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This project contains code to train and run a neural network to detect cat faces in videos. The network uses a pretrained ResNet-18 with รก trous trick as its core and adds three additional convolutional layers on top of that. It predicts heatmaps of face locations and derives bounding boxes from those outputs. The model does not use an RPN (region proposal network). Runtime is around 30-60ms per frame on medium hardware (though only ~5ms of that is down to the CNN, so there is a lot of room for improvement). Implementation is done in PyTorch.


Example video of detected bounding boxes:

Example video

Example video of the training progress:

Example video training progress