Updated GradCAM

app.py

@@ -68,12 +68,7 @@ def inference(input_img, conf_thres, iou_thres, is_false_detection_images=True,
     im0 = input_img.copy()
     im_resized = cv2.resize(im0, (640, 640))
     rgb_img = im_resized.copy()
-    transforms = albumentations.Compose(
-        # Normalize
-        [albumentations.Normalize([0.49139968, 0.48215841, 0.44653091], 
-                                  [0.24703223, 0.24348513, 0.26158784]), 
-        # Convert to tensor                          
-        ToTensorV2()])
+    transforms = albumentations.Compose([ToTensorV2()])
     im_resized = transforms(image = im_resized)['image']
     im_resized = im_resized.unsqueeze(0)
     stride, names, pt = model.stride, model.names, model.pt
@@ -123,9 +118,9 @@ def inference(input_img, conf_thres, iou_thres, is_false_detection_images=True,
         misclassified_images = None
 
     cam = EigenCAM(model, target_layers)
-    grayscale_cam = cam(im_resized)[0, :, :]
+    grayscale_cam = cam(im_resized)[0, :]
     cam_image = show_cam_on_image(rgb_img, grayscale_cam, use_rgb=True)
-
+    
     return im0, cam_image, misclassified_images
 
 title = "YOLOv9 model to detect shirt/tshirt"