Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into fix_doc

README.md

@@ -42,7 +42,7 @@ The above pictures are the visualizations of the general ppocr_server model. For
 - Scan the QR code below with your Wechat, you can access to official technical exchange group. Look forward to your participation.
 
 <div align="center">
-<img src="./doc/joinus.PNG"  width = "200" height = "200" />
+<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/joinus.PNG"  width = "200" height = "200" />
 </div>
 
 

README_ch.md

@@ -46,7 +46,7 @@ PaddleOCR同时支持动态图与静态图两种编程范式
 - 微信扫描二维码加入官方交流群，获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。
 
 <div align="center">
-<img src="./doc/joinus.PNG"  width = "200" height = "200" />
+<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/joinus.PNG"  width = "200" height = "200" />
 </div>
 
 ## 快速体验

deploy/cpp_infer/src/ocr_rec.cpp

@@ -76,7 +76,7 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
           float(*std::max_element(&predict_batch[n * predict_shape[2]],
                                   &predict_batch[(n + 1) * predict_shape[2]]));
 
-      if (argmax_idx > 0 && (!(i > 0 && argmax_idx == last_index))) {
+      if (argmax_idx > 0 && (!(n > 0 && argmax_idx == last_index))) {
         score += max_value;
         count += 1;
         str_res.push_back(label_list_[argmax_idx]);

ppocr/data/imaug/make_shrink_map.py

@@ -32,7 +32,6 @@ class MakeShrinkMap(object):
         text_polys, ignore_tags = self.validate_polygons(text_polys,
                                                          ignore_tags, h, w)
         gt = np.zeros((h, w), dtype=np.float32)
-        # gt = np.zeros((1, h, w), dtype=np.float32)
         mask = np.ones((h, w), dtype=np.float32)
         for i in range(len(text_polys)):
             polygon = text_polys[i]

tools/infer/predict_det.py

@@ -39,10 +39,7 @@ class TextDetector(object):
         self.args = args
         self.det_algorithm = args.det_algorithm
         pre_process_list = [{
-            'DetResizeForTest': {
-                'limit_side_len': args.det_limit_side_len,
-                'limit_type': args.det_limit_type
-            }
+            'DetResizeForTest': None
         }, {
             'NormalizeImage': {
                 'std': [0.229, 0.224, 0.225],

tools/infer_det.py

@@ -97,7 +97,7 @@ def main():
             preds = model(images)
             post_result = post_process_class(preds, shape_list)
             boxes = post_result[0]['points']
-            # write resule
+            # write result
             dt_boxes_json = []
             for box in boxes:
                 tmp_json = {"transcription": ""}