init

Dockerfile

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+FROM python:3.12-slim
+
+WORKDIR /app
+
+RUN pip install --no-cache-dir flask
+
+COPY libwcocr.so wcocr.cpython-312-x86_64-linux-gnu.so ./
+COPY wx ./wx
+COPY main.py .
+
+CMD ["python", "main.py"]

README.MD

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+# WeChat OCR API Docker
+
+A Dockerized REST API service for text recognition using WeChat's OCR engine.
+
+## Overview
+
+This project wraps the WeChat OCR functionality from the excellent [wechat-ocr](https://github.com/swigger/wechat-ocr) project into a simple REST API service that can be easily deployed using Docker. It allows you to perform optical character recognition on images by leveraging WeChat's powerful OCR capabilities.
+
+## Acknowledgements
+
+This project would not be possible without the work of [swigger](https://github.com/swigger) and their [wechat-ocr](https://github.com/swigger/wechat-ocr) project. Their efforts in reverse-engineering and creating a usable interface for WeChat's OCR functionality form the foundation of this service.
+
+## Quick Start
+
+### Using Docker
+
+```bash
+# Pull the image
+docker pull golangboyme/wxocr
+
+# Run the container
+docker run -d -p 5000:5000 --name wechat-ocr-api golangboyme/wxocr
+```
+
+### API Usage
+
+Send a POST request to `/ocr` with a JSON payload containing your base64-encoded image:
+
+```bash
+curl -X POST http://localhost:5000/ocr \
+  -H "Content-Type: application/json" \
+  -d '{"image": "BASE64_ENCODED_IMAGE_DATA"}'
+```
+
+#### Example Response
+
+```json
+{
+  "errcode": 0,
+  "height": 72,
+  "width": 410,
+  "imgpath": "temp/5726fe7b-25d6-43a6-a50d-35b5f668fbb6.png",
+  "ocr_response": [
+    {
+      "text": "aacss",
+      "left": 80.63632202148438,
+      "top": 29.634929656982422,
+      "right": 236.47093200683594,
+      "bottom": 55.28932189941406,
+      "rate": 0.9997046589851379
+    },
+    {
+      "text": "xxzsa",
+      "left": 312.625,
+      "top": 30.75,
+      "right": 395.265625,
+      "bottom": 55.09375,
+      "rate": 0.997739315032959
+    }
+  ]
+}
+```
+
+### Python Client Example
+
+Here's a simple Python client to use the OCR API:
+
+```python
+import requests
+import base64
+import os
+
+def ocr_recognize(image_path=None, image_url=None, api_url="http://localhost:5000/ocr"):
+    """
+    Send an image to the OCR API service and get the recognition results.
+    Use either image_path or image_url (one is required).
+    """
+    # Get image data
+    if image_path:
+        if not os.path.exists(image_path):
+            print(f"Error: Local image not found: {image_path}")
+            return
+        with open(image_path, "rb") as image_file:
+            img_data = image_file.read()
+    elif image_url:
+        try:
+            response = requests.get(image_url)
+            response.raise_for_status()
+            img_data = response.content
+        except Exception as e:
+            print(f"Failed to download image: {str(e)}")
+            return
+    else:
+        print("Please provide either image_path or image_url")
+        return
+
+    # Convert image to base64
+    base64_image = base64.b64encode(img_data).decode('utf-8')
+    
+    # Send request to API
+    try:
+        response = requests.post(api_url, json={"image": base64_image})
+        response.raise_for_status()
+        return response.json()
+    except Exception as e:
+        print(f"API request failed: {str(e)}")
+        return None
+
+# Example usage
+if __name__ == "__main__":
+    # Local image example
+    result = ocr_recognize(image_path="ocrtest.png")
+    if result:
+        print(result)
+    
+    # URL image example (uncomment to use)
+    # result = ocr_recognize(image_url="https://example.com/image.png")
+```
+
+## Project Structure
+
+- `main.py`: The Flask API service that handles OCR requests
+- `opt/wechat/wxocr`: WeChat OCR binary
+- `opt/wechat/`: WeChat runtime dependencies
+
+## Technical Details
+
+This service uses a Flask application to provide a REST API interface to the WeChat OCR functionality. When an image is submitted:
+
+1. The base64-encoded image is decoded
+2. A temporary file is created
+3. The image is processed by the WeChat OCR engine via the wcocr Python binding
+4. Results are returned in JSON format
+5. Temporary files are cleaned up
+
+## Limitations
+
+- Currently only supports PNG images (can be extended if needed)
+- Depends on WeChat's OCR binaries which may be updated by WeChat
+
+## License
+
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+## Contributing
+
+Contributions are welcome! Please feel free to submit a Pull Request.

main.py

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+import wcocr
+import os
+import uuid
+import base64
+from flask import Flask, request, jsonify
+
+app = Flask(__name__)
+wcocr.init("/app/wx/opt/wechat/wxocr", "/app/wx/opt/wechat")
+
+@app.route('/ocr', methods=['POST'])
+def ocr():
+    try:
+        # Get base64 image from request
+        image_data = request.json.get('image')
+        if not image_data:
+            return jsonify({'error': 'No image data provided'}), 400
+
+        # Create temp directory if not exists
+        temp_dir = 'temp'
+        if not os.path.exists(temp_dir):
+            os.makedirs(temp_dir)
+
+        # Generate unique filename and save image
+        filename = os.path.join(temp_dir, f"{str(uuid.uuid4())}.png")
+        try:
+            image_bytes = base64.b64decode(image_data)
+            with open(filename, 'wb') as f:
+                f.write(image_bytes)
+
+            # Process image with OCR
+            result = wcocr.ocr(filename)
+            return jsonify({'result': result})
+
+        finally:
+            # Clean up temp file
+            if os.path.exists(filename):
+                os.remove(filename)
+
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=5000, threaded=True)