Created
December 12, 2019 05:58
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PyTorch Helper: Plot the MNIST image and percentage graph
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import matplotlib.pyplot as plt | |
import numpy as np | |
def view_classify(img, ps, version="MNIST"): | |
''' Function for viewing an image and it's predicted classes. | |
''' | |
ps = ps.data.numpy().squeeze() | |
fig, (ax1, ax2) = plt.subplots(figsize=(6,9), ncols=2) | |
ax1.imshow(img.resize_(1, 28, 28).numpy().squeeze()) | |
ax1.axis('off') | |
ax2.barh(np.arange(10), ps) | |
ax2.set_aspect(0.1) | |
ax2.set_yticks(np.arange(10)) | |
if version == "MNIST": | |
ax2.set_yticklabels(np.arange(10)) | |
elif version == "Fashion": | |
ax2.set_yticklabels(['T-shirt/top', | |
'Trouser', | |
'Pullover', | |
'Dress', | |
'Coat', | |
'Sandal', | |
'Shirt', | |
'Sneaker', | |
'Bag', | |
'Ankle Boot'], size='small'); | |
ax2.set_title('Class Probability') | |
ax2.set_xlim(0, 1.1) | |
plt.tight_layout() |
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