Examples_core.ipynb doesn't work

[alfredonuhe]

Hi, I am running the core example code for Vanilla Gradient & SmoothGrad on a Kaggle notebook, and I get the error below:

---

ValueError Traceback (most recent call last)
in
6 ShowImage(im_orig)
7
----> 8 _, predictions = model(np.array([im]))
9 prediction_class = np.argmax(predictions[0])
10 call_model_args = {class_idx_str: prediction_class}

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in call(self, *args, **kwargs)
996 inputs = self._maybe_cast_inputs(inputs, input_list)
997
--> 998 input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
999 if eager:
1000 call_fn = self.call

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/input_spec.py in assert_input_compatibility(input_spec, inputs, layer_name)
272 ' is incompatible with layer ' + layer_name +
273 ': expected shape=' + str(spec.shape) +
--> 274 ', found shape=' + display_shape(x.shape))
275
276

ValueError: Input 0 is incompatible with layer model_1: expected shape=(None, 224, 224, 3), found shape=(1, 224, 224, 4)

---

Here is the kaggle notebook with the error.

The only lines I have modified in the example are:

# From our repository.
import saliency.core as saliency

and

# Load the image
im_orig = LoadImage('./doberman.png')

as

# From our repository.
try:
    import saliency.core as saliency`
except:
    ! pip install saliency
    import saliency.core as saliency`

and

# Load the image
im_orig = LoadImage('../input/saliency-imgs/doberman.png')

Also, I have seen there was an issue (#5) created for the code examples to be adapted to TF2. But since the current title of the examples states "for TF2 and other frameworks" I assume the code was finally adapted, and this issue isn't relevant anymore for the problem I am describing.

Thank you.

[joydisette]

@alfredonuhe You need to load jpg images or convert your png to jpg to remove a dimension

[bwedin]

Yes it looks like your version of the image has an extra alpha layer (RGBA image rather than RGB). You could do as @joydisette suggested above (convert to JPG, or convert to a PNG with no alpha/transparency layer). Alternatively, you could remove the extra alpha channel from the numpy array directly:

im_rgba = LoadImage('../input/saliency-imgs/doberman.png') im_rgb = im_rgba[:,:,:3] im = PreprocessImage(im_rgb)

Let us know if you are still having issues. Thanks!