Update app.py

app.py

@@ -1,24 +1,35 @@
 from flask import Flask, request, jsonify
+from flask_cors import CORS
 import cv2
 import mediapipe as mp
 import numpy as np
 from PIL import Image
 import base64
 import io
-from flask_cors import CORS
+import traceback
 
+# Initialize Flask
 app = Flask(__name__)
-CORS(app)  # Allow cross-origin requests from Flutter app
+CORS(app)  # Allow cross-origin requests (for Flutter or frontend)
 
-# MediaPipe Pose
-mp_pose = mp.solutions.pose
-pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5)
-mp_drawing = mp.solutions.drawing_utils
+print("✅ Flask app starting...")
 
-# Overlay function
+try:
+    # Initialize MediaPipe Pose
+    mp_pose = mp.solutions.pose
+    pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5)
+    mp_drawing = mp.solutions.drawing_utils
+    print("✅ MediaPipe initialized successfully")
+except Exception as e:
+    print("❌ Error initializing MediaPipe:", e)
+    traceback.print_exc()
+
+# ---------- Helper function ----------
 def overlay_dress(frame, dress, landmarks):
+    """Overlay a dress image on the user's frame based on pose landmarks."""
     if landmarks is not None:
         h, w, _ = frame.shape
+
         def to_pixel(lm):
             return int(lm.x * w), int(lm.y * h)
 
@@ -27,34 +38,37 @@ def overlay_dress(frame, dress, landmarks):
         left_hip = to_pixel(landmarks[mp_pose.PoseLandmark.LEFT_HIP.value])
         right_hip = to_pixel(landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value])
 
-        # Dress size & position
-        dress_width = int(np.linalg.norm(np.array(left_shoulder)-np.array(right_shoulder))*1.8)
+        # Estimate size and position of the dress
+        dress_width = int(np.linalg.norm(np.array(left_shoulder) - np.array(right_shoulder)) * 1.8)
         top_shoulder_y = min(left_shoulder[1], right_shoulder[1])
         bottom_hip_y = max(left_hip[1], right_hip[1])
-        dress_height = int((bottom_hip_y - top_shoulder_y)*1.2)
+        dress_height = int((bottom_hip_y - top_shoulder_y) * 1.2)
 
-        center_x = (left_shoulder[0]+right_shoulder[0])//2
-        x1 = max(center_x - dress_width//2, 0)
+        center_x = (left_shoulder[0] + right_shoulder[0]) // 2
+        x1 = max(center_x - dress_width // 2, 0)
         y1 = max(top_shoulder_y - 30, 0)
         x2 = min(x1 + dress_width, w)
         y2 = min(y1 + dress_height, h)
 
-        # Resize and blend dress
-        dress_resized = cv2.resize(dress, (x2-x1, y2-y1), interpolation=cv2.INTER_AREA)
-        if dress_resized.shape[2] == 4:  # has alpha channel
+        # Resize and overlay
+        dress_resized = cv2.resize(dress, (x2 - x1, y2 - y1), interpolation=cv2.INTER_AREA)
+        if dress_resized.shape[2] == 4:  # if dress has alpha channel
             alpha_s = dress_resized[:, :, 3] / 255.0
             alpha_l = 1.0 - alpha_s
             for c in range(3):
-                frame[y1:y2, x1:x2, c] = alpha_s*dress_resized[:, :, c] + alpha_l*frame[y1:y2, x1:x2, c]
+                frame[y1:y2, x1:x2, c] = (
+                    alpha_s * dress_resized[:, :, c] + alpha_l * frame[y1:y2, x1:x2, c]
+                )
 
     return frame
 
-# Home route for HF Spaces detection
+
+# ---------- Routes ----------
 @app.route("/", methods=["GET"])
 def home():
-    return "<h1>Flask API is running!</h1>"
+    return "<h1>✅ Flask Virtual Try-On API is Running!</h1>"
+
 
-# Virtual try-on API
 @app.route("/tryon", methods=["POST"])
 def tryon():
     try:
@@ -80,7 +94,7 @@ def tryon():
         # Overlay dress
         frame = overlay_dress(frame, dress_img, landmarks)
 
-        # Draw pose landmarks
+        # Draw pose landmarks (optional for debugging)
         if results.pose_landmarks:
             mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
 
@@ -91,7 +105,12 @@ def tryon():
         return jsonify({"image": img_base64})
 
     except Exception as e:
+        print("❌ Error during /tryon:", e)
+        traceback.print_exc()
         return jsonify({"error": str(e)}), 500
 
+
+# ---------- Local Debug Mode ----------
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=5000)
+    # Only for local testing (Gunicorn will handle production)
+    app.run(debug=True, host="0.0.0.0", port=5000)