resolved device access

yolov5.py

@@ -177,8 +177,7 @@ class DeepFeatureFactorization:
 def dff_nmf(image, target_lyr, n_components):
     mean = [0.485, 0.456, 0.406]  # Mean for RGB channels
     std = [0.229, 0.224, 0.225]   # Standard deviation for RGB channels
-    img, rgb_img_float, input_tensor = image.to(device)
-    img = cv2.resize(img, (640, 640))
+    img = cv2.resize(image, (640, 640))
     rgb_img_float = np.float32(img) / 255.0
     input_tensor = torch.from_numpy(rgb_img_float).permute(2, 0, 1).unsqueeze(0).to(device)