402, 295, 527], [0, 295, 402, 333, 528], [0, 333, 402, 369, 529], [0, 369, 402, 406, 530], [0, 406, 402, 444, 531], [0, 444, 402, 480, 532], [0, 480, 402, 517, 533], [0, 517, 402, 555, 534], [0, 555, 402, 591, 535], [0, 591, 402, 628, 536], [0, 628, 402, 666, 9852]], [[0, 0, 408, 37, 9858], [0, 37, 408, 73, 541], [0, 73, 408, 110, 542], [0, 110, 408, 147, 543], [0, 147, 408, 184, 544], [0, 184, 408, 220, 545], [0, 220, 408, 257, 546], [0, 257, 408, 294, 547], [0, 294, 408, 331, 548], [0, 331, 408, 367, 549], [0, 367, 408, 404, 550], [0, 404, 408, 441, 551], [0, 441, 408, 478, 552], [0, 478, 408, 514, 553], [0, 514, 408, 551, 554], [0, 551, 408, 588, 555], [0, 588, 408, 625, 556], [0, 625, 408, 661, 557], [0, 661, 408, 679, 9859]], [[0, 0, 401, 38, 562], [0, 38, 401, 75, 563], [0, 75, 401, 113, 564], [0, 113, 401, 150, 565], [0, 150, 401, 188, 566], [0, 188, 401, 225, 567], [0, 225, 401, 263, 568], [0, 263, 401, 300, 569], [0, 300, 401, 338, 570], [0, 338, 401, 375, 571], [0, 375, 401, 413, 572], [0, 413, 401, 450, 573], [0, 450, 401, 488, 574], [0, 488, 401, 525, 575], [0, 525, 401, 563, 576], [0, 563, 401, 600, 577], [0, 600, 401, 638, 578], [0, 638, 401, 674, 9860]], [[0, 0, 402, 36, 583], [0, 36, 402, 73, 584], [0, 73, 402, 110, 585], [0, 110, 402, 147, 586], [0, 147, 402, 184, 587], [0, 184, 402, 222, 588], [0, 222, 402, 258, 589], [0, 258, 402, 295, 590], [0, 295, 402, 333, 591], [0, 333, 402, 369, 592], [0, 369, 402, 406, 593], [0, 406, 402, 444, 594], [0, 444, 402, 480, 595], [0, 480, 402, 517, 596], [0, 517, 402, 555, 597], [0, 555, 402, 591, 598], [0, 591, 402, 628, 599], [0, 628, 402, 666, 600]], [[0, 0, 405, 36, 605], [0, 36, 405, 73, 606], [0, 73, 405, 110, 607], [0, 110, 405, 147, 608], [0, 147, 405, 184, 609], [0, 184, 405, 222, 610], [0, 222, 405, 258, 611], [0, 258, 405, 295, 612], [0, 295, 405, 333, 613], [0, 333, 405, 369, 614], [0, 369, 405, 406, 615], [0, 406, 405, 444, 616], [0, 444, 405, 480, 617], [0, 480, 405, 517, 618], [0, 517, 405, 555, 619], [0, 555, 405, 591, 620], [0, 591, 405, 628, 621], [0, 628, 405, 666, 11428]], [[0, 0, 402, 36, 9852], [0, 36, 402, 73, 626], [0, 73, 402, 110, 627], [0, 110, 402, 147, 628], [0, 147, 402, 184, 629], [0, 184, 402, 222, 630], [0, 222, 402, 258, 631], [0, 258, 402, 295, 632], [0, 295, 402, 333, 633], [0, 333, 402, 369, 634], [0, 369, 402, 406, 635], [0, 406, 402, 444, 636], [0, 444, 402, 480, 637], [0, 480, 402, 517, 638], [0, 517, 402, 555, 639], [0, 555, 402, 591, 640], [0, 591, 402, 628, 641], [0, 628, 402, 666, 642]], [[0, 0, 406, 36, 647], [0, 36, 406, 73, 648], [0, 73, 406, 110, 649], [0, 110, 406, 147, 650], [0, 147, 406, 185, 651], [0, 185, 406, 221, 652], [0, 221, 406, 259, 653], [0, 259, 406, 296, 654], [0, 296, 406, 333, 655], [0, 333, 406, 370, 656], [0, 370, 406, 407, 657], [0, 407, 406, 444, 658], [0, 444, 406, 481, 659], [0, 481, 406, 518, 660], [0, 518, 406, 555, 661], [0, 555, 406, 593, 662], [0, 593, 406, 629, 663], [0, 629, 406, 667, 9861]], [[0, 0, 396, 38, 668], [0, 38, 396, 76, 669], [0, 76, 396, 114, 670], [0, 114, 396, 152, 671], [0, 152, 396, 191, 672], [0, 191, 396, 229, 673], [0, 229, 396, 267, 674], [0, 267, 396, 305, 675], [0, 305, 396, 344, 676], [0, 344, 396, 382, 677], [0, 382, 396, 420, 678], [0, 420, 396, 458, 679], [0, 458, 396, 497, 680], [0, 497, 396, 535, 681], [0, 535, 396, 573, 682], [0, 573, 396, 611, 683], [0, 611, 396, 650, 684], [0, 650, 396, 671, 9853]], [[0, 0, 405, 36, 689], [0, 36, 405, 73, 690], [0, 73, 405, 110, 691], [0, 110, 405, 147, 692], [0, 147, 405, 184, 693], [0, 184, 405, 222, 694], [0, 222, 405, 258, 695], [0, 258, 405, 295, 696], [0, 295, 405, 333, 697], [0, 333, 405, 369, 698], [0, 369, 405, 406, 699], [0, 406, 405, 444, 700], [0, 444, 405, 480, 701], [0, 480, 405, 517, 702], [0, 517, 405, 555, 703], [0, 555, 405, 591, 704], [0, 591, 405, 628, 705], [0, 628, 405, 666, 11428]], [[0, 0, 401, 38, 710], [0, 38, 401, 75, 711], [0, 75, 401, 113, 712], [0, 113, 401, 150, 713], [0, 150, 401, 188, 714], [0, 188, 401, 225, 715], [0, 225, 401, 263, 716], [0, 263, 401, 300, 717], [0, 300, 401, 338, 718], [0, 338, 401, 375, 719], [0, 375, 401, 413, 720], [0, 413, 401, 450, 721], [0, 450, 401, 488, 722], [0, 488, 401, 525, 723], [0, 525, 401, 563, 724], [0, 563, 401, 600, 725], [0, 600, 401, 638, 726], [0, 638, 401, 674, 9860]], [[0, 0, 400, 38, 731], [0, 38, 400, 75, 732], [0, 75, 400, 113, 733], [0, 113, 400, 150, 734], [0, 150, 400, 188, 735], [0, 188, 400, 225, 736], [0, 225, 400, 263, 737], [0, 263, 400, 300, 738], [0, 300, 400, 338, 739], [0, 338, 400, 375, 740], [0, 375, 400, 413, 741], [0, 413, 400, 450, 742], [0, 450, 400, 488, 743], [0, 488, 400, 525, 744], [0, 525, 400, 563, 745], [0, 563, 400, 600, 746], [0, 600, 400, 638, 747], [0, 638, 400, 674, 9860]], [[0, 0, 396, 38, 752], [0, 38, 396, 76, 753], [0, 76, 396, 114, 754], [0, 114, 396, 152, 755], [0, 152, 396, 191, 756], [0, 191, 396, 229, 757], [0, 229, 396, 267, 758], [0, 267, 396, 305, 759], [0, 305, 396, 344, 760], [0, 344, 396, 382, 761], [0, 382, 396, 420, 762], [0, 420, 396, 458, 763], [0, 458, 396, 497, 764], [0, 497, 396, 535, 765], [0, 535, 396, 573, 766], [0, 573, 396, 611, 767], [0, 611, 396, 650, 768], [0, 650, 396, 671, 9853]], [[0, 0, 396, 38, 773], [0, 38, 396, 76, 774], [0, 76, 396, 114, 775], [0, 114, 396, 152, 776], [0, 152, 396, 191, 777], [0, 191, 396, 229, 778], [0, 229, 396, 267, 779], [0, 267, 396, 305, 780], [0, 305, 396, 344, 781], [0, 344, 396, 382, 782], [0, 382, 396, 420, 783], [0, 420, 396, 458, 784], [0, 458, 396, 497, 785], [0, 497, 396, 535, 786], [0, 535, 396, 573, 787], [0, 573, 396, 611, 788], [0, 611, 396, 650, 789], [0, 650, 396, 671, 9853]], [[0, 0, 408, 36, 9858], [0, 36, 408, 73, 794], [0, 73, 408, 110, 795], [0, 110, 408, 146, 796], [0, 146, 408, 183, 797], [0, 183, 408, 220, 798], [0, 220, 408, 257, 799], [0, 257, 408, 293, 800], [0, 293, 408, 330, 801], [0, 330, 408, 367, 802], [0, 367, 408, 404, 803], [0, 404, 408, 440, 804], [0, 440, 408, 477, 805], [0, 477, 408, 514, 806], [0, 514, 408, 551, 807], [0, 551, 408, 587, 808], [0, 587, 408, 624, 809], [0, 624, 408, 661, 810], [0, 661, 408, 677, 9862]], [[0, 0, 396, 38, 815], [0, 38, 