Update app.py

app.py

@@ -13,6 +13,7 @@ mp_pose = mp.solutions.pose
 pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5)
 mp_drawing = mp.solutions.drawing_utils
 
+# Overlay function
 def overlay_dress(frame, dress, landmarks):
     if landmarks is not None:
         h, w, _ = frame.shape
@@ -39,37 +40,45 @@ def overlay_dress(frame, dress, landmarks):
                 frame[y1:y2,x1:x2,c] = alpha_s*dress_resized[:,:,c] + alpha_l*frame[y1:y2,x1:x2,c]
     return frame
 
+# Simple home route for HF Spaces detection
+@app.route("/")
+def home():
+    return "<h1>Flask API is running!</h1>"
+
+# Virtual try-on API
 @app.route("/tryon", methods=["POST"])
 def tryon():
-    # Expect JSON with keys: 'image' (webcam) and 'dress' (uploaded dress)
-    data = request.json
-    if "image" not in data or "dress" not in data:
-        return jsonify({"error": "Both 'image' and 'dress' are required"}), 400
+    try:
+        data = request.json["image"]       # Base64 string of user webcam
+        dress_data = request.json["dress"] # Base64 string of uploaded dress
+
+        # Decode user image
+        img_bytes = base64.b64decode(data.split(",")[1])
+        img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
+        frame = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
 
-    # Decode webcam image
-    webcam_bytes = base64.b64decode(data["image"].split(",")[1])
-    webcam_img = Image.open(io.BytesIO(webcam_bytes)).convert("RGB")
-    frame = cv2.cvtColor(np.array(webcam_img), cv2.COLOR_RGB2BGR)
+        # Decode dress image
+        dress_bytes = base64.b64decode(dress_data.split(",")[1])
+        dress_img = cv2.imdecode(np.frombuffer(dress_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
 
-    # Decode uploaded dress image
-    dress_bytes = base64.b64decode(data["dress"].split(",")[1])
-    dress_img = cv2.cvtColor(np.array(Image.open(io.BytesIO(dress_bytes)).convert("RGBA")), cv2.COLOR_RGBA2BGRA)
+        # Pose detection
+        results = pose.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+        landmarks = results.pose_landmarks.landmark if results.pose_landmarks else None
 
-    # Pose detection
-    results = pose.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
-    landmarks = results.pose_landmarks.landmark if results.pose_landmarks else None
+        # Overlay dress
+        frame = overlay_dress(frame, dress_img, landmarks)
 
-    # Overlay dress
-    frame = overlay_dress(frame, dress_img, landmarks)
+        # Draw pose landmarks
+        if results.pose_landmarks:
+            mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
 
-    # Draw pose landmarks
-    if results.pose_landmarks:
-        mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
+        # Encode output
+        _, buffer = cv2.imencode(".jpg", frame)
+        img_base64 = "data:image/jpeg;base64," + base64.b64encode(buffer).decode()
 
-    # Encode result
-    _, buffer = cv2.imencode(".jpg", frame)
-    img_base64 = "data:image/jpeg;base64," + base64.b64encode(buffer).decode()
-    return jsonify({"image": img_base64})
+        return jsonify({"image": img_base64})
+    except Exception as e:
+        return jsonify({"error": str(e)})
 
 if __name__=="__main__":
     app.run(host="0.0.0.0", port=5000)