Update app.py

app.py

@@ -1,50 +1,50 @@
-import gradio as gr
-import os
-import cv2
-import torch
-import numpy as np
-from PIL import Image
-from gfpgan import GFPGANer
-
-# Download GFPGAN model if not already present
-model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
-model_path = "GFPGANv1.4.pth"
-
-if not os.path.exists(model_path):
-    import requests
-    r = requests.get(model_url, allow_redirects=True)
-    open(model_path, 'wb').write(r.content)
-
-# Initialize GFPGAN
-restorer = GFPGANer(
-    model_path=model_path,
-    upscale=2,
-    arch='clean',
-    channel_multiplier=2,
-    bg_upsampler=None
-)
-
-def enhance(image):
-    # Convert PIL to numpy
-    img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
-
-    _, _, restored_img = restorer.enhance(
-        img,
-        has_aligned=False,
-        only_center_face=False,
-        paste_back=True
-    )
-
-    restored_pil = Image.fromarray(cv2.cvtColor(restored_img, cv2.COLOR_BGR2RGB))
-    return restored_pil
-
-iface = gr.Interface(
-    fn=enhance,
-    inputs=gr.Image(type="pil"),
-    outputs="image",
-    title="IMGEN - AI Photo Enhancer",
-    description="Upload your photo (ID, CV, profile) and enhance it with AI using GFPGAN."
-)
-
-if __name__ == "__main__":
-    iface.launch()
+import gradio as gr
+import os
+import cv2
+import torch
+import numpy as np
+from PIL import Image
+from gfpgan import GFPGANer
+
+# Download GFPGAN model if not already present
+model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
+model_path = "GFPGANv1.4.pth"
+
+if not os.path.exists(model_path):
+    import requests
+    r = requests.get(model_url, allow_redirects=True)
+    open(model_path, 'wb').write(r.content)
+
+# Initialize GFPGAN
+restorer = GFPGANer(
+    model_path=model_path,
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=None
+)
+
+def enhance(image):
+    # Convert PIL to numpy
+    img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+
+    _, _, restored_img = restorer.enhance(
+        img,
+        has_aligned=False,
+        only_center_face=False,
+        paste_back=True
+    )
+
+    restored_pil = Image.fromarray(cv2.cvtColor(restored_img, cv2.COLOR_BGR2RGB))
+    return restored_pil
+
+iface = gr.Interface(
+    fn=enhance,
+    inputs=gr.Image(type="pil"),
+    outputs="image",
+    title="IMGEN - AI Photo Enhancer",
+    description="Upload your photo (ID, CV, profile) and enhance it with AI using GFPGAN."
+)
+
+if __name__ == "__main__":
+    iface.launch()