Update main.py

main.py

@@ -1,39 +1,38 @@
 import gradio as gr
 import dlib
 import cv2
-import numpy as np
-
+import numpy as np 
 
 # Load the pre-trained face detector and facial landmarks predictor
 detector = dlib.get_frontal_face_detector()
-predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") # You'll need to download this file
+predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")  # You'll need to download this file
 
 # Function to detect eyes in the image
 def detect_eyes(image):
-  image = cv2.imdecode(np.frombuffer(image.read(), np.uint8), -1)
-  gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-
-  # Detect faces in the image
-  faces = detector(gray)
-
-  # Loop through detected faces
-  for face in faces:
-    landmarks = predictor(gray, face)
-
-    # Define regions of interest for left and right eyes
-    left_eye_region = [(36, 37, 38, 39, 40, 41)]
-    right_eye_region = [(42, 43, 44, 45, 46, 47)]
-
-    # Draw rectangles around eyes
-    for region in left_eye_region + right_eye_region:
-      for i in region:
-        x = landmarks.part(i).x
-        y = landmarks.part(i).y
-        cv2.circle(image, (x, y), 2, (0, 255, 0), -1)
-
-  # Encode the image back to bytes
-  _, buffer = cv2.imencode('.jpg', image)
-  return buffer.tobytes()
+    image = cv2.imdecode(np.frombuffer(image.read(), np.uint8), -1)
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Detect faces in the image
+    faces = detector(gray)
+
+    # Loop through detected faces
+    for face in faces:
+        landmarks = predictor(gray, face)
+
+        # Define regions of interest for left and right eyes
+        left_eye_region = [(36, 37, 38, 39, 40, 41)]
+        right_eye_region = [(42, 43, 44, 45, 46, 47)]
+
+        # Draw rectangles around eyes
+        for region in left_eye_region + right_eye_region:
+            for i in region:
+                x = landmarks.part(i).x
+                y = landmarks.part(i).y
+                cv2.circle(image, (x, y), 2, (0, 255, 0), -1)
+
+    # Encode the image back to bytes
+    _, buffer = cv2.imencode('.jpg', image)
+    return buffer.tobytes()
 
 # Create a Gradio interface
 iface = gr.Interface(fn=detect_eyes)