some

main.py

@@ -4,4 +4,41 @@ app = Flask(__name__)
 
 @app.route('/')
 def hello():
-    return {"hei": "you succesfully deployed"}
+    return {"hei": "you succesfully deployed"}
+
+@app.route('/get-npy')
+def get_npy():
+    #     # Get the 'img_url' from the query parameters
+    #     img_url = request.args.get('img_url', '') # Default to empty string if not provided
+        
+    #     if not img_url:
+    #         return jsonify({"error": "No img_url provided"}), 400
+        
+    #     raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")
+    #     # Convert the PIL Image to a NumPy array
+    #     image_array = np.array(raw_image)
+    #     # Since OpenCV expects BGR, convert RGB to BGR
+    #     image = image_array[:, :, ::-1]
+
+    #     if image is None:
+    #         raise ValueError("Image not found or unable to read.")
+        
+    #     predictor.set_image(image)
+    #     image_embedding = predictor.get_image_embedding().cpu().numpy()
+        
+    #     # Convert the embedding array to bytes
+    #     buffer = io.BytesIO()
+    #     np.save(buffer, image_embedding)
+    #     buffer.seek(0)
+        
+    #     # Create a response with the correct MIME type
+    #     return send_file(buffer, mimetype='application/octet-stream', as_attachment=True, download_name='embedding.npy')
+    # except Exception as e:
+    #     # Log the error message if needed
+    #     print(f"Error processing the image: {e}")
+    #     # Return a JSON response with the error message and a 400 Bad Request status
+    #     return jsonify({"error": "Error processing the image", "details": str(e)}), 400
+    return {"hei": "gotnpy"}
+
+if __name__ == '__main__':
+    app.run(debug=True)