Update app.py

app.py

@@ -1,14 +1,14 @@
 from glob import glob
 
 import gradio as gr
-from gradio_client import Client
+from gradio_client import Client, handle_file
 
 from utils import make_flatten_background
 
 REPO_ID = "leonelhs/faceshine"
 
 clients = {
-    "GFPGAN": "leonelhs/GFPGAN",
+    "GFPGAN": "leonelhs/realesrgan_x2plus",
     "ZeroScratches": "leonelhs/ZeroScratches",
     "Deoldify": "leonelhs/deoldify",
     "EnhanceLight": "leonelhs/Zero-DCE",
@@ -26,27 +26,23 @@ def load_client(space):
 
 
 def gfpgan_face(image, version, scale):
-    return clients["GFPGAN"].predict(image, version, scale, fn_index=0)[0]
-
+    return clients["GFPGAN"].predict(img=handle_file(image), api_name="/predict")
 
 def zero_scratches(image):
-    return clients["ZeroScratches"].predict(image, api_name="/predict")
-
+    return clients["ZeroScratches"].predict(img=handle_file(image), api_name="/predict")
 
 def colorize_photo(image):
-    return clients["Deoldify"].predict(image, api_name="/predict")
-
+    return clients["Deoldify"].predict(image=handle_file(image), api_name="/predict")
 
 def enhance_light(image):
-    return clients["EnhanceLight"].predict(image, api_name="/predict")
+    return clients["EnhanceLight"].predict(image=handle_file(image), api_name="/predict")
 
 
 def zero_background(image, new_bgr=None):
-    # Fixme: cant find predict function by name
-    # return clients["ZeroBackground"].predict(image, new_bgr, fn_index=0)[1]
-    # return clients["ZeroBackground"].predict(image, fn_index=0)
-    img, mask = clients["ZeroBackground"].predict(image, "U2NET Human Seg", False, fn_index=9)
-    return make_flatten_background(img, mask)
+    img_cut, mask = clients["ZeroBackground"].predict(
+        image=handle_file(image), session="U2NET Human Seg", smoot=False, api_name="/predict")
+    return make_flatten_background(image, img_cut, mask)
+
 
 
 def parse_face(image):
@@ -136,5 +132,5 @@ with gr.Blocks(title="Face Shine") as app:
     with gr.Row():
         gr.HTML(footer)
 
-app.queue()
 app.launch(share=False, debug=True, show_error=True)
+app.queue()