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Docs/sa/fix readme (#71)
* updated logo * Increased the logo size * Increased the logo size * Update README.md * removed redundant padim line
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README.md

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<div align="center">
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<img src="docs/source/images/logos/anomalib-wide.png" width="400px">
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<img src="docs/source/images/logos/anomalib-wide-blue.png" width="600px">
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**A library for benchmarking, developing and deploying deep learning anomaly detection algorithms**
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___
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```
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Training a model on a specific dataset and category requires further configuration. Each model has its own configuration
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file, [`config.yaml`](https://gitlab-icv.inn.intel.com/algo_rnd_team/anomaly/-/blob/development/stfpm/anomalib/models/stfpm/config.yaml)
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file, [`config.yaml`](https://gitlab-icv.inn.intel.com/algo_rnd_team/anomaly/-/blob/development/padim/anomalib/models/padim/config.yaml)
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, which contains data, model and training configurable parameters. To train a specific model on a specific dataset and
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category, the config file is to be provided:
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```bash
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python tools/train.py --model_config_path <path/to/model/config.yaml>
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```
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For example, to train [STFPM](anomalib/models/stfpm) you can use
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For example, to train [PADIM](anomalib/models/padim) you can use
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```bash
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python tools/train.py --model_config_path anomalib/models/stfpm/config.yaml
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python tools/train.py --model_config_path anomalib/models/padim/config.yaml
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```
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Alternatively, a model name could also be provided as an argument, where the scripts automatically finds the corresponding config file.
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```bash
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python tools/train.py --model stfpm
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python tools/train.py --model padim
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```
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where the currently available models are:
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- [CFlow](anomalib/models/cflow)
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- [PADIM](anomalib/models/padim)
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- [PatchCore](anomalib/models/patchcore)
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- [PADIM](anomalib/models/padim)
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- [STFPM](anomalib/models/stfpm)
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- [DFM](anomalib/models/dfm)
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- [DFKDE](anomalib/models/dfkde)
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