Update app.py

app.py

@@ -2,16 +2,24 @@ import gradio as gr
 import cv2
 import insightface
 from insightface.app import FaceAnalysis
-from insightface.data import get_image as ins_get_image
 
 def predict(image_in_video, image_in_img):
     if image_in_video == None and image_in_img == None:
         raise gr.Error("Please capture an image using the webcam or upload an image.")
-    
     image = image_in_video or image_in_img
-    img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
-    
+    return swapi(image)
+
+app = FaceAnalysis(name='buffalo_l')
+app.prepare(ctx_id=0, det_size=(640, 640))
+swapper = insightface.model_zoo.get_model('/content/drive/MyDrive/inswapper_128.onnx', download='FALSE', download_zip= 'FALSE')
+
+def swapi(imagen):
+    img = cv2.cvtColor(np.array(imagen), cv2.COLOR_RGB2BGR)  # Convert image from RGB to BGR format
     faces = app.get(img)
+
+    if not faces:
+        return img  # If no faces are detected, return the original image
+
     source_face = faces[0]
     bbox = source_face['bbox']
     bbox = [int(b) for b in bbox]
@@ -22,10 +30,6 @@ def predict(image_in_video, image_in_img):
 
     return res[:, :, [2, 1, 0]]  # Convert BGR to RGB for Gradio display
 
-app = FaceAnalysis(name='buffalo_l')
-app.prepare(ctx_id=0, det_size=(640, 640))
-swapper = insightface.model_zoo.get_model('inswapper_128.onnx', download='FALSE', download_zip= 'FALSE')
-
 with gr.Blocks() as blocks:
     gr.Markdown("### Capture Image Using WebCam or Upload") 
 
@@ -53,5 +57,4 @@ with gr.Blocks() as blocks:
     gr.Examples(fn=predict, examples=[], inputs=[image_in_img, image_in_video], outputs=[image_out])
 
 blocks.queue()
-blocks.launch()
-
+blocks.launch()