ConvNet architectures on Google-Colaboratory
Main idea of QuickCNN is to train deep ConvNet without diving into architectural details. QuickCNN works as an interactive tool for transfer learning, finetuning, and scratch training with custom datasets. It has pretrained model zoo and also works with your custom keras model architecture.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size quickcnn-0.0.12-py3-none-any.whl (26.0 kB)||File type Wheel||Python version py3||Upload date||Hashes View hashes|
|Filename, size quickcnn-0.0.12.tar.gz (27.1 kB)||File type Source||Python version None||Upload date||Hashes View hashes|
Hashes for quickcnn-0.0.12-py3-none-any.whl