Update app.py

app.py

@@ -1,33 +1,26 @@
 import gradio as gr
 from fastai.vision.all import *
-
-from pathlib import Path
-import PIL
 import torchvision.transforms as transforms
-
-
+import torch
+from PIL import Image
+import numpy as np
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu") 
 model = torch.jit.load("unet.pth")
-model = model.cpu()
+model = model.to(device)
 model.eval()
 
 def transform_image(image):
-    my_transforms = transforms.Compose([transforms.ToTensor(),
-                                        transforms.Normalize(
-                                            [0.485, 0.456, 0.406],
-                                            [0.229, 0.224, 0.225])])
-    image_aux = image  
+    my_transforms = transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+    ])
     image = transforms.Resize((480,640))(Image.fromarray(image))
-    tensor = my_transforms(image_aux).unsqueeze(0).to(device)
-
+    tensor = my_transforms(image).unsqueeze(0).to(device)
 
-    model.to(device)
     with torch.no_grad():
         outputs = model(tensor)
-
-    outputs = torch.argmax(outputs,1)
-
+    outputs = torch.argmax(outputs, 1)
 
     mask = np.array(outputs.cpu())
     mask[mask==0]=255
@@ -36,10 +29,12 @@ def transform_image(image):
     mask[mask==3]=25
     mask[mask==4]=0
 
-    mask=np.reshape(mask,(480,640))
+    mask = np.reshape(mask, (480, 640))
     return Image.fromarray(mask.astype('uint8'))
 
-
-    
-# Creamos la interfaz y la lanzamos. 
-gr.Interface(fn=transform_image, inputs=gr.inputs.Image(shape=(640, 480)), outputs=gr.outputs.Image(),examples=['color_154.jpg','color_189.jpg']).launch(share=False)
+# Modificando la creación de la interfaz para usar gr.components en lugar de gr.inputs y gr.outputs
+interface = gr.Interface(fn=transform_image, 
+                         inputs=gr.components.Image(shape=(640, 480)), 
+                         outputs=gr.components.Image(),
+                         examples=['color_154.jpg', 'color_189.jpg'])
+interface.launch(share=False)