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| from flask import Flask, request, jsonify | |
| from transformers import TrOCRProcessor, VisionEncoderDecoderModel | |
| from PIL import Image | |
| import torch | |
| import io | |
| import os | |
| import requests | |
| # ========================================== | |
| # Initialize Flask App | |
| # ========================================== | |
| app = Flask(__name__) | |
| # ========================================== | |
| # Fix Hugging Face cache directory permission issue | |
| # ========================================== | |
| os.environ["HF_HOME"] = "/app/cache" | |
| os.makedirs("/app/cache", exist_ok=True) | |
| # ========================================== | |
| # Load Model and Processor | |
| # ========================================== | |
| MODEL_NAME = "anuashok/ocr-captcha-v3" | |
| print("🚀 Loading model...") | |
| processor = TrOCRProcessor.from_pretrained(MODEL_NAME, cache_dir="/app/cache") | |
| model = VisionEncoderDecoderModel.from_pretrained(MODEL_NAME, cache_dir="/app/cache") | |
| # Use GPU if available | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| model.to(device) | |
| model.eval() | |
| print("✅ Model loaded successfully on", device) | |
| # ========================================== | |
| # API Endpoint (Root) | |
| # ========================================== | |
| def root(): | |
| """ | |
| POST / -> Send image file | |
| GET /?url=image_url -> Send image URL | |
| Returns: JSON with recognized text | |
| """ | |
| try: | |
| # --------------------------- | |
| # Handle GET with ?url= | |
| # --------------------------- | |
| if request.method == "GET": | |
| image_url = request.args.get("url") | |
| if not image_url: | |
| return jsonify({ | |
| "message": "OCR Captcha API running. Use POST (file) or GET ?url=image_url." | |
| }) | |
| try: | |
| img_data = requests.get(image_url, timeout=10).content | |
| image = Image.open(io.BytesIO(img_data)).convert("RGB") | |
| except Exception as e: | |
| return jsonify({"error": f"Failed to fetch image from URL: {str(e)}"}), 400 | |
| # --------------------------- | |
| # Handle POST with file upload | |
| # --------------------------- | |
| elif request.method == "POST": | |
| if "file" not in request.files: | |
| return jsonify({"error": "No file provided"}), 400 | |
| file = request.files["file"] | |
| image = Image.open(io.BytesIO(file.read())).convert("RGB") | |
| # --------------------------- | |
| # Process Image with Model | |
| # --------------------------- | |
| pixel_values = processor(images=image, return_tensors="pt").pixel_values.to(device) | |
| with torch.no_grad(): | |
| generated_ids = model.generate(pixel_values) | |
| text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
| return jsonify({"text": text}) | |
| except Exception as e: | |
| return jsonify({"error": str(e)}), 500 | |
| # ========================================== | |
| # Run Server | |
| # ========================================== | |
| if __name__ == "__main__": | |
| # Host on 0.0.0.0 so Hugging Face Space can reach it | |
| app.run(host="0.0.0.0", port=7860) |