add comparion script

tests/compare_results.py

+import numpy as np
+import os
+import subprocess
+import json
+import argparse
+
+
+def init_args():
+    parser = argparse.ArgumentParser()
+    # params for prediction engine
+    parser.add_argument("--atol", type=float, default=1e-3)
+    parser.add_argument("--rtol", type=float, default=1e-3)
+    parser.add_argument("--gt_file", type=str, default="")
+    parser.add_argument("--log_file", type=str, default="")
+    return parser
+
+
+def parse_args():
+    parser = init_args()
+    return parser.parse_args()
+
+
+def run_shell_command(cmd):
+    p = subprocess.Popen(
+        cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
+    out, err = p.communicate()
+
+    if p.returncode == 0:
+        return out.decode('utf-8')
+    else:
+        return None
+
+
+def parser_results_from_log_by_name(log_path, names_list):
+    if not os.path.exists(log_path):
+        raise ValueError("The log file {} does not exists!".format(log_path))
+
+    if names_list is None or len(names_list) < 1:
+        return []
+
+    parser_results = {}
+    for name in names_list:
+        cmd = "grep {} {}".format(name, log_path)
+        outs = run_shell_command(cmd)
+        outs = outs.split("\n")[0]
+        result = outs.split("{}".format(name))[-1]
+        result = json.loads(result)
+        parser_results[name] = result
+    return parser_results
+
+
+def load_gt_from_file(gt_file):
+    if not os.path.exists(gt_file):
+        raise ValueError("The log file {} does not exists!".format(gt_file))
+    with open(gt_file, 'r') as f:
+        data = f.readlines()
+        f.close()
+    parser_gt = {}
+    for line in data:
+        image_name, result = line.strip("\n").split("\t")
+        result = json.loads(result)
+        parser_gt[image_name] = result
+    return parser_gt
+
+
+def testing_assert_allclose(dict_x, dict_y, atol=1e-7, rtol=1e-7):
+    for k in dict_x:
+        np.testing.assert_allclose(
+            np.array(dict_x[k]), np.array(dict_y[k]), atol=atol, rtol=rtol)
+
+
+if __name__ == "__main__":
+    # Usage:
+    # python3.7 tests/compare_results.py --gt_file=./det_results_gpu_fp32.txt  --log_file=./test_log.log
+
+    args = parse_args()
+    gt_dict = load_gt_from_file(args.gt_file)
+    key_list = list(gt_dict.keys())
+
+    pred_dict = parser_results_from_log_by_name(args.log_file, key_list)
+
+    testing_assert_allclose(gt_dict, pred_dict, atol=args.atol, rtol=args.rtol)

tools/infer/predict_det.py

@@ -30,7 +30,7 @@ from ppocr.utils.logging import get_logger
 from ppocr.utils.utility import get_image_file_list, check_and_read_gif
 from ppocr.data import create_operators, transform
 from ppocr.postprocess import build_post_process
-
+import json
 logger = get_logger()
 
 
@@ -242,6 +242,7 @@ if __name__ == "__main__":
 
     if not os.path.exists(draw_img_save):
         os.makedirs(draw_img_save)
+    save_results = []
     for image_file in image_file_list:
         img, flag = check_and_read_gif(image_file)
         if not flag:
@@ -255,7 +256,10 @@ if __name__ == "__main__":
         if count > 0:
             total_time += elapse
         count += 1
-
+        save_pred = os.path.basename(image_file) + "\t" + str(
+            json.dumps(np.array(dt_boxes).astype(np.int32).tolist())) + "\n"
+        save_results.append(save_pred)
+        logger.info(save_pred)
         logger.info("Predict time of {}: {}".format(image_file, elapse))
         src_im = utility.draw_text_det_res(dt_boxes, image_file)
         img_name_pure = os.path.split(image_file)[-1]
@@ -264,5 +268,8 @@ if __name__ == "__main__":
         cv2.imwrite(img_path, src_im)
         logger.info("The visualized image saved in {}".format(img_path))
 
+    with open(os.path.join(draw_img_save, "det_results.txt"), 'w') as f:
+        f.writelines(save_results)
+        f.close()
     if args.benchmark:
         text_detector.autolog.report()