396, 76, 816], [0, 76, 396, 114, 817], [0, 114, 396, 153, 818], [0, 153, 396, 191, 819], [0, 191, 396, 229, 820], [0, 229, 396, 267, 821], [0, 267, 396, 306, 822], [0, 306, 396, 344, 823], [0, 344, 396, 382, 824], [0, 382, 396, 420, 825], [0, 420, 396, 459, 826], [0, 459, 396, 497, 827], [0, 497, 396, 535, 828], [0, 535, 396, 573, 829], [0, 573, 396, 612, 830], [0, 612, 396, 650, 831], [0, 650, 396, 672, 9853]], [[0, 0, 410, 37, 9863], [0, 37, 410, 73, 836], [0, 73, 410, 110, 837], [0, 110, 410, 147, 838], [0, 147, 410, 184, 839], [0, 184, 410, 220, 840], [0, 220, 410, 257, 841], [0, 257, 410, 294, 842], [0, 294, 410, 331, 843], [0, 331, 410, 367, 844], [0, 367, 410, 404, 845], [0, 404, 410, 441, 846], [0, 441, 410, 478, 847], [0, 478, 410, 514, 848], [0, 514, 410, 551, 849], [0, 551, 410, 588, 850], [0, 588, 410, 625, 851], [0, 625, 410, 661, 852], [0, 661, 410, 679, 9864]], [[0, 0, 396, 38, 857], [0, 38, 396, 76, 858], [0, 76, 396, 114, 859], [0, 114, 396, 153, 860], [0, 153, 396, 191, 861], [0, 191, 396, 229, 862], [0, 229, 396, 267, 863], [0, 267, 396, 306, 864], [0, 306, 396, 344, 865], [0, 344, 396, 382, 866], [0, 382, 396, 420, 867], [0, 420, 396, 459, 868], [0, 459, 396, 497, 869], [0, 497, 396, 535, 870], [0, 535, 396, 573, 871], [0, 573, 396, 612, 872], [0, 612, 396, 650, 873], [0, 650, 396, 672, 9853]], [[0, 0, 396, 38, 878], [0, 38, 396, 76, 879], [0, 76, 396, 114, 880], [0, 114, 396, 152, 881], [0, 152, 396, 191, 882], [0, 191, 396, 229, 883], [0, 229, 396, 267, 884], [0, 267, 396, 305, 885], [0, 305, 396, 344, 886], [0, 344, 396, 382, 887], [0, 382, 396, 420, 888], [0, 420, 396, 458, 889], [0, 458, 396, 497, 890], [0, 497, 396, 535, 891], [0, 535, 396, 573, 892], [0, 573, 396, 611, 893], [0, 611, 396, 650, 894], [0, 650, 396, 671, 9853]], [[0, 0, 402, 36, 899], [0, 36, 402, 73, 900], [0, 73, 402, 110, 901], [0, 110, 402, 147, 902], [0, 147, 402, 184, 903], [0, 184, 402, 222, 904], [0, 222, 402, 258, 905], [0, 258, 402, 295, 906], [0, 295, 402, 333, 907], [0, 333, 402, 369, 908], [0, 369, 402, 406, 909], [0, 406, 402, 444, 910], [0, 444, 402, 480, 911], [0, 480, 402, 517, 912], [0, 517, 402, 555, 913], [0, 555, 402, 591, 914], [0, 591, 402, 628, 915], [0, 628, 402, 666, 916]], [[0, 0, 402, 36, 921], [0, 36, 402, 73, 922], [0, 73, 402, 110, 923], [0, 110, 402, 147, 924], [0, 147, 402, 184, 925], [0, 184, 402, 222, 926], [0, 222, 402, 258, 927], [0, 258, 402, 295, 928], [0, 295, 402, 333, 929], [0, 333, 402, 369, 930], [0, 369, 402, 406, 931], [0, 406, 402, 444, 932], [0, 444, 402, 480, 933], [0, 480, 402, 517, 934], [0, 517, 402, 555, 935], [0, 555, 402, 591, 936], [0, 591, 402, 628, 937], [0, 628, 402, 666, 938]], [[0, 0, 406, 36, 943], [0, 36, 406, 73, 944], [0, 73, 406, 110, 945], [0, 110, 406, 147, 946], [0, 147, 406, 185, 947], [0, 185, 406, 221, 948], [0, 221, 406, 259, 949], [0, 259, 406, 296, 950], [0, 296, 406, 333, 951], [0, 333, 406, 370, 952], [0, 370, 406, 407, 953], [0, 407, 406, 444, 954], [0, 444, 406, 481, 955], [0, 481, 406, 518, 956], [0, 518, 406, 555, 957], [0, 555, 406, 593, 958], [0, 593, 406, 629, 959], [0, 629, 406, 667, 960]], [[0, 0, 405, 36, 965], [0, 36, 405, 73, 966], [0, 73, 405, 110, 967], [0, 110, 405, 147, 968], [0, 147, 405, 185, 969], [0, 185, 405, 221, 970], [0, 221, 405, 259, 971], [0, 259, 405, 296, 972], [0, 296, 405, 333, 973], [0, 333, 405, 370, 974], [0, 370, 405, 407, 975], [0, 407, 405, 444, 976], [0, 444, 405, 481, 977], [0, 481, 405, 518, 978], [0, 518, 405, 555, 979], [0, 555, 405, 593, 980], [0, 593, 405, 629, 981], [0, 629, 405, 667, 11428]], [[0, 0, 410, 37, 9863], [0, 37, 410, 73, 986], [0, 73, 410, 110, 987], [0, 110, 410, 147, 988], [0, 147, 410, 184, 989], [0, 184, 410, 220, 990], [0, 220, 410, 257, 991], [0, 257, 410, 294, 992], [0, 294, 410, 331, 993], [0, 331, 410, 367, 994], [0, 367, 410, 404, 995], [0, 404, 410, 441, 996], [0, 441, 410, 478, 997], [0, 478, 410, 514, 998], [0, 514, 410, 551, 999], [0, 551, 410, 588, 1000], [0, 588, 410, 625, 1001], [0, 625, 410, 661, 1002], [0, 661, 410, 679, 9864]]],
"expected_junk_img_bojids": []
},
"scihub/scihub_25800000/libgen.scimag25889000-25889999.zip_10.2307/4153991" : {
"expected_image_info": [[[50,726,110,792,21],[50,80,202,230,22]],[[0,0,468,720,17]],[[0,0,468,720,31]]],
"expected_junk_img_bojids": []
},
"scanned_detection/llm-raw-scihub-o.O-0584-8539%2891%2980165-f" : {
"expected_image_info": [[[0, 0, 504, 29, 33], [0, 29, 504, 59, 35], [0, 59, 504, 89, 37], [0, 89, 504, 119, 39], [0, 119, 504, 148, 41], [0, 148, 504, 178, 43], [0, 178, 504, 208, 45], [0, 208, 504, 238, 47], [0, 238, 504, 267, 49], [0, 267, 504, 297, 51], [0, 297, 504, 327, 53], [0, 327, 504, 357, 55], [0, 357, 504, 386, 57], [0, 386, 504, 416, 59], [0, 416, 504, 446, 61], [0, 446, 504, 476, 63], [0, 476, 504, 505, 65], [0, 505, 504, 535, 67], [0, 535, 504, 565, 69], [0, 565, 504, 595, 71], [0, 595, 504, 624, 73], [0, 624, 504, 654, 75], [0, 654, 504, 684, 77], [0, 684, 504, 714, 79], [0, 714, 504, 744, 81], [0, 773, 504, 792, 83]]],
"expected_junk_img_bojids": []
},
"scanned_detection/llm-raw-scihub-o.O-bf01427123" : {
"expected_image_info": [[[0, 0, 532, 698, 76]], [[0, 0, 532, 698, 14]], [[0, 0, 532, 698, 30]]],
"expected_junk_img_bojids": []
},
"scihub/scihub_25900000/libgen.scimag25991000-25991999.zip_10.2307/40066695" : {
