LIME explainer error

nima_pw: <p>Hi,</p>
<p>I want to explain images using LIME:</p>
<pre><code class="lang-auto">path = "image.jpg"
image = torch.stack(transform(Image.open(path))

model = loadmodel()

#  Define the lime explainer
explainer = lime_image.LimeImageExplainer()

# Define a function to get predictions from the model
def predict_function(image):
    # Add necessary preprocessing steps if required
    outputs = model(image)
    return outputs

# Visualize the fourth convolutional layer using LIME
    image = image.unsqueeze(0)
    
    # Convert the image to a numpy array
    image_np = image.squeeze(0).permute(1, 2, 0).cpu().numpy()

    explanation = explainer.explain_instance(image_np, predict_function, top_labels=5, hide_color=0, num_samples=1000)
    temp, mask = explanation.get_image_and_mask(3, positive_only=False, num_features=5, hide_rest=False)
    
    plt.imshow(temp)
    plt.show()
</code></pre>
<p>but I get this error:</p>
<pre><code class="lang-auto">TypeError                                 Traceback (most recent call last)
&lt;ipython-input-48-0ad542da0c28&gt; in &lt;cell line: 20&gt;()
     24     image_np = image.squeeze(0).permute(1, 2, 0).numpy()
     25 
---&gt; 26     explanation = explainer.explain_instance(image_np, predict_function, top_labels=5, hide_color=0, num_samples=1000)
     27     temp, mask = explanation.get_image_and_mask(3, positive_only=False, num_features=5, hide_rest=False)
     28 

9 frames
/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py in _conv_forward(self, input, weight, bias)
    454                             weight, bias, self.stride,
    455                             _pair(0), self.dilation, self.groups)
--&gt; 456         return F.conv2d(input, weight, bias, self.stride,
    457                         self.padding, self.dilation, self.groups)
    458 

TypeError: conv2d() received an invalid combination of arguments - got (numpy.ndarray, Parameter, Parameter, tuple, tuple, tuple, int), but expected one of:
 * (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, tuple of ints padding, tuple of ints dilation, int groups)
      didn't match because some of the arguments have invalid types: (!numpy.ndarray!, !Parameter!, !Parameter!, !tuple of (int, int)!, !tuple of (int, int)!, !tuple of (int, int)!, int)
 * (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, str padding, tuple of ints dilation, int groups)
      didn't match because some of the arguments have invalid types: (!numpy.ndarray!, !Parameter!, !Parameter!, !tuple of (int, int)!, !tuple of (int, int)!, !tuple of (int, int)!, int)
</code></pre>
<p>without converting to numpy:<br>
<code>image_np = image.squeeze(0).permute(1, 2, 0)</code></p>
<p>this error occurs:</p>
<pre><code class="lang-auto">AttributeError                            Traceback (most recent call last)
&lt;ipython-input-49-04ca51ebb1aa&gt; in &lt;cell line: 20&gt;()
     24     image_np = image.squeeze(0).permute(1, 2, 0)
     25 
---&gt; 26     explanation = explainer.explain_instance(image_np, predict_function, top_labels=5, hide_color=0, num_samples=1000)
     27     temp, mask = explanation.get_image_and_mask(3, positive_only=False, num_features=5, hide_rest=False)
     28 

/usr/local/lib/python3.10/dist-packages/lime/lime_image.py in explain_instance(self, image, classifier_fn, labels, hide_color, top_labels, num_features, num_samples, batch_size, segmentation_fn, distance_metric, model_regressor, random_seed)
    184             raise e
    185 
--&gt; 186         fudged_image = image.copy()
    187         if hide_color is None:
    188             for x in np.unique(segments):

AttributeError: 'Tensor' object has no attribute 'copy'
</code></pre>