Update app.py

app.py

@@ -2,72 +2,84 @@ import cv2
 import gradio as gr
 import numpy as np
 from moviepy.editor import *
-
+import logger
+logging.basicConfig(filename='logs/error.log', level=logging.ERROR)
 class FaceSwapper:
     def __init__(self):
+        self.logger = logging.getLogger()
         self.face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
 
     def swap_faces(self, image1, image2, alpha):
-        # Load the input images
-        img1 = cv2.imread(image1.name)
-        img2 = cv2.imread(image2.name)
-
-        # Detect faces in the images
-        faces = self.face_cascade.detectMultiScale(img1)
-        faces1 = self.face_cascade.detectMultiScale(img2)
-
-        if len(faces) > 0:
-            for (x, y, w, h) in faces:
-                # Crop the face region from the first image
-                cropped_face = img1[y:y+h, x:x+w]
-
-                # Calculate dimensions for resizing the face from the second image
-                desired_width = faces1[0][0] + faces1[0][2]
-                desired_height = faces1[0][1] + faces1[0][3]
-
-                # Resize the cropped face to match dimensions
-                resized_cropped_face = cv2.resize(cropped_face, (desired_width, desired_height))
-
-                # Blend the faces using the alpha value
-                blended_face = cv2.addWeighted(resized_cropped_face, alpha, img2[y:y+h, x:x+w], 1-alpha, 0)
-
-                # Position the blended face on the first image
-                x_position = x
-                y_position = y
-                img1[y_position:y_position+desired_height, x_position:x_position+desired_width] = blended_face
-
-            return img1
-        else:
+        try:
+            # Load the input images
+            img1 = cv2.imread(image1.name)
+            img2 = cv2.imread(image2.name)
+    
+            # Detect faces in the images
+            faces = self.face_cascade.detectMultiScale(img1)
+            faces1 = self.face_cascade.detectMultiScale(img2)
+    
+            if len(faces) > 0:
+                for (x, y, w, h) in faces:
+                    # Crop the face region from the first image
+                    cropped_face = img1[y:y+h, x:x+w]
+    
+                    # Calculate dimensions for resizing the face from the second image
+                    desired_width = faces1[0][0] + faces1[0][2]
+                    desired_height = faces1[0][1] + faces1[0][3]
+    
+                    # Resize the cropped face to match dimensions
+                    resized_cropped_face = cv2.resize(cropped_face, (desired_width, desired_height))
+    
+                    # Blend the faces using the alpha value
+                    blended_face = cv2.addWeighted(resized_cropped_face, alpha, img2[y:y+h, x:x+w], 1-alpha, 0)
+    
+                    # Position the blended face on the first image
+                    x_position = x
+                    y_position = y
+                    img1[y_position:y_position+desired_height, x_position:x_position+desired_width] = blended_face
+    
+                return img1
+            else:
+                return None
+                
+        except Exception as e:
+            logger.error(f"An error occurred during face swapping: {e}")
             return None
 
     def generate_morph(self, image1, image2, num_frames, alpha):
-        # Load the input images
-        img1 = cv2.imread(image1.name)
-        img2 = cv2.imread(image2.name)
-
-        # Detect faces in the images
-        faces = self.face_cascade.detectMultiScale(img1)
-        faces1 = self.face_cascade.detectMultiScale(img2)
-
-        if len(faces) > 0:
-            frames = []
-            for i in range(num_frames):
-                alpha_i = alpha + (1-alpha) * i / (num_frames-1)
-                img = self.swap_faces(image1, image2, alpha_i)
-                frames.append(img)
-
-            # Convert the frames to a video
-            fps = 30
-            height, width, _ = frames[0].shape
-            fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-            video = cv2.VideoWriter('output.mp4', fourcc, fps, (width, height))
-
-            for frame in frames:
-                video.write(frame)
-
-            video.release()
-            return 'output.mp4'
-        else:
+        try:
+            # Load the input images
+            img1 = cv2.imread(image1.name)
+            img2 = cv2.imread(image2.name)
+    
+            # Detect faces in the images
+            faces = self.face_cascade.detectMultiScale(img1)
+            faces1 = self.face_cascade.detectMultiScale(img2)
+    
+            if len(faces) > 0:
+                frames = []
+                for i in range(num_frames):
+                    alpha_i = alpha + (1-alpha) * i / (num_frames-1)
+                    img = self.swap_faces(image1, image2, alpha_i)
+                    frames.append(img)
+    
+                # Convert the frames to a video
+                fps = 30
+                height, width, _ = frames[0].shape
+                fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+                video = cv2.VideoWriter('output.mp4', fourcc, fps, (width, height))
+    
+                for frame in frames:
+                    video.write(frame)
+    
+                video.release()
+                return 'output.mp4'
+            else:
+                return None
+                
+        except Exception as e:
+            logger.error(f"An error occurred during morphing: {e}")
             return None
             
 iface = gr.Interface(