Debug: yolov8 target lyr

yolov8.py

@@ -5,6 +5,8 @@ from PIL import Image
 import torch
 from torchcam.methods import GradCAM
 from torchcam.utils import overlay_mask
+
+# Set random colors for detection bounding boxes
 COLORS = np.random.uniform(0, 255, size=(80, 3))
 
 def parse_detections_yolov8(results):
@@ -45,9 +47,8 @@ def xai_yolov8(image):
     # Convert image to PyTorch tensor for Grad-CAM
     image_tensor = torch.tensor(np.array(image)).permute(2, 0, 1).unsqueeze(0).float() / 255.0
     image_tensor = image_tensor.to('cpu')
-
-    # Initialize Grad-CAM
-    grad_cam = GradCAM(model.model, target_layer='backbone')  # You can change the target_layer if needed
+    print(model.model)  # Output model layers to find the target layer
+    grad_cam = GradCAM(model.model, target_layer='model.model[0]')  
 
     # Perform Grad-CAM
     cam_map = grad_cam(image_tensor)