Update app.py

app.py

@@ -27,24 +27,9 @@ optimizer = optim.Adam(model.parameters(), lr=config.LEARNING_RATE, weight_decay
 
 utils.load_checkpoint("checkpoint.pth[1].tar", model, optimizer, config.LEARNING_RATE)
 
-test_transforms_exp = A.Compose(
-    [
-        A.LongestMaxSize(max_size=config.IMAGE_SIZE),
-        A.PadIfNeeded(
-            min_height=config.IMAGE_SIZE, min_width=config.IMAGE_SIZE
-        ),
-        A.Normalize(mean=[0, 0, 0], std=[1, 1, 1], max_pixel_value=255,),
-        ToTensorV2(),
-    ]
-)
 
 def inference(input_img,show_gradcam="yes", transparency = 0.5, target_layer_number = -1):
 
-    transform = transforms.ToTensor()
-    org_img = input_img
-    input_img = transform(input_img)
-    input_img = input_img
-    input_img = input_img.unsqueeze(0)
     out_fig = utils.plot_single_image(model, input_img, 0.6, 0.5,scaled_anchors)
     return out_fig