***Use case n°1:** Use a pre-trained µPIX model to denoise an image dataset (```metrology``` dataset) [](https://colab.research.google.com/drive/1EbV04iv141q7ebVUOErJupYboaCV40OD?usp=drive_link)
***Use case n°2:** Train a µPIX model from scratch using a custom dataset (```metrology``` dataset) [](https://colab.research.google.com/drive/1GaD6rjWGJsBr2dFy-WPLC3YjCZO4LJGl?usp=drive_link)
***Use Case n°1:** Use a pre-trained µPIX model to denoise an image dataset (```metrology``` dataset) [](https://colab.research.google.com/drive/1EbV04iv141q7ebVUOErJupYboaCV40OD?usp=drive_link)
***Use Case n°2:** Train a µPIX model from scratch using a custom dataset (```metrology``` dataset) [](https://colab.research.google.com/drive/1GaD6rjWGJsBr2dFy-WPLC3YjCZO4LJGl?usp=drive_link)
## Install required µPIX Environment and Sources ([Tutorial VIDEO](https://sync.lis-lab.fr/index.php/s/GeNyYdLHMCRTfS9))
...
...
@@ -176,7 +176,7 @@ Once finished, the denoised images are stored inside ```./experiments/metrology_
</details>
## Use case n°2 - Train a µPIX model from scratch using a custom dataset
## Use Case n°2 - Train a µPIX model from scratch using a custom dataset