{"id":24409550,"url":"https://github.com/light4code/tensorflow-research","last_synced_at":"2025-09-30T14:33:22.682Z","repository":{"id":39729922,"uuid":"243961595","full_name":"Light4Code/tensorflow-research","owner":"Light4Code","description":"Research TensorFlow for machine vision industrial usage","archived":false,"fork":false,"pushed_at":"2022-11-21T22:47:26.000Z","size":29575,"stargazers_count":5,"open_issues_count":2,"forks_count":3,"subscribers_count":6,"default_branch":"master","last_synced_at":"2023-03-08T22:56:10.880Z","etag":null,"topics":["anomaly-detection","image-processing","industrial","industrial-automation","keras","neural-structured-learning","nsl","segmentation","tensorflow","unet","unet-image-segmentation","unet-keras"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# tensorflow-research\n\n## Goal\n\nThe goal of this repository is to research TensorFlow for machine vision industrial usage. \u003cbr/\u003e\nIt will provide easy to use methods to train models from scratch and also fine tune them afterwards.\n\n## Starting point\nTo quickly get into the usage you can look into the notebooks, they provide the whole training pipline step by step.\n\n## Backbones\nBackbones provide you with a ready to use model architectur.\n### Anomaly detection\nAnomaly detection will use a autoencoder approche, the prediction substratced from the original image should show the anomaly.\n\n### Segmentation\n#### Unet\n- [Vanilla Unet](https://arxiv.org/pdf/1505.04597.pdf) (original paper)\n- [Custom/Satellite Unet](https://github.com/karolzak/keras-unet)\n\n|           Class            |       Group       |           Backbone            |            Sample notebook            |\n|:--------------------------:|:-----------------:|:-----------------------------:|:-------------------------------------:|\n|    `ClassificationConv`    |  Classification   |     `classification_conv`     |                                       |\n|                            |        ---        |              ---              |                                       |\n|     `AutoEncoderConv`      | Anomaly Detection |      `auto_encoder_conv`      | Choco waffle anomaly detection sample |\n| `AutoEncoderFullConnected` | Anomaly Detection | `auto_encoder_full_connected` |                                       |\n|                            |        ---        |              ---              |                  ---                  |\n| `SegmentationVanillaUnet`  |   Segmentation    |  `segmentation_vanilla_unet`  |    Wood plate segmentation sample     |\n|            TODO            |   Segmentation    |       `satellite_unet`        |                                       |\n|            TODO            |   Segmentation    |         `custom_unet`         |                                       |","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flight4code%2Ftensorflow-research","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flight4code%2Ftensorflow-research","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flight4code%2Ftensorflow-research/lists"}