Merge pull request #1113 from LDOUBLEV/fixocr

TestReader.infer_img to Global.infer_img

configs/det/det_db_icdar15_reader.yml

@@ -15,7 +15,6 @@ EvalReader:
 TestReader:
   reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
   process_function: ppocr.data.det.db_process,DBProcessTest
-  infer_img:
   img_set_dir: ./train_data/icdar2015/text_localization/
   label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
   do_eval: True

configs/det/det_east_icdar15_reader.yml

@@ -17,7 +17,6 @@ EvalReader:
 TestReader:
   reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
   process_function: ppocr.data.det.east_process,EASTProcessTest
-  infer_img:
   img_set_dir: ./train_data/icdar2015/text_localization/
   label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
   do_eval: True

configs/det/det_mv3_db.yml

@@ -16,6 +16,7 @@ Global:
   checkpoints:
   save_res_path: ./output/det_db/predicts_db.txt
   save_inference_dir:
+  infer_img:
   
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_mv3_db_v1.1.yml

@@ -16,6 +16,7 @@ Global:
   checkpoints:
   save_res_path: ./output/det_db/predicts_db.txt
   save_inference_dir:
+  infer_img:
   
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_mv3_east.yml

@@ -15,6 +15,7 @@ Global:
   checkpoints:
   save_res_path: ./output/det_east/predicts_east.txt
   save_inference_dir:
+  infer_img:
   
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_r18_vd_db_v1.1.yml

@@ -15,6 +15,7 @@ Global:
   save_res_path: ./output/det_r18_vd_db/predicts_db.txt
   checkpoints:
   save_inference_dir:
+  infer_img:
 
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_r50_vd_db.yml

@@ -15,6 +15,7 @@ Global:
   save_res_path: ./output/det_db/predicts_db.txt
   checkpoints:
   save_inference_dir:
+  infer_img:
 
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_r50_vd_east.yml

@@ -15,6 +15,7 @@ Global:
   save_res_path: ./output/det_east/predicts_east.txt
   checkpoints:
   save_inference_dir:
+  infer_img:
 
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_r50_vd_sast_icdar15.yml

@@ -15,6 +15,7 @@ Global:
   save_res_path: ./output/det_sast/predicts_sast.txt
   checkpoints: 
   save_inference_dir:
+  infer_img:
 
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_r50_vd_sast_totaltext.yml

@@ -15,6 +15,7 @@ Global:
   save_res_path: ./output/det_sast/predicts_sast.txt
   checkpoints:
   save_inference_dir:
+  infer_img:
 
 Architecture:
   function: ppocr.modeling.architectures.det_model,DetModel

configs/det/det_sast_icdar15_reader.yml

@@ -20,5 +20,4 @@ EvalReader:
 TestReader:
   reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
   process_function: ppocr.data.det.sast_process,SASTProcessTest
-  infer_img: ./train_data/icdar2015/text_localization/ch4_test_images/img_11.jpg
   max_side_len: 1536

configs/det/det_sast_totaltext_reader.yml

@@ -20,5 +20,4 @@ EvalReader:
 TestReader:
   reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
   process_function: ppocr.data.det.sast_process,SASTProcessTest
-  infer_img: ./train_data/afs/total_text/Images/Test/img623.jpg
   max_side_len: 768

doc/doc_ch/detection.md

@@ -17,7 +17,7 @@ wget -P ./train_data/  https://paddleocr.bj.bcebos.com/dataset/test_icdar2015_la
 PaddleOCR 也提供了数据格式转换脚本，可以将官网 label 转换支持的数据格式。 数据转换工具在 `train_data/gen_label.py`, 这里以训练集为例：
 
 ```
-# 将官网下载的标签文件转换为 train_icdar2015_label.txt 
+# 将官网下载的标签文件转换为 train_icdar2015_label.txt
 python gen_label.py --mode="det" --root_path="icdar_c4_train_imgs/"  \
                     --input_path="ch4_training_localization_transcription_gt" \
                     --output_label="train_icdar2015_label.txt"
@@ -74,7 +74,7 @@ tar -xf ./pretrain_models/MobileNetV3_large_x0_5_pretrained.tar ./pretrain_model
 
 ```shell
 # 训练 mv3_db 模型，并将训练日志保存为 tain_det.log
-python3 tools/train.py -c configs/det/det_mv3_db_v1.1.yml \ 
+python3 tools/train.py -c configs/det/det_mv3_db_v1.1.yml \
      -o Global.pretrain_weights=./pretrain_models/MobileNetV3_large_x0_5_pretrained/ \
      2>&1 | tee train_det.log
 ```
@@ -119,16 +119,16 @@ python3 tools/eval.py -c configs/det/det_mv3_db_v1.1.yml  -o Global.checkpoints=
 
 测试单张图像的检测效果
 ```shell
-python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o TestReader.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy"
+python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o Global.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy"
 ```
 
 测试DB模型时，调整后处理阈值，
 ```shell
-python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o TestReader.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy" PostProcess.box_thresh=0.6 PostProcess.unclip_ratio=1.5
+python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o Global.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy" PostProcess.box_thresh=0.6 PostProcess.unclip_ratio=1.5
 ```
 
 
 测试文件夹下所有图像的检测效果
 ```shell
-python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o TestReader.infer_img="./doc/imgs_en/" Global.checkpoints="./output/det_db/best_accuracy"
+python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o Global.infer_img="./doc/imgs_en/" Global.checkpoints="./output/det_db/best_accuracy"
 ```

doc/doc_en/detection_en.md

@@ -27,7 +27,7 @@ The provided annotation file format is as follow, seperated by "\t":
 " Image file name             Image annotation information encoded by json.dumps"
 ch4_test_images/img_61.jpg    [{"transcription": "MASA", "points": [[310, 104], [416, 141], [418, 216], [312, 179]]}, {...}]
 ```
-The image annotation after **json.dumps()** encoding is a list containing multiple dictionaries. 
+The image annotation after **json.dumps()** encoding is a list containing multiple dictionaries.
 
