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Before Width: | Height: | Size: 53 KiB After Width: | Height: | Size: 53 KiB |
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import requests
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import base64
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from PIL import Image
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url = 'http://192.168.1.21:7860/tagger/v1/interrogate'
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image_path = r'D:\KeCheng\BaiHu\Backup\mote2.png'
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# 反推模型
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model = 'wd14-vit-v2-git' # 'wd14-convnext'
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# 阀值
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threshold = 0.35
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# 确认照片为上传照片
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image = Image.open(image_path)
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# 将图片转换为Base64字符串
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with open(image_path, 'rb') as file:
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image_data = file.read()
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base64_image = base64.b64encode(image_data).decode('utf-8')
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image.close()
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# 构建请求体的JSON数据
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data = {
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"image": base64_image,
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"model": model,
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"threshold": threshold
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}
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# 发送POST请求
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response = requests.post(url, json=data)
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# 检查响应状态码
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if response.status_code == 200:
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json_data = response.json()
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# 处理返回的JSON数据
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caption_dict = json_data['caption']
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sorted_items = sorted(caption_dict.items(), key=lambda x: x[1], reverse=True)
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# output = '\n'.join([f'{k}: {v}, {int(v * 100)}%' for k, v in sorted_items])
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# output = ','.join([f'{k.replace("_"," ")}' for k, v in sorted_items])
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output = ''
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for k, v in sorted_items:
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if v > threshold:
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output = output + "," + k.replace("_", " ")
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output = output[1:]
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print(output)
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else:
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print('Error:', response.status_code)
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print('Response body:', response.text)
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