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https://github.com/brookisme/tfbox
Tensorflow Models and Tools
https://github.com/brookisme/tfbox
Last synced: 22 days ago
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Tensorflow Models and Tools
- Host: GitHub
- URL: https://github.com/brookisme/tfbox
- Owner: brookisme
- License: mit
- Created: 2020-07-23T03:45:37.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-09-07T18:49:20.000Z (about 2 years ago)
- Last Synced: 2024-10-01T16:38:49.069Z (about 1 month ago)
- Language: Python
- Size: 4.28 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# tfbox
a collection of models and tools for tensorflow
---
TFBox's main utility lies within:
- [`tfbox.nn.encoder/decoder/encoder-decoder`](#models): an extremely flexible encoder/decoder python classes from which most modern architectures can be built using a simple (yaml) config file.
Additionally, TFBox contains a number of useful tools for TensorFlow, including:
- [an extremely flexible sequence class](#sequence)
- [tools for model scoring](#scores)
- [weighted metrics](#metrics)
- [weighted loss function](#loss)
- [tensorboard callbacks](#tb)
---
##### INSTALL
`pip install tfbox`
##### ADDITIONAL REQUIREMENTS
- imagebox: https://github.com/brookisme/imagebox
- TF>2
- numpy
- pandas
- pyyaml
---
#### MODELS
`tfbox.nn.encoder/decoder/encoder-decoder` use yaml files to combine keras-model-blocks in `tfbox.nn.blocks` to build neural-networks. The result is an flexible system from which you can build a large variety of models. Lets start with some examples.
Here is the config for the [Xception Network](https://arxiv.org/abs/1610.02357):
xception:
```yaml
blocks_config:
- conv:
filters: 32
strides: 2
- 64
- stack:
name: entry_flow_blocks
seperable: true
depth: 3
output_stride: 2
layers: [128,256,728]
- stack:
name: middle_flow
nb_repeats: 16
depth: 3
filters: 728
- stack:
name: exit_flow_block
output_stride: 2
filters_list: [728,1024,1024]
- stack:
name: exit_flow_convs
seperable: true
residual: false
layers: [1536,1536,2048]
- aspp
```
---
#### DFSequence
`tfbox.loaders.DFSequence` builds instances of `tf.keras.utils.Sequence` for image segmentation models using pandas dataframes. In particular it does almost anything you can imagine - but also can be bit overwhelming.
---
#### SCORING
---
#### METRICS
---
#### LOSS FUNCTIONS
---
#### TENSORBOARD CALLBACKS