"expected_image_info": [[[50, 726, 110, 792, 113], [50, 80, 168, 230, 114]], [[0, 709, 468, 717, 17], [0, 226, 468, 233, 21], [0, 218, 468, 226, 22], [0, 233, 468, 241, 33], [0, 272, 468, 280, 39], [0, 280, 468, 288, 41], [0, 288, 468, 296, 42], [0, 296, 468, 304, 43], [0, 241, 468, 249, 44], [0, 249, 468, 257, 45], [0, 257, 468, 265, 46], [0, 265, 468, 272, 47], [0, 592, 468, 600, 50], [0, 304, 468, 311, 53], [0, 545, 468, 553, 54], [0, 577, 468, 584, 55], [0, 569, 468, 577, 56], [0, 561, 468, 569, 57], [0, 553, 468, 561, 58], [0, 311, 468, 319, 59], [0, 319, 468, 327, 60], [0, 374, 468, 382, 61], [0, 382, 468, 389, 62], [0, 358, 468, 366, 63], [0, 366, 468, 374, 64], [0, 343, 468, 350, 65], [0, 350, 468, 358, 66], [0, 327, 468, 335, 67], [0, 335, 468, 343, 68], [0, 538, 468, 545, 69], [0, 530, 468, 538, 70], [0, 506, 468, 514, 71], [0, 499, 468, 506, 72], [0, 522, 468, 530, 73], [0, 514, 468, 522, 74], [0, 475, 468, 483, 75], [0, 467, 468, 475, 76], [0, 491, 468, 499, 77], [0, 483, 468, 491, 78], [0, 116, 468, 124, 84], [0, 124, 468, 132, 85], [0, 460, 468, 467, 86], [0, 148, 468, 155, 87], [0, 452, 468, 460, 88], [0, 140, 468, 148, 89], [0, 444, 468, 452, 90], [0, 132, 468, 140, 91], [0, 436, 468, 444, 93], [0, 717, 468, 720, 94], [0, 428, 468, 436, 95], [0, 421, 468, 428, 96], [0, 413, 468, 421, 98], [0, 405, 468, 413, 99], [0, 397, 468, 405, 100], [0, 389, 468, 397, 101], [0, 171, 468, 179, 102], [0, 179, 468, 187, 103], [0, 155, 468, 163, 104], [0, 163, 468, 171, 105], [0, 202, 468, 210, 106], [0, 210, 468, 218, 107], [0, 187, 468, 194, 108], [0, 194, 468, 202, 109]], [[0, 709, 468, 717, 123], [0, 210, 468, 218, 133], [0, 226, 468, 233, 134], [0, 218, 468, 226, 135], [0, 241, 468, 249, 136], [0, 233, 468, 241, 137], [0, 257, 468, 265, 138], [0, 249, 468, 257, 139], [0, 272, 468, 280, 140], [0, 265, 468, 272, 141], [0, 280, 468, 288, 142], [0, 124, 468, 132, 143], [0, 592, 468, 600, 144], [0, 140, 468, 148, 154], [0, 132, 468, 140, 155], [0, 171, 468, 179, 156], [0, 163, 468, 171, 157], [0, 155, 468, 163, 158], [0, 148, 468, 155, 159], [0, 202, 468, 210, 160], [0, 194, 468, 202, 161], [0, 187, 468, 194, 162], [0, 179, 468, 187, 163], [0, 608, 468, 616, 164], [0, 319, 468, 327, 165], [0, 600, 468, 608, 166], [0, 327, 468, 335, 167], [0, 335, 468, 343, 169], [0, 343, 468, 350, 171], [0, 350, 468, 358, 173], [0, 358, 468, 366, 175], [0, 288, 468, 296, 180], [0, 296, 468, 304, 181], [0, 304, 468, 311, 182], [0, 311, 468, 319, 183], [0, 116, 468, 124, 187], [0, 717, 468, 720, 206], [0, 366, 468, 374, 207], [0, 389, 468, 397, 208], [0, 374, 468, 382, 212], [0, 382, 468, 389, 213]]]
},
"scihub/scihub_53700000/libgen.scimag53724000-53724999.zip_10.1097/00129191-200509000-00018": {
"expected_image_info": [[[-2, 0, 603, 80, 24]], [[-3, 0, 602, 80, 24]]]
},
"zlib/zlib_22115997": {
"expected_image_info": [[[0, 0, 426, 603, 11080]], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []],
"expected_junk_img_bojids": [3830, 3831, 3832, 3837, 3833, 3838, 3842, 3834, 3835, 3836, 3839, 3840, 3841, 3872, 3854, 3868, 3850, 3869, 3847, 3873, 3866, 3870, 3857, 3858, 3871, 3855, 3849, 3874, 3843, 3859, 3844, 3853, 3860, 3856, 3851, 3861, 3862, 3845, 3846, 3863, 3848, 3864, 3865, 3867, 3852, 3899, 3906, 3894, 3903, 3902, 3901, 3895, 3905, 3884, 3879, 3904, 3875, 3876, 3889, 3888, 3877, 3882, 3885, 3878, 3896, 3880, 3881, 3890, 3900, 3883, 3891, 3893, 3886, 3887, 3892, 3897, 3898, 3918, 3922, 3936, 3913, 3938, 3920, 3908, 3937, 3909, 3926, 3923, 3919, 3933, 3907, 3934, 3914, 3921, 3931, 3915, 3916, 3924, 3925, 3910, 3927, 3935, 3928, 3929, 3930, 3932, 3911, 3912, 3917, 3965, 3960, 3942, 3951, 3958, 3946, 3952, 3947, 3939, 3963, 3943, 3968, 3969, 3950, 3964, 3961, 3962, 3944, 3966, 3970, 3959, 3967, 3940, 3941, 3945, 3948, 3953, 3949, 3954, 3955, 3956, 3957, 3982, 3991, 3998, 3984, 3975, 4002, 3974, 3999, 3976, 4000, 3985, 3992, 4001, 3971, 3989, 3988, 3983, 3977, 3980, 3997, 3986, 3990, 3993, 3987, 3972, 3994, 3995, 3996, 3973, 3978, 3979, 3981, 4006, 4007, 4010, 4011, 4019, 4016, 4009, 4017, 4012, 4008, 4018, 4003, 4013, 4004, 4014, 4005, 4015, 3796, 3789, 3792, 3790, 3797, 3768, 3783, 3791, 3766, 3773, 3778, 3774, 3767, 3788, 3793, 3769, 3775, 3794, 3776, 3777, 3795, 3779, 3784, 3770, 3772, 3771, 3780, 3781, 3785, 3782, 3786, 3787, 3829, 3811, 3802, 3814, 3820, 3822, 3799, 3806, 3823, 3808, 3809, 3816, 3826, 3804, 3805, 3810, 3827, 3812, 3813, 3828, 3807, 3821, 3824, 3815, 3801, 3803, 3817, 3825, 3818, 3819, 3798, 3800, 3765, 2839, 2818, 2824, 2821, 2833, 2813, 2825, 2823, 2837, 2819, 2838, 2816, 2842, 2835, 2840, 2822, 2830, 2814, 2812, 2815, 2841, 2826, 2827, 2832, 2843, 2817, 2820, 2836, 2828, 2829, 2831, 2834, 2866, 2875, 2865, 2867, 2846, 2859, 2854, 2855, 2856, 2861, 2860, 2850, 2857, 2858, 2862, 2853, 2863, 2852, 2848, 2868, 2873, 2869, 2872, 2864, 2870, 2871, 2845, 2874, 2847, 2844, 2849, 2851, 2885, 2898, 2882, 2876, 2886, 2892, 2884, 2880, 2900, 2905, 2899, 2904, 2895, 2887, 2894, 2906, 2890, 2893, 2877, 2889, 2878, 2888, 2896, 2891, 2897, 2901, 2881, 2902, 2907, 2903, 2879, 2883, 2921, 2915, 2916, 2923, 2924, 2939, 2933, 2919, 2935, 2925, 2926, 2912, 2917, 2936, 2937, 2931, 2932, 2918, 2927, 2908, 2922, 2928, 2913, 2920, 2929, 2930, 2934, 2938, 2909, 2910, 2911, 2914, 2953, 2942, 2947, 2950, 2954, 2956, 2940, 2955, 2941, 2944, 2969, 2961, 2957, 2962, 2945, 2946, 2943, 2949, 2958, 2968, 2948, 2951, 2952, 2959, 2960, 2963, 2970, 2964, 2965, 2966, 2967, 2971, 2982, 2978, 3003, 2985, 3001, 2998, 2991, 3002, 2996, 2972, 2973, 2992, 2974, 2975, 3000, 2986, 2983, 2993, 2976, 2999, 2977, 2984, 2979, 2980, 2994, 2987, 2981, 2988, 2995, 2989, 2990, 2997, 3008, 3032, 3015, 3028, 3005, 3012, 3029, 3014, 3016, 3022, 3033, 3010, 3011, 3017, 3034, 3018, 3023, 3035, 3030, 3024, 3004, 3031, 3006, 3007, 3019, 3020, 3021, 3025, 3026, 3027, 3009, 3013, 3057, 3037, 3065, 3038, 3055, 3051, 3066, 3039, 3049, 3058, 3056, 3064, 3052, 3040, 3067, 3059, 3044, 3041, 3060, 3036, 3061, 3042, 3062, 3050, 3063, 3043, 3045, 3053, 3046, 3047, 3048, 3054, 3081, 3072, 3099, 3071, 3089, 3069, 3097, 3070, 3087, 3083, 3079, 3077, 3090, 3074, 3091, 3068, 3073, 3085, 3095, 3080, 3075, 3092, 3076, 3082, 3088, 3093, 3094, 3098, 3096, 3078, 3084, 3086, 3125, 3110, 3111, 3126, 3107, 3112, 3108, 3100, 3124, 3113, 3115, 3101, 3114, 3122, 3103, 3127, 3104, 3129, 3105, 3121, 3123, 3106, 3128, 3130, 3116, 3117, 3131, 3109, 3118, 3119, 3120, 3102, 3150, 3138, 3143, 3146, 3136, 3132, 3145, 3151, 3147, 3141, 3148, 3142, 3152, 3154, 3153, 3133, 3137, 3168, 3164, 3173, 3174, 3160, 3167, 3169, 3170, 3157, 3176, 3163, 3197, 3192, 3190, 3187, 3188, 3189, 3194, 3186, 3193, 3196, 3204, 3203, 3212, 3211, 3220, 3201, 3199, 3205, 3200, 3214, 3216, 3223, 3241, 3227, 3235, 3224, 3222, 3225, 3221, 3226, 3233, 3238, 3253, 3260, 3250, 3254, 3251, 3252, 3257, 3243, 3258, 3247, 3281, 3272, 3284, 3278, 3275, 3274, 3270, 3277, 3264, 3269, 3265, 3288, 3304, 3305, 3294, 3286, 3300, 3291, 3287, 3293, 3290, 3295, 3307, 3322, 3323, 3309, 3317, 3308, 3312, 3310, 3314, 