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file.\n\nAdditionally, TFBox contains a number of useful tools for TensorFlow, including:\n\n- [an extremely flexible sequence class](#sequence) \n- [tools for model scoring](#scores) \n- [weighted metrics](#metrics) \n- [weighted loss function](#loss)\n- [tensorboard callbacks](#tb)\n\n---\n\n##### INSTALL\n\n`pip install tfbox`\n\n##### ADDITIONAL REQUIREMENTS\n\n- imagebox: https://github.com/brookisme/imagebox    \n- TF\u003e2\n- numpy\n- pandas\n- pyyaml\n\n\n\u003ca name='#models'\u003e\u003c/a\u003e\n\n---\n\n#### MODELS\n\n`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.\n\nHere is the config for the [Xception Network](https://arxiv.org/abs/1610.02357):\n\nxception:\n\n```yaml\n    blocks_config:\n        - conv:\n            filters: 32\n            strides: 2\n        - 64\n        - stack:\n            name: entry_flow_blocks\n            seperable: true\n            depth: 3\n            output_stride: 2\n            layers: [128,256,728]\n        - stack:\n            name: middle_flow\n            nb_repeats: 16\n            depth: 3\n            filters: 728\n        - stack:\n            name: exit_flow_block\n            output_stride: 2\n            filters_list: [728,1024,1024]\n        - stack:\n            name: exit_flow_convs\n            seperable: true\n            residual: false\n            layers: [1536,1536,2048]\n        - aspp\n```\n\n\n\u003ca name='#sequence'\u003e\u003c/a\u003e\n\n---\n\n#### DFSequence\n\n`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.\n\n\u003ca name='#scoring'\u003e\u003c/a\u003e\n\n---\n\n#### SCORING\n\n\n\n\n\u003ca name='#metrics]'\u003e\u003c/a\u003e\n\n\n---\n\n#### METRICS\n\n\u003ca name='#loss'\u003e\u003c/a\u003e\n\n---\n\n#### LOSS FUNCTIONS\n\n\n\n\u003ca name='#callbacks'\u003e\u003c/a\u003e\n\n---\n\n#### TENSORBOARD CALLBACKS\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrookisme%2Ftfbox","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbrookisme%2Ftfbox","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrookisme%2Ftfbox/lists"}