improve system prediction and remove some hard code (PaddlePaddle#4643)

* fix center yaml * rm init_center param * fix typo * improve pred system
Liyulingyue · Nov 17, 2021 · 7dccfe5 · 7dccfe5
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diff --git a/configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec_enhanced_ctc_loss.yml b/configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec_enhanced_ctc_loss.yml
@@ -62,8 +62,7 @@ Loss:
       weight: 0.05
       num_classes: 6625
       feat_dim: 96
-      init_center: false
-      center_file_path: "./train_center.pkl"
+      center_file_path:
   # you can also try to add ace loss on your own dataset
   # - ACELoss:
   #     weight: 0.1

diff --git a/doc/doc_ch/models_list.md b/doc/doc_ch/models_list.md
@@ -33,8 +33,8 @@ PaddleOCR提供的可下载模型包括`推理模型`、`训练模型`、`预训
 
 |模型名称|模型简介|配置文件|推理模型大小|下载地址|
 | --- | --- | --- | --- | --- |
-|ch_PP-OCRv2_det_slim|【最新】slim量化+蒸馏版超轻量模型，支持中英文、多语种文本检测|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCR_det_cml.yml)| 3M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_slim_quant_infer.tar)|
-|ch_PP-OCRv2_det|【最新】原始超轻量模型，支持中英文、多语种文本检测|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCR_det_cml.yml)|3M|[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar)|
+|ch_PP-OCRv2_det_slim|【最新】slim量化+蒸馏版超轻量模型，支持中英文、多语种文本检测|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml)| 3M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_slim_quant_infer.tar)|
+|ch_PP-OCRv2_det|【最新】原始超轻量模型，支持中英文、多语种文本检测|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml)|3M|[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar)|
 |ch_ppocr_mobile_slim_v2.0_det|slim裁剪版超轻量模型，支持中英文、多语种文本检测|[ch_det_mv3_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml)| 2.6M |[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_infer.tar)|
 |ch_ppocr_mobile_v2.0_det|原始超轻量模型，支持中英文、多语种文本检测|[ch_det_mv3_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml)|3M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|
 |ch_ppocr_server_v2.0_det|通用模型，支持中英文、多语种文本检测，比超轻量模型更大，但效果更好|[ch_det_res18_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml)|47M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar)|

diff --git a/doc/doc_en/models_list_en.md b/doc/doc_en/models_list_en.md
@@ -29,8 +29,8 @@ Relationship of the above models is as follows.
 
 |model name|description|config|model size|download|
 | --- | --- | --- | --- | --- |
-|ch_PP-OCRv2_det_slim|[New] slim quantization with distillation lightweight model, supporting Chinese, English, multilingual text detection|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCR_det_cml.yml)| 3M |[inference model](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_slim_quant_infer.tar)|
-|ch_PP-OCRv2_det|[New] Original lightweight model, supporting Chinese, English, multilingual text detection|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCR_det_cml.yml)|3M|[inference model](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar)|
+|ch_PP-OCRv2_det_slim|[New] slim quantization with distillation lightweight model, supporting Chinese, English, multilingual text detection|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml)| 3M |[inference model](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_slim_quant_infer.tar)|
+|ch_PP-OCRv2_det|[New] Original lightweight model, supporting Chinese, English, multilingual text detection|[ch_PP-OCRv2_det_cml.yml](../../configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml)|3M|[inference model](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar)|
 |ch_ppocr_mobile_slim_v2.0_det|Slim pruned lightweight model, supporting Chinese, English, multilingual text detection|[ch_det_mv3_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml)|2.6M |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_infer.tar)|
 |ch_ppocr_mobile_v2.0_det|Original lightweight model, supporting Chinese, English, multilingual text detection|[ch_det_mv3_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml)|3M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|
 |ch_ppocr_server_v2.0_det|General model, which is larger than the lightweight model, but achieved better performance|[ch_det_res18_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml)|47M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar)|

diff --git a/ppocr/losses/center_loss.py b/ppocr/losses/center_loss.py
@@ -30,21 +30,17 @@ class CenterLoss(nn.Layer):
     Reference: Wen et al. A Discriminative Feature Learning Approach for Deep Face Recognition. ECCV 2016.
     """
 
-    def __init__(self,
-                 num_classes=6625,
-                 feat_dim=96,
-                 init_center=False,
-                 center_file_path=None):
+    def __init__(self, num_classes=6625, feat_dim=96, center_file_path=None):
         super().__init__()
         self.num_classes = num_classes
         self.feat_dim = feat_dim
         self.centers = paddle.randn(
             shape=[self.num_classes, self.feat_dim]).astype("float64")
 
-        if init_center:
+        if center_file_path is not None:
             assert os.path.exists(
                 center_file_path
-            ), f"center path({center_file_path}) must exist when init_center is set as True."
+            ), f"center path({center_file_path}) must exist when it is not None."
             with open(center_file_path, 'rb') as f:
                 char_dict = pickle.load(f)
                 for key in char_dict.keys():

diff --git a/tools/infer/predict_system.py b/tools/infer/predict_system.py
@@ -49,11 +49,19 @@ def __init__(self, args):
         if self.use_angle_cls:
             self.text_classifier = predict_cls.TextClassifier(args)
 
-    def print_draw_crop_rec_res(self, img_crop_list, rec_res):
+        self.args = args
+        self.crop_image_res_index = 0
+
+    def draw_crop_rec_res(self, output_dir, img_crop_list, rec_res):
+        os.makedirs(output_dir, exist_ok=True)
         bbox_num = len(img_crop_list)
         for bno in range(bbox_num):
-            cv2.imwrite("./output/img_crop_%d.jpg" % bno, img_crop_list[bno])
-            logger.info(bno, rec_res[bno])
+            cv2.imwrite(
+                os.path.join(output_dir,
+                             f"mg_crop_{bno+self.crop_image_res_index}.jpg"),
+                img_crop_list[bno])
+            logger.debug(f"{bno}, {rec_res[bno]}")
+        self.crop_image_res_index += bbox_num
 
     def __call__(self, img, cls=True):
         ori_im = img.copy()
@@ -80,7 +88,9 @@ def __call__(self, img, cls=True):
         rec_res, elapse = self.text_recognizer(img_crop_list)
         logger.debug("rec_res num  : {}, elapse : {}".format(
             len(rec_res), elapse))
-        # self.print_draw_crop_rec_res(img_crop_list, rec_res)
+        if self.args.save_crop_res:
+            self.draw_crop_rec_res(self.args.crop_res_save_dir, img_crop_list,
+                                   rec_res)
         filter_boxes, filter_rec_res = [], []
         for box, rec_reuslt in zip(dt_boxes, rec_res):
             text, score = rec_reuslt
@@ -135,17 +145,17 @@ def main(args):
         if not flag:
             img = cv2.imread(image_file)
         if img is None:
-            logger.info("error in loading image:{}".format(image_file))
+            logger.debug("error in loading image:{}".format(image_file))
             continue
         starttime = time.time()
         dt_boxes, rec_res = text_sys(img)
         elapse = time.time() - starttime
         total_time += elapse
 
-        logger.info(
+        logger.debug(
             str(idx) + "  Predict time of %s: %.3fs" % (image_file, elapse))
         for text, score in rec_res:
-            logger.info("{}, {:.3f}".format(text, score))
+            logger.debug("{}, {:.3f}".format(text, score))
 
         if is_visualize:
             image = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
@@ -160,19 +170,17 @@ def main(args):
                 scores,
                 drop_score=drop_score,
                 font_path=font_path)
-            draw_img_save = "./inference_results/"
-            if not os.path.exists(draw_img_save):
-                os.makedirs(draw_img_save)
+            draw_img_save_dir = args.draw_img_save_dir
+            os.makedirs(draw_img_save_dir, exist_ok=True)
             if flag:
                 image_file = image_file[:-3] + "png"
             cv2.imwrite(
-                os.path.join(draw_img_save, os.path.basename(image_file)),
+                os.path.join(draw_img_save_dir, os.path.basename(image_file)),
                 draw_img[:, :, ::-1])
-            logger.info("The visualized image saved in {}".format(
-                os.path.join(draw_img_save, os.path.basename(image_file))))
+            logger.debug("The visualized image saved in {}".format(
+                os.path.join(draw_img_save_dir, os.path.basename(image_file))))
 
     logger.info("The predict total time is {}".format(time.time() - _st))
-    logger.info("\nThe predict total time is {}".format(total_time))
     if args.benchmark:
         text_sys.text_detector.autolog.report()
         text_sys.text_recognizer.autolog.report()

diff --git a/tools/infer/utility.py b/tools/infer/utility.py
@@ -110,7 +110,13 @@ def init_args():
     parser.add_argument("--enable_mkldnn", type=str2bool, default=False)
     parser.add_argument("--cpu_threads", type=int, default=10)
     parser.add_argument("--use_pdserving", type=str2bool, default=False)
-    parser.add_argument("--warmup", type=str2bool, default=True)
+    parser.add_argument("--warmup", type=str2bool, default=False)
+
+    #
+    parser.add_argument(
+        "--draw_img_save_dir", type=str, default="./inference_results")
+    parser.add_argument("--save_crop_res", type=str2bool, default=False)
+    parser.add_argument("--crop_res_save_dir", type=str, default="./output")
 
     # multi-process
     parser.add_argument("--use_mp", type=str2bool, default=False)