demo init

.gitignore

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+__pycache__
+.vscode
+.DS_Store

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;}"
+
+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, share=True)

packages.txt

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+ffmpeg 
+libsm6 
+libxext6

requirements.txt

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+paddleocr