Add the function of adjusting parameters

app.py

@@ -93,20 +93,32 @@ def visualize(image_path, boxes, rec_res, font_path="resources/fonts/FZYTK.TTF")
  return image_save
 
 
-def inference(img):
+def inference(img, box_thresh, unclip_ratio, text_score):
  img_path = img.name
  img = cv2.imread(img_path)
- dt_boxes, rec_res = text_sys(img)
+ dt_boxes, rec_res = text_sys(img,
+ box_thresh=box_thresh,
+ unclip_ratio=unclip_ratio,
+ text_score=text_score)
  img_save_path = visualize(img_path, dt_boxes, rec_res)
  return img_save_path, rec_res
 
+
 title = 'Rapid🗲OCR Demo (捷智OCR)'
 description = 'Gradio demo for RapidOCR. Github Repo: https://github.com/RapidAI/RapidOCR'
 article = "<p style='text-align: center'> Completely open source, free and support offline deployment of multi-platform and multi-language OCR SDK <a href='https://github.com/RapidAI/RapidOCR'>Github Repo</a></p>"
 css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
 gr.Interface(
  inference,
- inputs=gr.inputs.Image(type='file', label='Input'),
+ inputs=[
+ gr.inputs.Image(type='file', label='Input'),
+ gr.Slider(minimum=0, maximum=1.0, value=0.5,
+ label='box_thresh', step=0.1),
+ gr.Slider(minimum=1.5, maximum=2.0, value=1.6,
+ label='unclip_ratio', step=0.1),
+ gr.Slider(minimum=0, maximum=1.0, value=0.5,
+ label='text_score', step=0.1),
+ ],
  outputs=[
  gr.outputs.Image(type='file', label='Output_image'),
  gr.outputs.Textbox(type='text', label='Output_text')

rapidocr_onnxruntime/rapid_ocr_api.py

@@ -42,7 +42,19 @@ class TextSystem(object):
  config['Cls']['class_name'])
  self.text_cls = TextClassifier(config['Cls'])
 
- def __call__(self, img: np.ndarray):
+ def __call__(self, img: np.ndarray, **kwargs):
+ # 这里更改几个超参数的值
+ if kwargs:
+ # 获得超参数
+ box_thresh = kwargs.get('box_thresh', 0.5)
+ unclip_ratio = kwargs.get('unclip_ratio', 1.6)
+ text_score = kwargs.get('text_score', 0.5)
+
+ # 更新超参数
+ self.text_detector.postprocess_op.box_thresh = box_thresh
+ self.text_detector.postprocess_op.unclip_ratio = unclip_ratio
+ self.text_score = text_score
+
  h, w = img.shape[:2]
  if self.width_height_ratio == -1:
  use_limit_ratio = False

requirements.txt

@@ -1,7 +1,7 @@
 Gradio
 pyclipper>=1.2.0
 Shapely>=1.7.1
-opencv_python==4.5.1.48
+opencv_python>=4.5.1.48
 six>=1.15.0
 numpy>=1.19.5
 Pillow