Update app.py

app.py

@@ -11,7 +11,7 @@ import matplotlib.pyplot as plt
 
 
 # Load the pre-trained model
-model = torch.load('model.pth', map_location=torch.device('cuda' if torch.cuda.is_available() else 'cpu'))
+model = torch.load('model.pth', map_location=torch.device('cpu'))
 model.eval()
 
 #define the target layer to pull for gradcam 
@@ -37,9 +37,9 @@ def classify_image(inp, transperancy=0.8):
     #image = Image.fromarray((inp * 255).astype(np.uint8))  # Convert NumPy array to PIL Image
     #input_tensor = preprocess(image)
     input_tensor = preprocess(inp)
-    input_batch = input_tensor.unsqueeze(0).to('cuda' if torch.cuda.is_available() else 'cpu')  # Create a batch
+    input_batch = input_tensor.unsqueeze(0).to('cpu')  # Create a batch
     
-    cam = GradCAM(model=model,use_cuda=True, target_layers=target_layers)
+    cam = GradCAM(model=model,use_cuda=False, target_layers=target_layers)
 
     grayscale_cam = cam(input_tensor=input_batch, targets=None)
     grayscale_cam = grayscale_cam[0, :]