3320, 3328, 3348, 3329, 3327, 3332, 3337, 3345, 3346, 3331, 3343, 3347, 3367, 3358, 3351, 3350, 3356, 3369, 3361, 3362, 3364, 3365, 3366, 3390, 3379, 3373, 3386, 3387, 3374, 3385, 3375, 3378, 3389, 3407, 3401, 3391, 3406, 3411, 3398, 3409, 3392, 3393, 3402, 3394, 3431, 3427, 3416, 3430, 3418, 3429, 3414, 3424, 3421, 3422, 3428, 3439, 3451, 3443, 3450, 3436, 3440, 3434, 3448, 3452, 3437, 3464, 3471, 3462, 3465, 3461, 3456, 3457, 3475, 3468, 3459, 3467, 3493, 3494, 3482, 3496, 3497, 3484, 3478, 3488, 3479, 3491, 3481, 3510, 3505, 3506, 3512, 3504, 3501, 3508, 3500, 3509, 3513, 3540, 3521, 3527, 3528, 3534, 3537, 3520, 3535, 3529, 3538, 3524, 3551, 3555, 3542, 3556, 3552, 3554, 3544, 3559, 3558, 3546, 3560, 3571, 3572, 3564, 3576, 3573, 3575, 3565, 3577, 3582, 3578, 3598, 3604, 3587, 3602, 3601, 3590, 3588, 3595, 3585, 3593, 3594, 3622, 3623, 3611, 3624, 3625, 3615, 3621, 3616, 3618, 3610, 3620, 3635, 3636, 3629, 3639, 3627, 3630, 3631, 3632, 3633, 3645, 3648, 3655, 3667, 3665, 3666, 3668, 3647, 3656, 3652, 3653, 3664, 3685, 3687, 3673, 3683, 3680, 3688, 3681, 3669, 3684, 3674, 3686, 3703, 3706, 3708, 3698, 3691, 3699, 3704, 3705, 3693, 3694, 3711, 3721, 3723, 3724, 3732, 3727, 3728, 3715, 3730, 3716, 3718, 3743, 3749, 3752, 3741, 3744, 3733, 3742, 3746, 3736, 3737, 3750, 3761, 3755, 3756, 3762, 3764, 2759, 2748, 2762, 2749, 2755, 2768, 2764, 2750, 2751, 2756, 2766, 2780, 2774, 2789, 2771, 2788, 2772, 2783, 2773, 2786, 2787, 2776, 2800, 2809, 2804, 2792, 2811, 2806, 2793, 2807, 2797, 2808, 2325, 2332, 2335, 2341, 2321, 2331, 2333, 2327, 2337, 2324, 2339, 2351, 2344, 2361, 2360, 2343, 2359, 2356, 2347, 2350, 2353, 2357, 2382, 2367, 2383, 2374, 2369, 2379, 2363, 2366, 2365, 2380, 2397, 2401, 2403, 2402, 2392, 2404, 2384, 2385, 2390, 2387, 2394, 2425, 2413, 2411, 2415, 2418, 2426, 2421, 2410, 2420, 2408, 2409, 2445, 2447, 2428, 2438, 2430, 2442, 2433, 2441, 2439, 2443, 2454, 2449, 2451, 2455, 2460, 2465, 2468, 2457, 2461, 2464, 2466, 2486, 2490, 2471, 2470, 2473, 2483, 2472, 2487, 2484, 2485, 2489, 2499, 2511, 2496, 2509, 2502, 2491, 2505, 2506, 2494, 2495, 2532, 2526, 2521, 2531, 2522, 2533, 2515, 2520, 2513, 2524, 2528, 2547, 2551, 2542, 2554, 2543, 2538, 2549, 2548, 2536, 2550, 2537, 2556, 2568, 2559, 2560, 2574, 2570, 2565, 2567, 2575, 2562, 2579, 2597, 2592, 2585, 2577, 2586, 2581, 2587, 2590, 2591, 2593, 2617, 2601, 2605, 2607, 2608, 2610, 2609, 2603, 2613, 2604, 2615, 2622, 2623, 2638, 2625, 2628, 2636, 2637, 2631, 2629, 2633, 2640, 2645, 2660, 2646, 2642, 2657, 2650, 2648, 2651, 2654, 2652, 2677, 2680, 2665, 2671, 2673, 2674, 2676, 2679, 2662, 2664, 2666, 2696, 2685, 2686, 2687, 2702, 2691, 2692, 2693, 2698, 2699, 2719, 2721, 2711, 2705, 2723, 2720, 2704, 2707, 2708, 2712, 2710, 2732, 2739, 2744, 2745, 2743, 2741, 2730, 2746, 2734, 2742, 2735]
},
"zlib/zlib_21814957": {
"expected_image_info": [[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []],
"expected_junk_img_bojids": [8472, 8571, 8572, 8573, 8574, 8575, 8576, 8577, 8578, 8579, 8580, 8482, 8581, 8582, 8583, 8584, 8585, 8586, 8587, 8588, 8589, 8590, 8483, 8591, 8592, 8593, 8594, 8595, 8596, 8597, 8598, 8599, 8600, 8484, 8601, 8602, 8603, 8604, 8605, 8606, 8607, 8608, 8609, 8610, 8485, 8611, 8612, 8613, 8614, 8615, 8616, 8617, 8618, 8619, 8620, 8486, 8621, 8622, 8623, 8624, 8625, 8626, 8627, 8628, 8629, 8630, 8487, 8631, 8632, 8633, 8634, 8635, 8636, 8637, 8638, 8639, 8640, 8488, 8641, 8642, 8643, 8644, 8645, 8646, 8647, 8648, 8649, 8650, 8489, 8651, 8652, 8653, 8654, 8655, 8656, 8657, 8658, 8659, 8660, 8490, 8661, 8662, 8663, 8664, 8665, 8666, 8667, 8668, 8669, 8670, 8491, 8671, 8672, 8673, 8674, 8675, 8676, 8677, 8678, 8679, 8680, 8492, 8681, 8682, 8683, 8684, 8685, 8686, 8687, 8688, 8689, 8690, 8493, 8691, 8692, 8693, 8694, 8695, 8696, 8697, 8698, 8699, 8700, 8494, 8701, 8702, 8703, 8704, 8705, 8706, 8707, 8708, 8709, 8710, 8495, 8711, 8712, 8713, 8714, 8715, 8716, 8717, 8718, 8719, 8720, 8496, 8721, 8722, 8723, 8724, 8725, 8726, 8727, 8728, 8729, 8730, 8497, 8731, 8732, 8733, 8734, 8735, 8736, 8737, 8738, 8739, 8740, 8498, 8741, 8742, 8743, 8744, 8745, 8746, 8747, 8748, 8749, 8750, 8499, 8751, 8752, 8753, 8754, 8755, 8756, 8757, 8758, 8759, 8760, 8500, 8761, 8762, 8763, 8764, 8765, 8766, 8767, 8768, 8769, 8770, 8501, 8771, 8772, 8773, 8774, 8775, 8776, 8777, 8778, 8779, 8780, 8502, 8781, 8782, 8783, 8784, 8785, 8786, 8787, 8788, 8789, 8790, 8503, 8791, 8792, 8793, 8794, 8795, 8796, 8797, 8798, 8799, 8800, 8504, 8801, 8802, 8803, 8804, 8805, 8806, 8807, 8808, 8809, 8810, 8505, 8811, 8812, 8813, 8814, 8815, 8816, 8817, 8818, 8819, 8820, 8506, 8821, 8822, 8823, 8824, 8825, 8826, 8827, 8828, 8829, 8830, 8507, 8831, 8832, 8833, 8834, 8835, 8836, 8837, 8838, 8839, 8840, 8508, 8841, 8842, 8843, 8844, 8845, 8846, 8847, 8848, 8849, 8850, 8509, 8851, 8852, 8853, 8854, 8855, 8856, 8857, 8858, 8859, 8860, 8510, 8861, 8862, 8863, 8864, 8865, 8866, 8867, 8868, 8869, 8870, 8511, 8871, 8872, 8873, 8874, 8875, 8876, 8877, 8878, 8879, 8880, 8512, 8881, 8882, 8883, 8884, 8885, 8886, 8887, 8888, 8889, 8890, 8513, 8891, 8892, 8893, 8894, 8895, 8896, 8897, 8898, 8899, 8900, 8514, 8901, 8902, 8903, 8904, 8905, 8906, 8907, 8908, 8909, 8910, 8515, 8911, 8912, 8913, 8914, 8915, 8916, 8917, 8918, 8919, 8920, 8516, 8921, 8922, 8923, 8924, 8925, 8926, 8927, 8928, 8929, 8930, 8517, 8931, 8932, 8933, 8934, 8935, 8936, 8937, 8938, 8939, 8940, 8518, 8941, 8942, 8943, 8944, 8945, 8946, 8947, 8948, 8949, 8950, 8519, 8951, 8952, 8953, 8954, 8955, 8956, 8957, 8958, 8959, 8960, 8520, 8961, 8962, 8963, 8964, 8965, 8966, 8967, 8968, 8969, 8970, 8476, 8521, 8971, 8972, 8973, 8974, 8975, 8976, 8977, 8978, 8979, 8980, 8522, 8981, 8982, 8983, 8984, 8985, 8986, 8987, 8988, 8989, 8990, 8523, 8991, 8992, 8993, 8994, 8995, 8996, 8997, 8998, 8999, 9000, 8524, 9001, 9002, 9003, 9004, 9005, 9006, 9007, 9008, 9009, 9010, 8525, 9011, 9012, 9013, 9014, 9015, 9016, 9017, 9018, 9019, 9020, 8526, 9021, 9022, 9023, 9024, 9025, 9026, 9027, 9028, 9029, 9030, 8527, 9031, 9032, 9033, 9034, 9035, 9036, 9037, 9038, 9039, 9040, 8528, 9041, 9042, 9043, 9044, 9045, 9046, 9047, 9048, 9049, 9050, 8529, 9051, 9052, 9053, 9054, 9055, 9056, 9057, 9058, 