Simple convolutional neural network to detect cat bounding boxes in images. The system is restricted to one bounding box per image, which is localized using regression (i.e. directly predicting the bounding box coordinates). The model consists of 7 convolutional layers and 2 fully connected layers (including output layer).
/foo/bar/10k-cats
. That directory should contain the subdirectories CAT_00
, CAT_01
, etc.train_convnet.py --dataset="/foo/bar/10k-cats"
.train_convnet.py --dataset="/foo/bar/directory-with-cat-images"
.Example results: