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

* fix center yaml

* rm init_center param

* fix typo

* improve pred system

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

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)|

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)|

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():

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()

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)