9059, 9060, 8530, 9061, 9062, 9063, 9064, 9065, 9066, 9067, 9068, 9069, 9070, 8531, 9071, 9072, 9073, 9074, 9075, 9076, 9077, 9078, 9079, 9080, 8532, 9081, 9082, 9083, 9084, 9085, 9086, 9087, 9088, 9089, 9090, 8533, 9091, 9092, 9093, 9094, 9095, 9096, 9097, 9098, 9099, 8534, 8535, 8536, 8537, 8538, 8539, 8540, 8478, 8541, 8542, 8543, 8544, 8545, 8546, 8547, 8548, 8549, 8550, 8479, 8551, 8552, 8553, 8554, 8555, 8556, 8557, 8558, 8559, 8560, 8480, 8561, 8562, 8563, 8564, 8565, 8566, 8567, 8568, 8569, 8570, 9100, 9102, 9104, 9106, 9108, 9110, 9112, 9114, 9116, 9118, 9120, 9122, 9124, 9126, 9128, 9130, 9132, 9134, 9136, 9138, 9140, 9142, 9144, 9146, 9148, 9150, 9152, 9154, 9156, 9158, 9160, 9162, 9164, 9166, 9168, 9170, 9172, 9174, 9176, 9178, 9180, 9182, 9184, 9186, 9188, 9190, 9192, 9194, 9196, 9198, 9200, 9202, 9204, 9206, 9208, 9210, 9212, 9214, 9216, 9218, 9220, 9222, 9224, 9226, 9228, 9230, 9232, 9234, 9236, 9238, 9240, 9242, 9244, 9246, 9248, 9250, 9252, 9254, 9256, 9258, 9260, 9262, 9264, 9266, 9268, 9270, 9272, 9274, 9276, 9278, 9280, 9282, 9284, 9286, 9288, 9290, 9292, 9294, 9296, 9298, 9300, 9302, 9304, 9306, 9308, 9310, 9312, 9314, 9316, 9318, 9320, 9322, 9324, 9326, 9328, 9330, 9332, 9334, 9336, 9338, 9340, 9342, 9344, 9346, 9348, 9350, 9352, 9354, 9356, 9358, 9360, 9362, 9364, 9366, 9368, 9370, 9372, 9374, 9376, 9378, 9380, 9382, 9384, 9386, 9388, 9390, 9392, 9394, 9396, 9398, 9400, 9402, 9404, 9406, 9408, 9410, 9412, 9414, 9416, 9418, 9420, 9422, 9424, 9426, 9428, 9430, 9432, 9434, 9436, 9438, 9440, 9442, 9444, 9446, 9448, 9450, 9452, 9454, 9456, 9458, 9460, 9462, 9464, 9466, 9468, 9470, 9472, 9474, 9476, 9478, 9480, 9482, 9484, 9486, 9488, 9490, 9492, 9494, 9496, 9498, 9500, 9502, 9504, 9506, 9508, 9510, 9512, 9514, 9516, 9518, 9520, 9522, 9524, 9526, 9528, 9530, 9532, 9534, 9536, 9538, 9540, 9542, 9544, 9546, 9548, 9550, 9552, 9554, 9556, 9558, 9560, 9562, 9564, 9566, 9568, 9570, 9572, 9574, 9576, 9578, 9580, 9582, 9584, 9586, 9588, 9590, 9592, 9594, 9596, 9598, 9600, 9602, 9604, 9606, 9608, 9610, 9612, 9614, 9616, 9618, 9620, 9622, 9624, 9626, 9628, 9630, 9632, 9634, 9636, 9638, 9640, 9642, 9644, 9646, 9648, 9650, 9652, 9654, 9656, 9658, 9660, 9662, 9664, 9666, 9668, 9670, 9672, 9674, 9676, 9678, 9680, 9682, 9684, 9686, 9688, 9690, 9692, 9694, 9696, 9698, 9700, 9702, 9704, 9706, 9708, 9710, 9712, 9714, 9716, 9718, 9720, 9722, 9724, 9726, 9728, 9730, 9732, 9734, 9736, 9738, 9740, 9742, 9744, 9746, 9748, 9750, 9752, 9754, 9756, 9758, 9760, 9762, 9764, 9766, 9768, 9770, 9772, 9774, 9776, 9778, 9780, 9782, 9784, 9786, 9788, 9790, 9792, 9794, 9796, 9798, 9800, 9802, 9804, 9806, 9808, 9810, 9812, 9814, 9816, 9818, 9820, 9822, 9824, 9826, 9828, 9830, 9832, 9834, 9836, 9838, 9840, 9842, 9844, 9846, 9848, 9850, 9852, 9854, 9856, 9858, 9860, 9862, 9864, 9866, 9868, 9870, 9872, 9874, 9876, 9878, 9880, 9882, 9884, 9886, 9888, 9890, 9892, 9894, 9896, 9898, 9900, 9902, 9904, 9906, 9908, 9910, 9912, 9914, 9916, 9918, 9920, 9922, 9924, 9926, 9928, 9930, 9932, 9934, 9936, 9938, 9940, 9942, 9944, 9946, 9948, 9950, 9952, 9954, 9956, 9958, 9960, 9962, 9964, 9966, 9968, 9970, 9972, 9974, 9976, 9978, 9980, 9982, 9984, 9986, 9988, 9990, 9992, 9994, 9996, 9998, 10000, 10002, 10004, 10006, 10008, 10010, 10012, 10014, 10016, 10018, 10020, 10022, 10024, 10026, 10028, 10030, 10032, 10034, 10036, 10038, 10040, 10042, 10044, 10046, 10048, 10050, 10052, 10054, 10056, 10058, 10060, 10062, 10064, 10066, 10068, 10070, 10072, 10074, 10076, 10078, 10080, 10082, 10084, 10086, 10088, 10090, 10092, 10094, 10096, 10098, 10100, 10102, 10104, 10106, 10108, 10110, 10112, 10114, 10116, 10118, 10120, 10122, 10124, 10126, 10128, 10130, 10132, 10134, 10136, 10138, 10140, 10142, 10144, 10146, 10148, 10150, 10152, 10154, 10156, 10158, 10160, 10162, 10164, 10166, 10168, 10170, 10172, 10174, 10176, 10178, 10180, 10182, 10184, 10186, 10188, 10190, 10192, 10194, 10196, 10198, 10200, 10202, 10204, 10206, 10208, 10210, 10212, 10214, 10216, 10218, 10220, 10222, 10224, 10226, 10228, 10230, 10232, 10234, 10236, 10238, 10240, 10242, 10244, 10246, 10248, 10250, 10252, 10254, 10256, 10258, 10260, 10262, 10264, 10266, 10268, 10270, 10272, 10274, 10276, 10278, 10280, 10282, 10284, 10286, 10288, 10290, 10292, 10294, 10296, 10298, 10300, 10302, 10304, 10306, 10308, 10310, 10312, 10314, 10316, 10318, 10320, 10322, 10324, 10326, 10328, 10330, 10332, 10334, 10336, 10338, 10340, 10342, 10344, 10346, 8481, 8477, 8473, 8474, 8475, 10348, 10350, 10352, 10354]
},
"zlib/zlib_21814955": {
"expected_image_info": [[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []],
"expected_junk_img_bojids": [5678, 5687, 5777, 5778, 5779, 5780, 5781, 5782, 5783, 5784, 5785, 5786, 5688, 5787, 5788, 5789, 5790, 5791, 5792, 5793, 5794, 5795, 5796, 5689, 5797, 5798, 5799, 5800, 5801, 5802, 5803, 5804, 5805, 5806, 5690, 5807, 5808, 5809, 5810, 5811, 5812, 5813, 5814, 5815, 5816, 5691, 5817, 5818, 5819, 5820, 5821, 5822, 5823, 5824, 5825, 5826, 5692, 5827, 5828, 5829, 5830, 5831, 5832, 5833, 5834, 5835, 5836, 5693, 5837, 5838, 5839, 5840, 5841, 5842, 5843, 5844, 5845, 5846, 5694, 5847, 5848, 5849, 5850, 5851, 5852, 5853, 5854, 5855, 5856, 5695, 5857, 5858, 5859, 5860, 5861, 5862, 5863, 5864, 5865, 5866, 5696, 5867, 5868, 5869, 5870, 5871, 5872, 5873, 5874, 5875, 5876, 5697, 5877, 5878, 5879, 5880, 5881, 5882, 5883, 5884, 5885, 5886, 5698, 5887, 5888, 5889, 5890, 5891, 5892, 5893, 5894, 5895, 5896, 5699, 5897, 5898, 5899, 5900, 5901, 5902, 5903, 5904, 5905, 5906, 5700, 5907, 5908, 5909, 5910, 5911, 5912, 5913, 5914, 5915, 5916, 5701, 5917, 5918, 5919, 5920, 5921, 5922, 5923, 5924, 5925, 5926, 5702, 5927, 5928, 5929, 5930, 5931, 5932, 5933, 5934, 5935, 5936, 5703, 5937, 5938, 5939, 5940, 5941, 5942, 5943, 5944, 5945, 5946, 5704, 5947, 5948, 5949, 5950, 5951, 5952, 5953, 5954, 5955, 5956, 5705, 5957, 5958, 5959, 5960, 5961, 5962, 5963, 5964, 5965, 5966, 5706, 5967, 5968, 5969, 5970, 5971, 5972, 5973, 5974, 5975, 5976, 5707, 5977, 5978, 5979, 5980, 5981, 5982, 5983, 5984, 5985, 5986, 5708, 5987, 5988, 5989, 5990, 5991, 5992, 5993, 5994, 5995, 5996, 5709, 5997, 5998, 5999, 6000, 6001, 6002, 6003, 6004, 6005, 6006, 5710, 6007, 