Hi,
I want to explain images using LIME:
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()
but I get this error:
TypeError Traceback (most recent call last)
<ipython-input-48-0ad542da0c28> in <cell line: 20>()
24 image_np = image.squeeze(0).permute(1, 2, 0).numpy()
25
---> 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)
--> 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)
without converting to numpy:
image_np = image.squeeze(0).permute(1, 2, 0)
this error occurs:
AttributeError Traceback (most recent call last)
<ipython-input-49-04ca51ebb1aa> in <cell line: 20>()
24 image_np = image.squeeze(0).permute(1, 2, 0)
25
---> 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
--> 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'