Fix: figure canvas args

yolov5.py

@@ -1,20 +1,14 @@
 
 import torch
 import cv2
-import os
-import warnings
-warnings.filterwarnings('ignore')
 import numpy as np
 from PIL import Image
 import torchvision.transforms as transforms
 from pytorch_grad_cam import EigenCAM
 from pytorch_grad_cam.utils.image import show_cam_on_image, scale_cam_image
 import gradio as gr
-import yaml
-import requests
-from pytorch_grad_cam import DeepFeatureFactorization
-from pytorch_grad_cam.utils.image import show_cam_on_image, preprocess_image
-from pytorch_grad_cam.utils.image import deprocess_image, show_factorization_on_image
+import os
+# Global Color Palette
 COLORS = np.random.uniform(0, 255, size=(80, 3))
 
 
@@ -88,6 +82,20 @@ def xai_yolov5(image):
     return Image.fromarray(final_image), caption
 
 
+ 
+import yaml
+import torch
+import warnings
+warnings.filterwarnings('ignore')
+from PIL import Image
+import numpy as np
+import requests
+import cv2
+import torch
+from pytorch_grad_cam import DeepFeatureFactorization
+from pytorch_grad_cam.utils.image import show_cam_on_image, preprocess_image
+from pytorch_grad_cam.utils.image import deprocess_image, show_factorization_on_image
+
 # Check if CUDA is available
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 mean = [0.485, 0.456, 0.406]  # Mean for RGB channels