6008, 6009, 6010, 6011, 6012, 6013, 6014, 6015, 6016, 5711, 6017, 6018, 6019, 6020, 6021, 6022, 6023, 6024, 6025, 6026, 5712, 6027, 6028, 6029, 6030, 6031, 6032, 6033, 6034, 6035, 6036, 5713, 6037, 6038, 6039, 6040, 6041, 6042, 6043, 6044, 6045, 6046, 5714, 6047, 6048, 6049, 6050, 6051, 6052, 6053, 6054, 6055, 6056, 5715, 6057, 6058, 6059, 6060, 6061, 6062, 6063, 6064, 6065, 6066, 5716, 6067, 6068, 6069, 6070, 6071, 6072, 6073, 6074, 6075, 6076, 5717, 6077, 6078, 6079, 6080, 6081, 6082, 6083, 6084, 6085, 6086, 5718, 6087, 6088, 6089, 6090, 6091, 6092, 6093, 6094, 6095, 6096, 5719, 6097, 6098, 6099, 6100, 6101, 6102, 6103, 6104, 6105, 6106, 5720, 6107, 6108, 6109, 6110, 6111, 6112, 6113, 6114, 6115, 6116, 5721, 6117, 6118, 6119, 6120, 6121, 6122, 6123, 6124, 6125, 6126, 5722, 6127, 6128, 6129, 6130, 6131, 6132, 6133, 6134, 6135, 6136, 5723, 6137, 6138, 6139, 6140, 6141, 6142, 6143, 6144, 6145, 6146, 5724, 6147, 6148, 6149, 6150, 6151, 6152, 6153, 6154, 6155, 6156, 5725, 6157, 6158, 6159, 6160, 6161, 6162, 6163, 6164, 6165, 6166, 5726, 6167, 6168, 6169, 6170, 6171, 6172, 6173, 6174, 6175, 6176, 5682, 5727, 6177, 6178, 6179, 6180, 6181, 6182, 6183, 6184, 6185, 6186, 5728, 6187, 6188, 6189, 6190, 6191, 6192, 6193, 6194, 6195, 6196, 5729, 6197, 6198, 6199, 6200, 6201, 6202, 6203, 6204, 6205, 6206, 5730, 6207, 6208, 6209, 6210, 6211, 6212, 6213, 6214, 6215, 6216, 5731, 6217, 6218, 6219, 6220, 6221, 6222, 6223, 6224, 6225, 6226, 5732, 6227, 6228, 6229, 6230, 6231, 6232, 6233, 6234, 6235, 6236, 5733, 6237, 6238, 6239, 6240, 6241, 6242, 6243, 6244, 6245, 6246, 5734, 6247, 5735, 5736, 5737, 5738, 5739, 5740, 5741, 5742, 5743, 5744, 5745, 5746, 5747, 5748, 5749, 5750, 5751, 5752, 5753, 5754, 5755, 5756, 5685, 5757, 5758, 5759, 5760, 5761, 5762, 5763, 5764, 5765, 5766, 5686, 5767, 5768, 5769, 5770, 5771, 5772, 5773, 5774, 5775, 5776, 6248, 6250, 6252, 6254, 6256, 6258, 6260, 6262, 6264, 6266, 6268, 6270, 6272, 6274, 6276, 6278, 6280, 6282, 6284, 6286, 6288, 6290, 6292, 6294, 6296, 6298, 6300, 6302, 6304, 6306, 6308, 6310, 6312, 6314, 6316, 6318, 6320, 6322, 6324, 6326, 6328, 6330, 6332, 6334, 6336, 6338, 6340, 6342, 6344, 6346, 6348, 6350, 6352, 6354, 6356, 6358, 6360, 6362, 6364, 6366, 6368, 6370, 6372, 6374, 6376, 6378, 6380, 6382, 6384, 6386, 6388, 6390, 6392, 6394, 6396, 6398, 6400, 6402, 6404, 6406, 6408, 6410, 6412, 6414, 6416, 6418, 6420, 6422, 6424, 6426, 6428, 6430, 6432, 6434, 6436, 6438, 6440, 6442, 6444, 6446, 6448, 6450, 6452, 6454, 6456, 6458, 6460, 6462, 6464, 6466, 6468, 6470, 6472, 6474, 6476, 6478, 6480, 6482, 6484, 6486, 6488, 6490, 6492, 6494, 6496, 6498, 6500, 6502, 6504, 6506, 6508, 6510, 6512, 6514, 6516, 6518, 6520, 6522, 6524, 6526, 6528, 6530, 6532, 6534, 6536, 6538, 6540, 6542, 6544, 6546, 6548, 6550, 6552, 6554, 6556, 6558, 6560, 6562, 6564, 6566, 6568, 6570, 6572, 6574, 6576, 6578, 6580, 6582, 6584, 6586, 6588, 6590, 6592, 6594, 6596, 6598, 6600, 6602, 6604, 6606, 6608, 6610, 6612, 6614, 6616, 6618, 6620, 6622, 6624, 6626, 6628, 6630, 6632, 6634, 6636, 6638, 6640, 6642, 6644, 6646, 6648, 6650, 6652, 6654, 6656, 6658, 6660, 6662, 6664, 6666, 6668, 6670, 6672, 6674, 6676, 6678, 6680, 6682, 6684, 6686, 6688, 6690, 6692, 6694, 6696, 6698, 6700, 6702, 6704, 6706, 6708, 6710, 6712, 6714, 6716, 6718, 6720, 6722, 6724, 6726, 6728, 6730, 6732, 6734, 6736, 6738, 6740, 6742, 6744, 6746, 6748, 6750, 6752, 6754, 6756, 6758, 6760, 6762, 6764, 6766, 6768, 6770, 6772, 6774, 6776, 6778, 6780, 6782, 6784, 6786, 6788, 6790, 6792, 6794, 6796, 6798, 6800, 6802, 6804, 6806, 6808, 6810, 6812, 6814, 6816, 6818, 6820, 6822, 6824, 6826, 6828, 6830, 6832, 6834, 6836, 6838, 6840, 6842, 6844, 6846, 6848, 6850, 6852, 6854, 6856, 6858, 6860, 6862, 6864, 6866, 6868, 6870, 6872, 6874, 6876, 6878, 6880, 6882, 6884, 6886, 6888, 6890, 6892, 6894, 6896, 6898, 6900, 6902, 6904, 6906, 6908, 6910, 6912, 6914, 6916, 6918, 6920, 6922, 6924, 6926, 6928, 6930, 6932, 6934, 6936, 6938, 6940, 6942, 6944, 6946, 6948, 6950, 6952, 6954, 6956, 6958, 6960, 6962, 6964, 6966, 6968, 6970, 6972, 6974, 6976, 6978, 6980, 6982, 6984, 6986, 6988, 6990, 6992, 6994, 6996, 6998, 7000, 7002, 7004, 7006, 7008, 7010, 7012, 7014, 7016, 7018, 7020, 7022, 7024, 7026, 7028, 7030, 7032, 7034, 7036, 7038, 7040, 7042, 7044, 7046, 7048, 7050, 7052, 7054, 7056, 7058, 7060, 7062, 7064, 7066, 7068, 7070, 7072, 7074, 7076, 7078, 7080, 7082, 7084, 7086, 7088, 7090, 7092, 7094, 7096, 7098, 7100, 7102, 7104, 7106, 7108, 7110, 7112, 7114, 7116, 7118, 7120, 7122, 7124, 7126, 7128, 7130, 7132, 7134, 7136, 7138, 7140, 7142, 7144, 7146, 7148, 7150, 7152, 7154, 7156, 7158, 7160, 7162, 7164, 7166, 7168, 7170, 7172, 7174, 7176, 7178, 7180, 7182, 7184, 7186, 7188, 7190, 7192, 7194, 7196, 7198, 7200, 7202, 7204, 7206, 7208, 7210, 7212, 7214, 7216, 7218, 7220, 7222, 7224, 7226, 7228, 7230, 7232, 7234, 7236, 7238, 7240, 7242, 7244, 7246, 7248, 7250, 7252, 7254, 7256, 7258, 7260, 7262, 7264, 7266, 7268, 7270, 7272, 7274, 7276, 7278, 7280, 7282, 7284, 7286, 7288, 7290, 7292, 7294, 7296, 7298, 7300, 7302, 7304, 7306, 7308, 7310, 7312, 7314, 7316, 7318, 7320, 7322, 7324, 7326, 7328, 7330, 7332, 7334, 7336, 7338, 7340, 7342, 7344, 7346, 7348, 7350, 7352, 7354, 7356, 7358, 7360, 7362, 7364, 7366, 7368, 7370, 7372, 7374, 7376, 7378, 5679, 5680, 5681, 5683, 5684, 7380, 7382, 7384, 7386]
},
"scihub/scihub_41200000/libgen.scimag41253000-41253999.zip_10.1080/00222938709460256": {
"expected_image_info": [[[21, 117, 144, 290, 44]], [], [[0, -9, 383, 602, 84]], [[2, -7, 385, 604, 91]], [[1, -9, 384, 602, 96]], [[1, -9, 384, 602, 104]], [[0, -5, 383, 606, 109]], [[3, -7, 386, 604, 114]], [[0, -6, 383, 605, 119]], [[0, 0, 383, 611, 124]], [[-4, 1, 379, 613, 131]], [[-1, -4, 382, 607, 138]], [[-1, -12, 382, 599, 144]]],
"expected_junk_img_bojids": []
},
"scihub/scihub_37000000/libgen.scimag37068000-37068999.zip_10.1080/0015587X.1936.9718622": {
"expected_image_info": [[[21, 117, 144, 277, 20]], [], [[0, 0, 430, 649, 53]], [[0, 0, 430, 649, 77]], [[0, 0, 430, 649, 80]]],
"expected_junk_img_bojids": []
}
}
tests/unittest/test_model/assets/test_01.model.json deleted 100644 → 0
View file @ 343eaac1
[
{
"layout_dets": [
{
"category_id": 3,
