debug: list index out of range

yolov5.py

@@ -90,6 +90,7 @@ def xai_yolov5(image,target_lyr = -5, n_components = 8):
 
     rgb_img_float, batch_explanations, result = dff_nmf(image, target_lyr = -5, n_components = 8)
     #result = np.hstack(result)
+    print("sample...",rgb_img_float.shape,batch_explanations.shape )
     im = visualize_batch_explanations(rgb_img_float, batch_explanations)  ##########to be displayed
     
     # Combine results
@@ -233,14 +234,13 @@ def dff_nmf(image, target_lyr, n_components):
 
         fig.canvas.draw()  # Draw the canvas to make sure the image is rendered
         image_array = np.array(fig.canvas.renderer.buffer_rgba())  # Convert to numpy array
-        print("____________image_arrya", image_array.shape)
         image_resized = cv2.resize(image_array, (640, 640))
         rgba_channels = cv2.split(image_resized)
         alpha_channel = rgba_channels[3] 
         rgb_channels = np.stack(rgba_channels[:3], axis=-1)
-        #overlay_img = (alpha_channel[..., None] * image) + ((1 - alpha_channel[..., None]) * rgb_channels)
+        overlay_img = (alpha_channel[..., None] * image) + ((1 - alpha_channel[..., None]) * rgb_channels)
         print("shape....", rgb_img_float.shape, rgb_channels.shape)
-        visualization = show_factorization_on_image(rgb_img_float, rgb_channels , image_weight=0.3)
+        #visualization = show_factorization_on_image(rgb_img_float, rgb_channels , image_weight=0.3)
         
         #temp = image_array.reshape((rgb_img_float.shape[0],rgb_img_float.shape[1]) )
         #visualization = show_factorization_on_image(rgb_img_float, image_array.resize((rgb_img_float.shape)) , image_weight=0.3)