Neural networks are often described as "black box". The lack of understanding on how neural networks make predictions enables unpredictable/biased models, causing real harm to society and a loss of trust in AI-assisted systems.
Feature visualization is an area of research, which aims to understand how neural networks perceive images. However, implementing such techniques is often complicated.
FlashTorch was created to solve this problem!
You can apply feature visualization techniques such as saliency maps and activation maximization on your model, with as little as a few lines of code.
It is compatible with pre-trained models that come with torchvision, and seamlessly integrates with other custom models built in PyTorch.
All FlashTorch wheels on PyPI are distrubuted with the MIT License.
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