init

app.py

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+from paddleocr import PaddleOCR
+import json
+from PIL import Image
+import gradio as gr
+import numpy as np
+import cv2
+
+
+# 获取随机的颜色
+def get_random_color():
+    c = tuple(np.random.randint(0 ,256 ,3).tolist())
+    return c
+
+
+# 绘制ocr识别结果
+def draw_ocr_bbox( image ,boxes ,colors ):
+    print(colors)
+    box_num = len(boxes)
+    for i in range(box_num):
+        box = np.reshape(np.array(boxes[i]) ,[-1 ,1 ,2]).astype(np.int64)
+        image = cv2.polylines(np.array(image) ,[box] ,True ,colors[i] ,2)
+    return image
+
+
+# torch.hub.download_url_to_file('https://i.imgur.com/aqMBT0i.jpg', 'example.jpg')
+
+def inference( img: Image.Image ,lang ,confidence ):
+    ocr = PaddleOCR(use_angle_cls = True ,lang = lang ,use_gpu = False)
+    # img_path = img.name
+    img2np = np.array(img)
+    result = ocr.ocr(img2np ,cls = True)[0]
+    # rgb
+    image = img.convert('RGB')
+    boxes = [line[0] for line in result]
+    txts = [line[1][0] for line in result]
+    scores = [line[1][1] for line in result]
+
+    # 识别结果
+    final_result = [dict(boxes = box ,txt = txt ,score = score ,_c = get_random_color()) for box ,txt ,score in
+                    zip(boxes ,txts ,scores)]
+    # 过滤 score < 0.5 的
+    final_result = [item for item in final_result if item['score'] > confidence]
+
+    im_show = draw_ocr_bbox(image ,[item['boxes'] for item in final_result] ,[item['_c'] for item in final_result])
+    im_show = Image.fromarray(im_show)
+    data = [[json.dumps(item['boxes']) ,round(item['score'] ,3) ,item['txt']] for item in final_result]
+    return im_show ,data
+
+
+title = 'PaddleOCR'
+description = 'Gradio demo for PaddleOCR.'
+
+examples = [
+    ['example_imgs/example.jpg' ,'en' ,0.5] ,
+    ['example_imgs/ch.jpg' ,'ch' ,0.7] ,
+    ['example_imgs/img_12.jpg' ,'en' ,0.7] ,
+]
+
+css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
+
+if __name__ == '__main__':
+    demo = gr.Interface(
+        inference ,
+        [gr.Image(type = 'pil' ,label = 'Input') ,
+         gr.Dropdown(choices = ['ch' ,'en' ,'fr' ,'german' ,'korean' ,'japan'] ,value = 'ch' ,label = 'language') ,
+         gr.Slider(0.1 ,1 ,0.5 ,step = 0.1 ,label = 'confidence_threshold')
+         ] ,
+        # 输出
+        [gr.Image(type = 'pil' ,label = 'Output') ,
+         gr.Dataframe(headers = ['bbox' ,'score' ,'text'] ,label = 'Result')] ,
+        title = title ,
+        description = description ,
+        examples = examples ,
+        css = css ,
+    )
+    demo.queue(max_size = 10)
+    demo.launch(debug = True ,server_name = "0.0.0.0")

requirements.txt

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+paddlepaddle==2.6.1
+paddleocr==2.7.3