Training Doesn't work

[kgkatzonis]

Even though training completes, I can not test the cascade. Here's the training output for 5 positive and 5 negative examples.

Importing face examples from: data/f/ ...
Importing background examples from: data/n/ ...

Generating type 1 features...
Generating type 2 features...
Generating type 3 features...
Generating type 4 features...

Training 6526017 features...

BOOSTING ROUND 1

Selected ((0, 11), (0, 9)) ((0, 10), (0, 10)) -1 -1.0 0.0
Boosted classifier has 1 features with ensemble false positive rate
0.00000 and error 0.00000.
Boosting concluded with 1 classifiers and remaining background
proportion: 0.00000

And here's the output from testing:

PS D:\PC Media Files\Desktop\ViolaJones-master> python violajones.py -f data/f/ -b data/n/ -l cascade_save.json -t test.
jpg -v
Evaluating cascade in 0 image patches.
Traceback (most recent call last):
File "violajones.py", line 439, in
run()
File "D:\PC Media Files\Desktop\Python\lib\site-packages\click\core.py", line 722, in call
return self.main(*args, **kwargs)
File "D:\PC Media Files\Desktop\Python\lib\site-packages\click\core.py", line 697, in main
rv = self.invoke(ctx)
File "D:\PC Media Files\Desktop\Python\lib\site-packages\click\core.py", line 895, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "D:\PC Media Files\Desktop\Python\lib\site-packages\click\core.py", line 535, in invoke
return callback(*args, **kwargs)
File "violajones.py", line 434, in run
face_indices = get_cascade_prediction(cascade, np.array(integral_images), np.array(indices), verbose=verbose)
File "violajones.py", line 386, in get_cascade_prediction
classifiers, alphas, +0.25 * threshold, integral_image(integral_images), integral_images[:1]
File "D:\PC Media Files\Desktop\ViolaJones-master\util.py", line 36, in integral_image
return arr.cumsum(axis=-1).cumsum(axis=-2)
numpy.core._internal.AxisError: axis -2 is out of bounds for array of dimension 1