Appropriated from https://github.com/GeorgeSeif/Transfer-Learning-Suite and heavily modified. New:
- bottleneck features for super-fast classifier retraining (within imagenet scope)
- bottleneck generator allows use of large datasets
- automatic on-the-fly splitting into train and validation dataset, with pre-split shuffle
- TensorBoard integration
- precision and recall metrics
- other stuff
Still under heavy construction.
All of the Keras built in models are made available:
Model | Size | Top-1 Accuracy | Top-5 Accuracy | Parameters | Depth |
---|---|---|---|---|---|
VGG16 | 528 MB | 0.715 | 0.901 | 138,357,544 | 23 |
VGG19 | 549 MB | 0.727 | 0.910 | 143,667,240 | 26 |
ResNet50 | 99 MB | 0.759 | 0.929 | 25,636,712 | 168 |
Xception | 88 MB | 0.790 | 0.945 | 22,910,480 | 126 |
InceptionV3 | 92 MB | 0.788 | 0.944 | 23,851,784 | 159 |
InceptionResNetV2 | 215 MB | 0.804 | 0.953 | 55,873,736 | 572 |
MobileNet | 17 MB | 0.665 | 0.871 | 4,253,864 | 88 |
DenseNet121 | 33 MB | 0.745 | 0.918 | 8,062,504 | 121 |
DenseNet169 | 57 MB | 0.759 | 0.928 | 14,307,880 | 169 |
DenseNet201 | 80 MB | 0.770 | 0.933 | 20,242,984 | 201 |
NASNetMobile | 21 MB | NA | NA | 5,326,716 | NA |
NASNetLarge | 342 MB | NA | NA | 88,949,818 | NA |