"poly": [
776.7277221679688,
688.448974609375,
1242.224365234375,
688.448974609375,
1242.224365234375,
1182.0628662109375,
776.7277221679688,
1182.0628662109375
],
"score": 0.999997079372406
},
{
"category_id": 3,
"poly": [
775.9269409179688,
1389.754638671875,
1243.672119140625,
1389.754638671875,
1243.672119140625,
1859.716064453125,
775.9269409179688,
1859.716064453125
],
"score": 0.9999949932098389
},
{
"category_id": 1,
"poly": [
752.11572265625,
1939.3634033203125,
1430.1146240234375,
1939.3634033203125,
1430.1146240234375,
2041.1771240234375,
752.11572265625,
2041.1771240234375
],
"score": 0.999975323677063
},
{
"category_id": 3,
"poly": [
46.55152893066406,
686.12939453125,
638.8861083984375,
686.12939453125,
638.8861083984375,
1803.419189453125,
46.55152893066406,
1803.419189453125
],
"score": 0.999961256980896
},
{
"category_id": 3,
"poly": [
33.684722900390625,
150.77980041503906,
1238.0679931640625,
150.77980041503906,
1238.0679931640625,
524.98291015625,
33.684722900390625,
524.98291015625
],
"score": 0.9999504089355469
},
{
"category_id": 1,
"poly": [
24.685693740844727,
1875.9998779296875,
703.5064697265625,
1875.9998779296875,
703.5064697265625,
2050.7431640625,
24.685693740844727,
2050.7431640625
],
"score": 0.9999105334281921
},
{
"category_id": 1,
"poly": [
750.97705078125,
1252.206787109375,
1430.0809326171875,
1252.206787109375,
1430.0809326171875,
1357.2947998046875,
750.97705078125,
1357.2947998046875
],
"score": 0.999853789806366
},
{
"category_id": 4,
"poly": [
904.842041015625,
1213.027099609375,
1273.5655517578125,
1213.027099609375,
1273.5655517578125,
1242.717529296875,
904.842041015625,
1242.717529296875
],
"score": 0.9995817542076111
},
{
"category_id": 4,
"poly": [
905.3208618164062,
1898.5325927734375,
1273.1282958984375,
1898.5325927734375,
1273.1282958984375,
1928.9906005859375,
905.3208618164062,
1928.9906005859375
],
"score": 0.9986443519592285
},
{
"category_id": 4,
"poly": [
372.0135498046875,
556.02685546875,
1084.9647216796875,
556.02685546875,
1084.9647216796875,
586.6792602539062,
372.0135498046875,
586.6792602539062
],
"score": 0.9985352754592896
},
{
"category_id": 2,
"poly": [
1350.63671875,
79.77919006347656,
1379.6220703125,
79.77919006347656,
1379.6220703125,
99.83788299560547,
1350.63671875,
99.83788299560547
],
"score": 0.9973036646842957
},
{
"category_id": 4,
"poly": [
203.2659912109375,
597.2034912109375,
1251.0240478515625,
597.2034912109375,
1251.0240478515625,
657.985595703125,
203.2659912109375,
657.985595703125
],
"score": 0.9622809886932373
},
{
"category_id": 0,
"poly": [
70.87332916259766,
1834.5714111328125,
657.8504638671875,
1834.5714111328125,
657.8504638671875,
1865.07373046875,
70.87332916259766,
1865.07373046875
],
"score": 0.8580453395843506
},
{
"category_id": 1,
"poly": [
189.0360870361328,
597.2406616210938,
1252.3204345703125,
597.2406616210938,
1252.3204345703125,
658.4781494140625,
189.0360870361328,
658.4781494140625
],
"score": 0.3083903193473816
},
{
"category_id": 13,
"poly": [
1190,
1980,
1206,
1980,
1206,
1997,
1190,
1997
],
"score": 0.51,
"latex": ":"
},
{
"category_id": 13,
"poly": [
1219,
1331,
1235,
1331,
1235,
1348,
1219,
1348
],
"score": 0.49,
"latex": ":"
},
{
"category_id": 13,
"poly": [
798,
2016,
813,
2016,
813,
2033,
798,
2033
],
"score": 0.41,
"latex": ":"
},
{
"category_id": 13,
"poly": [
135,
1991,
148,
1991,
148,
2006,
135,
2006
],
"score": 0.39,
"latex": ":"
},
{
"category_id": 13,
"poly": [
400,
1916,
416,
1916,
416,
1933,
400,
1933
],
"score": 0.38,
"latex": ":"
},
{
"category_id": 13,
"poly": [
1148,
1944,
1162,
1944,
1162,
1961,
1148,
1961
],
"score": 0.31,
"latex": ":"
},
{
"category_id": 15,
"poly": [
798.0,
1943.0,
1147.0,
1943.0,
1147.0,
1968.0,
798.0,
1968.0
],
"score": 0.95,
"text": "Fig 4 SSCP analysis of FHIT exon 4. T"
},
{
"category_id": 15,
"poly": [
1163.0,
1943.0,
1425.0,
1943.0,
1425.0,
1968.0,
1163.0,
1968.0
],
"score": 0.96,
"text": "Tumor tissue ; N :Corresponding"
},
{
"category_id": 15,
"poly": [
755.0,
1979.0,
1189.0,
1979.0,
1189.0,
2004.0,
755.0,
2004.0
],
"score": 0.92,
"text": "normal tissue ; M : PBR322/Hae II Marker ; ssDNA"
},
{
"category_id": 15,
"poly": [
1207.0,
1979.0,
1422.0,
1979.0,
1422.0,
2004.0,
1207.0,
2004.0
],
"score": 0.97,
"text": "Single-stranded DNA ; ds-"
},
{
"category_id": 15,
"poly": [
755.0,
2015.0,
797.0,
2015.0,
797.0,
2038.0,
755.0,
2038.0
],
"score": 1.0,
"text": "DNA"
},
{
"category_id": 15,
"poly": [
814.0,
2015.0,
996.0,
2015.0,
996.0,
2038.0,
814.0,
2038.0
],
"score": 0.98,
"text": "Double-stranded DNA"
},
{
"category_id": 15,
"poly": [
71.0,
1880.0,
698.0,
1880.0,
698.0,
1902.0,
71.0,
1902.0
],
"score": 0.96,
"text": "Fig 2Alterations of PCR amplified products of FHIT exon 3,4,5 and"
},
{
"category_id": 15,
"poly": [
28.0,
1916.0,
399.0,
1916.0,
399.0,
1937.0,
28.0,
1937.0
],
"score": 0.98,
"text": "microsatellite marker D3S1300、D3S1312.A"
},
{
"category_id": 15,
"poly": [
417.0,
1916.0,
701.0,
1916.0,
701.0,
1937.0,
417.0,
1937.0
],
"score": 0.9,
"text": "Deletion of exon5(arrows）;B :"
},
{
"category_id": 15,
"poly": [
29.0,
1953.0,
700.0,
1953.0,
700.0,
1974.0,
29.0,
1974.0
],
"score": 0.95,
"text": "Deletion of exon 3 A( arrows）;C : Deletion of microsatellite marker D3S1300,"
},
{
"category_id": 15,
"poly": [
28.0,
1989.0,
134.0,
1989.0,
134.0,
2014.0,
28.0,
2014.0
],
"score": 1.0,
"text": "D3S1312.T"
},
{
"category_id": 15,
"poly": [
149.0,
1989.0,
696.0,
1989.0,
696.0,
2014.0,
149.0,
2014.0
],
"score": 0.96,
"text": "Tumor ; N : Corresponding normal tissue ; L : Corresponding lymph"
},
{
"category_id": 15,
"poly": [
30.0,
2027.0,
634.0,
2027.0,
634.0,
2047.0,
30.0,
2047.0
],
"score": 0.94,
"text": "node tissue;M :DL2000 DNA marker;L1:Lewis ;A :A549;S SPAC-1"
},
{
"category_id": 15,
"poly": [
801.0,
1259.0,
1427.0,
1259.0,
1427.0,
1280.0,
801.0,
1280.0
],
"score": 0.94,
"text": "Fig 3SSCP analysis of FHIT exon 3.The arrow indicateda deletion of"
},
{
"category_id": 15,
"poly": [
757.0,
1294.0,
1424.0,
1294.0,
1424.0,
1318.0,
757.0,
1318.0
],
"score": 0.96,
"text": "exon 3 of 41T. T : Tumor tissue ; N : Corresponding normal tissue ; M PBR322/"
},
{
"category_id": 15,
"poly": [
755.0,
1329.0,
