add title, description, forward pass

app.py

@@ -87,17 +87,17 @@ model = Generator(3, 1, 3)
 model.load_state_dict(torch.load('model.pth', map_location=torch.device('cpu')))
 model.eval()
 
-transforms_r = [transforms.Resize(int(opt.size), Image.BICUBIC),
-                   transforms.ToTensor()]
-transforms.Compose([transforms.Resize(int(opt.size), Image.BICUBIC), transforms.ToTensor()])
-
 def predict(input_img):
     input_img = Image.open(input_img)
-    ratio = 256.0 / input_img.size[1]
-    input_img = input_img.resize((int(ratio*input_img.size[0]),256), Image.ANTIALIAS)
-    
+    transforms.Compose([transforms.Resize(256, Image.BICUBIC), transforms.ToTensor()])
+    input_img = transform(input_img)
+    input_img = torch.unsqueeze(input_img, 0)
 
-    return input_img
+    with torch.no_grad():
+        drawing = model(input_img)[0].detach()
+    
+    drawing = transforms.ToPILImage()(drawing)
+    return drawing
 
 title="informative-drawings"
 description="Gradio Demo for line drawing generation. "

requirements.txt

@@ -1 +1,2 @@
-torch
+torch
+torchvision