147 lines
4.1 KiB
Python
147 lines
4.1 KiB
Python
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"""
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OCR服务示例实现
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这是一个简单的OCR HTTP服务示例，使用 PaddleOCR 或 Tesseract 作为后端
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你可以根据实际需求修改此文件或使用其他OCR服务
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启动方式: python ocr_server_example.py
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服务地址: http://localhost:8000
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"""
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import base64
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import io
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from typing import List
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try:
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from flask import Flask, request, jsonify
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except ImportError:
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print("请先安装Flask: pip install flask")
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raise
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try:
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from PIL import Image
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except ImportError:
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print("请先安装Pillow: pip install pillow")
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raise
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app = Flask(__name__)
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# 尝试导入OCR引擎，按优先级：PaddleOCR > Tesseract > 模拟
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ocr_engine = None
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ocr_type = None
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try:
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from paddleocr import PaddleOCR
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ocr_engine = PaddleOCR(
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use_angle_cls=True,
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lang='ch',
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show_log=False
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)
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ocr_type = "paddle"
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print("使用 PaddleOCR 引擎")
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except ImportError:
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try:
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import pytesseract
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ocr_engine = pytesseract
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ocr_type = "tesseract"
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print("使用 Tesseract OCR 引擎")
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except ImportError:
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ocr_type = "mock"
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print("警告: 未找到OCR引擎，使用模拟模式")
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print("建议安装 PaddleOCR: pip install paddleocr")
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print("或安装 Tesseract + pytesseract: pip install pytesseract")
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def recognize_with_paddle(image: Image.Image) -> List[str]:
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"""使用PaddleOCR识别"""
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import numpy as np
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img_array = np.array(image)
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result = ocr_engine.ocr(img_array, cls=True)
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texts = []
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if result and result[0]:
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for line in result[0]:
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if line:
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text = line[1][0] # 提取文字内容
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confidence = line[1][1] # 置信度
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if confidence > 0.5: # 过滤低置信度结果
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texts.append(text)
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return texts
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def recognize_with_tesseract(image: Image.Image) -> List[str]:
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"""使用Tesseract识别"""
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text = ocr_engine.image_to_string(image, lang='chi_sim+eng')
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# 按行分割
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lines = [line.strip() for line in text.split('\n') if line.strip()]
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return lines
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def recognize_mock(image: Image.Image) -> List[str]:
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"""模拟OCR（用于测试）"""
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return ["[模拟OCR] 请安装实际的OCR引擎"]
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def recognize_image(image: Image.Image) -> List[str]:
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"""根据配置的引擎进行识别"""
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if ocr_type == "paddle":
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return recognize_with_paddle(image)
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elif ocr_type == "tesseract":
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return recognize_with_tesseract(image)
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else:
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return recognize_mock(image)
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@app.route('/ocr', methods=['POST'])
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def ocr_endpoint():
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"""
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OCR API端点
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接收JSON: {"image": "base64编码的图片"}
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返回JSON: {"texts": ["识别到的文字1", "识别到的文字2", ...]}
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"""
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try:
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data = request.get_json()
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if not data or 'image' not in data:
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return jsonify({"error": "缺少image字段"}), 400
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# 解码base64图片
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img_base64 = data['image']
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img_data = base64.b64decode(img_base64)
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image = Image.open(io.BytesIO(img_data))
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# 转换为RGB（如果是RGBA或其他模式）
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if image.mode != 'RGB':
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image = image.convert('RGB')
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# 执行OCR
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texts = recognize_image(image)
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return jsonify({
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"texts": texts,
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"count": len(texts),
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"engine": ocr_type
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})
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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@app.route('/health', methods=['GET'])
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def health_check():
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"""健康检查端点"""
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return jsonify({
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"status": "ok",
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"engine": ocr_type
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})
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if __name__ == '__main__':
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print("=" * 60)
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print("OCR HTTP 服务")
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print("=" * 60)
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print(f"OCR引擎: {ocr_type}")
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print("API地址: http://localhost:8000/ocr")
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print("健康检查: http://localhost:8000/health")
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print("=" * 60)
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print("\n启动服务中...")
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app.run(host='0.0.0.0', port=8000, debug=False)
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