Update app.py

app.py

@@ -12,21 +12,14 @@ label_names = np.load("model/label_names.npy")
 with open("model/img_shape.txt", "r") as f:
     img_h, img_w = map(int, f.read().strip().split())
 
-# Distance threshold (tune based on performance)
 THRESHOLD = 8000
 
 def recognize_face_from_frame(frame):
-    # Convert to grayscale
     img = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    # Resize to training size
     img = cv2.resize(img, (img_w, img_h))
-    # Flatten and normalize
     img_flat = img.flatten()
     img_centered = img_flat - mean_face
-    # Project to eigenface space
     projected = np.dot(img_centered, eigenfaces.T)
-
-    # Compare with stored projections
     dists = euclidean_distances([projected], projections)[0]
     min_dist = np.min(dists)
     min_index = np.argmin(dists)
@@ -37,13 +30,12 @@ def recognize_face_from_frame(frame):
     else:
         return "😕 Unknown face"
 
-# Web UI
 iface = gr.Interface(
     fn=recognize_face_from_frame,
-    inputs=gr.Camera(),
+    inputs=gr.Image(tool="editor", type="numpy"),
     outputs="text",
     title="🔍 EigenFace Recognition",
-    description="Scan your face. If you're in the dataset, the system will recognize you."
+    description="Upload a face image or take a picture with your webcam."
 )
 
 iface.launch()