Update app.py

app.py

@@ -3,23 +3,16 @@ from transformers import AutoModelForImageClassification, AutoProcessor
 from PIL import Image
 import io
 import fitz  # PyMuPDF
-from flask_cors import CORS, cross_origin
+from flask_cors import CORS
 
 app = Flask(__name__)
-CORS(app)
+CORS(app)  # Allow cross-origin requests
 
-# Add debugging logs to check the model loading process
+# Load model and processor
 model_name = "AsmaaElnagger/Diabetic_RetinoPathy_detection"
+model = AutoModelForImageClassification.from_pretrained(model_name)
+processor = AutoProcessor.from_pretrained(model_name)
 
-try:
-    print("Loading model...")
-    model = AutoModelForImageClassification.from_pretrained(model_name, cache_dir="/mnt/data")  # Specifying the cache dir for Hugging Face Space
-    processor = AutoProcessor.from_pretrained(model_name, cache_dir="/mnt/data")
-    print("Model loaded successfully.")
-except Exception as e:
-    print(f"Error loading model: {e}")
-
-# Function to convert PDF to images
 def pdf_to_images_pymupdf(pdf_data):
     try:
         pdf_document = fitz.open(stream=pdf_data, filetype="pdf")
@@ -35,7 +28,6 @@ def pdf_to_images_pymupdf(pdf_data):
         return None
 
 @app.route('/classify', methods=['POST'])
-@cross_origin()  # Allows cross-origin requests (important for frontend)
 def classify_file():
     if 'file' not in request.files:
         return jsonify({'error': 'No file provided'}), 400
@@ -79,4 +71,4 @@ def classify_file():
         return jsonify({'error': f'An error occurred: {e}'}), 500
 
 if __name__ == '__main__':
-    app.run(port=5001, debug=True)
+    app.run(host="0.0.0.0", port=7860, debug=True)  # Make it accessible from any network interface