 The `points` in the dictionary represent the coordinates (x, y) of the four points of the text box, arranged clockwise from the point at the upper left corner.
 
@@ -110,16 +110,16 @@ python3 tools/eval.py -c configs/det/det_mv3_db_v1.1.yml  -o Global.checkpoints=
 
 Test the detection result on a single image:
 ```shell
-python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o TestReader.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy"
+python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o Global.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy"
 ```
 
 When testing the DB model, adjust the post-processing threshold:
 ```shell
-python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o TestReader.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy" PostProcess.box_thresh=0.6 PostProcess.unclip_ratio=1.5
+python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o Global.infer_img="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy" PostProcess.box_thresh=0.6 PostProcess.unclip_ratio=1.5
 ```
 
 
 Test the detection result on all images in the folder:
 ```shell
-python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o TestReader.infer_img="./doc/imgs_en/" Global.checkpoints="./output/det_db/best_accuracy"
+python3 tools/infer_det.py -c configs/det/det_mv3_db_v1.1.yml -o Global.infer_img="./doc/imgs_en/" Global.checkpoints="./output/det_db/best_accuracy"
 ```

doc/doc_en/recognition_en.md

@@ -294,7 +294,7 @@ The default prediction picture is stored in `infer_img`, and the weight is speci
 
 ```
 # Predict English results
-python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v1.1/rec_chinese_lite_train_v1.1.yml -o Global.checkpoints={path/to/weights}/best_accuracy TestReader.infer_img=doc/imgs_words/en/word_1.jpg
+python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v1.1/rec_chinese_lite_train_v1.1.yml -o Global.checkpoints={path/to/weights}/best_accuracy Global.infer_img=doc/imgs_words/en/word_1.jpg
 ```
 
 Input image:
@@ -313,7 +313,7 @@ The configuration file used for prediction must be consistent with the training.
 
 ```
 # Predict Chinese results
-python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v1.1/rec_chinese_lite_train_v1.1.yml -o Global.checkpoints={path/to/weights}/best_accuracy TestReader.infer_img=doc/imgs_words/ch/word_1.jpg
+python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v1.1/rec_chinese_lite_train_v1.1.yml -o Global.checkpoints={path/to/weights}/best_accuracy Global.infer_img=doc/imgs_words/ch/word_1.jpg
 ```
 
 Input image:

tools/infer_det.py

@@ -104,8 +104,8 @@ def main():
     save_res_path = config['Global']['save_res_path']
     if not os.path.exists(os.path.dirname(save_res_path)):
         os.makedirs(os.path.dirname(save_res_path))
-    with open(save_res_path, "wb") as fout:
 
+    with open(save_res_path, "wb") as fout:
         test_reader = reader_main(config=config, mode='test')
         tackling_num = 0
         for data in test_reader():
@@ -135,9 +135,15 @@ def main():
             elif config['Global']['algorithm'] == 'DB':
                 dic = {'maps': outs[0]}
             elif config['Global']['algorithm'] == 'SAST':
-                dic = {'f_score': outs[0], 'f_border': outs[1], 'f_tvo': outs[2], 'f_tco': outs[3]}
+                dic = {
+                    'f_score': outs[0],
+                    'f_border': outs[1],
+                    'f_tvo': outs[2],
+                    'f_tco': outs[3]
+                }
             else:
-                raise Exception("only support algorithm: ['EAST', 'DB', 'SAST']")
+                raise Exception(
+                    "only support algorithm: ['EAST', 'DB', 'SAST']")
             dt_boxes_list = postprocess(dic, ratio_list)
             for ino in range(img_num):
                 dt_boxes = dt_boxes_list[ino]
@@ -151,7 +157,7 @@ def main():
                 fout.write(otstr.encode())
                 src_img = cv2.imread(img_name)
                 draw_det_res(dt_boxes, config, src_img, img_name)
-                
+
     logger.info("success!")
 
 

tools/program.py

@@ -121,7 +121,10 @@ def merge_config(config):
                 global_config.keys(), sub_keys[0])
             cur = global_config[sub_keys[0]]
             for idx, sub_key in enumerate(sub_keys[1:]):
-                assert (sub_key in cur)
+                assert (
+                    sub_key in cur
+                ), "key {} not in sub_keys: {}, please check your running command.".format(
+                    sub_key, cur)
                 if idx == len(sub_keys) - 2:
                     cur[sub_key] = value
                 else: