Update main.py

main.py

@@ -1,38 +1,47 @@
 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)
+  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)
+  # Detect faces in the image
+  faces = detector(gray)
 
-    # Loop through detected faces
-    for face in faces:
-        landmarks = predictor(gray, face)
+  # 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)]
+    # 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)
+    # 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()
+  # Encode the image back to bytes
+  _, buffer = cv2.imencode('.jpg', image)
+  return buffer.tobytes()
 
-iface = gr.Interface(fn=detect_eyes, inputs=gr.inputs.Image(), outputs=gr.outputs.Image())
+# Create a Gradio interface
+iface = gr.Interface(fn=detect_eyes)
+
+# Add an image input to the interface
+iface.add_input("Image", gr.inputs.Image())
+
+# Add an image output to the interface
+iface.add_output("Detected Eyes", gr.outputs.Image())
+
+# Launch the interface
 iface.launch()