fix

gradcam.py

@@ -33,11 +33,11 @@ class GradCam():
     def __init__(self):
         pass
     
-    def category_name_to_index(model, category_name):
+    def category_name_to_index(self, model, category_name):
         name_to_index = dict((v, k) for k, v in model.config.id2label.items())
         return name_to_index[category_name]
         
-    def run_grad_cam_on_image(model: torch.nn.Module,
+    def run_grad_cam_on_image(self, model: torch.nn.Module,
                             target_layer: torch.nn.Module,
                             targets_for_gradcam: List[Callable],
                             reshape_transform: Optional[Callable],
@@ -67,14 +67,14 @@ class GradCam():
             return np.hstack(results)
         
         
-    def print_top_categories(model, img_tensor, top_k=5):
+    def print_top_categories(self, model, img_tensor, top_k=5):
         logits = model(img_tensor.unsqueeze(0)).logits
         probabilities = torch.nn.functional.softmax(logits, dim=1)
         indices = logits.cpu()[0, :].detach().numpy().argsort()[-top_k :][::-1]
         for i in indices:
             print(f"Predicted class (sorted from most confident) {i}: {model.config.id2label[i]}, confidence: {probabilities[0][i].item()}")
 
-    def reshape_transform_vit_huggingface(x):
+    def reshape_transform_vit_huggingface(self, x):
         activations = x[:, 1:, :]
         activations = activations.view(activations.shape[0],
                                     14, 14, activations.shape[2])
@@ -118,7 +118,7 @@ if __name__ == "__main__":
     cv.resizeWindow("DFF Image", 2500, 700)
     # cv.waitKey(0)
     # cv.destroyAllWindows()
-    grad_cam_image = run_grad_cam_on_image(model=model,
+    grad_cam_image = gradCam.run_grad_cam_on_image(model=model,
                                         target_layer=target_layer_gradcam,
                                         targets_for_gradcam=targets_for_gradcam,
                                         input_tensor=tensor_resized,
@@ -130,5 +130,4 @@ if __name__ == "__main__":
     cv.resizeWindow("Grad-CAM Image", 2000, 1250)
     cv.waitKey(0)
     cv.destroyAllWindows()
-    gradCam.print_top_categories(model, tensor_resized)
-
+    gradCam.print_top_categories(model, tensor_resized)