Gradio2

app.py

@@ -3,15 +3,21 @@ import numpy as np
 import gradio as gr
 from glob import glob
 from huggingface_hub import from_pretrained_keras
+import cv2
+
 
 model = from_pretrained_keras('Rietta/CycleGAN_DL', compile=False)
 
+imagen = cv2.imread('Kirby.png', cv2.COLOR_BGR2RGB) 
+
 def transform(img, direction):
     img = (img / 127.5) - 1
     if direction==0:
+        pred = model.generator_wow.predict(img[None,:,:,:])[0]
+    elif direction == 1:
         pred = model.generator_sims.predict(img[None,:,:,:])[0]
     else:
-        pred = model.generator_wow.predict(img[None,:,:,:])[0]
+        pred = imagen
     pred = (pred-pred.min())/(pred.max()-pred.min())
     pred = (pred * 255).astype(np.uint8)
     return pred
@@ -22,7 +28,7 @@ def transform(img, direction):
 
 demo = gr.Interface(fn=transform, 
                     inputs=[gr.inputs.Image(shape=(256, 256), type='numpy'),
-                            gr.inputs.Radio(choices=['Sims', 'Warcraft'],
+                            gr.inputs.Radio(choices=['Sims', 'Warcraft', "Kirby"],
                                             type='index')], 
                     outputs=gr.outputs.Image(type='numpy'))
                     #examples=examples)