1218.0,
1329.0,
1218.0,
1355.0,
755.0,
1355.0
],
"score": 0.95,
"text": "Hae Il Marker / ssDNA : Single-stranded DNA ; dsDNA"
},
{
"category_id": 15,
"poly": [
1236.0,
1329.0,
1418.0,
1329.0,
1418.0,
1355.0,
1236.0,
1355.0
],
"score": 1.0,
"text": "Double-strandedDNA"
},
{
"category_id": 15,
"poly": [
910.0,
1217.0,
1269.0,
1217.0,
1269.0,
1241.0,
910.0,
1241.0
],
"score": 1.0,
"text": "图3FHIT基因外显子3的SSCP分析"
},
{
"category_id": 15,
"poly": [
909.0,
1904.0,
1269.0,
1904.0,
1269.0,
1927.0,
909.0,
1927.0
],
"score": 1.0,
"text": "图4FHIT基因外显子4的SSCP分析"
},
{
"category_id": 15,
"poly": [
374.0,
563.0,
1077.0,
563.0,
1077.0,
583.0,
374.0,
583.0
],
"score": 0.99,
"text": "图1FHIT基因外显子3、4、5、8和微卫星灶的PCR扩增产物琼脂糖电泳图"
},
{
"category_id": 15,
"poly": [
1351.0,
81.0,
1376.0,
81.0,
1376.0,
102.0,
1351.0,
102.0
],
"score": 1.0,
"text": "13"
},
{
"category_id": 15,
"poly": [
207.0,
600.0,
1245.0,
600.0,
1245.0,
624.0,
207.0,
624.0
],
"score": 0.96,
"text": "Fig 1 Agarose electrophoresis of PCR products of exor( A)3 ,4 ,5 ,8 and three microsatellite markers( B）of FHIT gene"
},
{
"category_id": 15,
"poly": [
309.0,
634.0,
1142.0,
634.0,
1142.0,
662.0,
309.0,
662.0
],
"score": 0.97,
"text": "M1 :DL2000 DNA marker ; M2 PBR322/Hae Il marker ; T :Tumor ; N :Corresponding normal tissue"
},
{
"category_id": 15,
"poly": [
73.0,
1840.0,
651.0,
1840.0,
651.0,
1864.0,
73.0,
1864.0
],
"score": 1.0,
"text": "图2FHIT基因外显子和微卫星灶PCR扩增产物缺失电泳图"
},
{
"category_id": 15,
"poly": [
207.0,
600.0,
1245.0,
600.0,
1245.0,
625.0,
207.0,
625.0
],
"score": 0.96,
"text": "Fig 1 Agarose electrophoresis of PCR products of exor A)3 ,4 ,5 ,8 and three microsatellite markers( B)of FHIT gene"
},
{
"category_id": 15,
"poly": [
309.0,
635.0,
1142.0,
635.0,
1142.0,
661.0,
309.0,
661.0
],
"score": 0.97,
"text": "M1 :DL2000 DNA marker ; M2 PBR322/Hae Il marker ; T Tumor ; N :Corresponding normal tissue"
}
],
"page_info": {
"page_no": 0,
"height": 2080,
"width": 1472
}
}
]
tests/unittest/test_model/assets/test_02.model.json deleted 100644 → 0
View file @ 343eaac1
This source diff could not be displayed because it is too large. You can view the blob instead.
tests/unittest/test_model/test_magic_model.py deleted 100644 → 0
View file @ 343eaac1
import json
from magic_pdf.data.read_api import read_local_pdfs
from magic_pdf.model.magic_model import MagicModel
def test_magic_model_image_v2():
datasets = read_local_pdfs('tests/unittest/test_model/assets/test_01.pdf')
with open('tests/unittest/test_model/assets/test_01.model.json') as f:
model_json = json.load(f)
magic_model = MagicModel(model_json, datasets[0])
imgs = magic_model.get_imgs_v2(0)
print(imgs)
tables = magic_model.get_tables_v2(0)
print(tables)
def test_magic_model_table_v2():
datasets = read_local_pdfs('tests/unittest/test_model/assets/test_02.pdf')
with open('tests/unittest/test_model/assets/test_02.model.json') as f:
model_json = json.load(f)
magic_model = MagicModel(model_json, datasets[0])
tables = magic_model.get_tables_v2(5)
print(tables)
tables = magic_model.get_tables_v2(8)
print(tables)
tests/unittest/test_table/test_rapidtable.py deleted 100644 → 0
View file @ 343eaac1
import unittest
import os
from PIL import Image
from lxml import etree
from magic_pdf.model.sub_modules.model_init import AtomModelSingleton
from magic_pdf.model.sub_modules.table.rapidtable.rapid_table import RapidTableModel
class TestppTableModel(unittest.TestCase):
def test_image2html(self):
img = Image.open(os.path.join(os.path.dirname(__file__), "assets/table.jpg"))
atom_model_manager = AtomModelSingleton()
ocr_engine = atom_model_manager.get_atom_model(
atom_model_name='ocr',
ocr_show_log=False,
det_db_box_thresh=0.5,
det_db_unclip_ratio=1.6,
lang='ch'
)
table_model = RapidTableModel(ocr_engine, 'slanet_plus')
html_code, table_cell_bboxes, logic_points, elapse = table_model.predict(img)
# 验证生成的 HTML 是否符合预期
parser = etree.HTMLParser()
tree = etree.fromstring(html_code, parser)
# 检查 HTML 结构
assert tree.find('.//table') is not None, "HTML should contain a <table> element"
assert tree.find('.//tr') is not None, "HTML should contain a <tr> element"
assert tree.find('.//td') is not None, "HTML should contain a <td> element"
# 检查具体的表格内容
headers = tree.xpath('//table/tr[1]/td')
assert len(headers) == 5, "Thead should have 5 columns"
assert headers[0].text and headers[0].text.strip() == "Methods", "First header should be 'Methods'"
assert headers[1].text and headers[1].text.strip() == "R", "Second header should be 'R'"
assert headers[2].text and headers[2].text.strip() == "P", "Third header should be 'P'"
assert headers[3].text and headers[3].text.strip() == "F", "Fourth header should be 'F'"
assert headers[4].text and headers[4].text.strip() == "FPS", "Fifth header should be 'FPS'"
# 检查第一行数据
first_row = tree.xpath('//table/tr[2]/td')
assert len(first_row) == 5, "First row should have 5 cells"
assert first_row[0].text and 'SegLink' in first_row[0].text.strip(), "First cell should be 'SegLink [26]'"
assert first_row[1].text and first_row[1].text.strip() == "70.0", "Second cell should be '70.0'"
assert first_row[2].text and first_row[2].text.strip() == "86.0", "Third cell should be '86.0'"
assert first_row[3].text and first_row[3].text.strip() == "77.0", "Fourth cell should be '77.0'"
assert first_row[4].text and first_row[4].text.strip() == "8.9", "Fifth cell should be '8.9'"
# 检查倒数第二行数据
second_last_row = tree.xpath('//table/tr[position()=last()-1]/td')
assert len(second_last_row) == 5, "second_last_row should have 5 cells"
assert second_last_row[0].text and second_last_row[0].text.strip() == "Ours (SynText)", "First cell should be 'Ours (SynText)'"
assert second_last_row[1].text and second_last_row[1].text.strip() == "80.68", "Second cell should be '80.68'"
assert second_last_row[2].text and second_last_row[2].text.strip() == "85.40", "Third cell should be '85.40'"
# assert second_last_row[3].text and second_last_row[3].text.strip() == "82.97", "Fourth cell should be '82.97'"
# assert second_last_row[3].text and second_last_row[4].text.strip() == "12.68", "Fifth cell should be '12.68'"
if __name__ == "__main__":
unittest.main()
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment