update READMEs

.gitignore

@@ -114,4 +114,7 @@ venv.bak/
 Part1Unet/models
 Part1Unet/logs
 Part1Unet/unet_model.png
+Part1Unet/unet_full.ipynb
 Part2Cellpose/models
+Part2Cellpose/train_cellpose_full.ipynb
+Part2Cellpose/use_cellpose_full.ipynb
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Part1Unet/README.md

-# Unet
+# U-Net
 
-Install unet env in conda
+To run the notebook:
 
 ```
 setconda
-conda env create -f unet_env.yml
-```
-
-Launch the jupyter notebook
-
-```
-setconda
-conda activate qlife25-unet
+conda activate /users/bioensei/mphan/.conda/envs/qlife25-unet
 setenv LD_LIBRARY_PATH "${CONDA_PREFIX}/lib:${LD_LIBRARY_PATH}"
 jupyter notebook
 ```
+
+

Part2Cellpose/README.md

 # Cellpose
 
-Run the following commands to install cellpose env in conda
+To run the notebook:
 
 ```
 setconda
-conda create -n qlife25-cellpose python=3.10 -y
-conda activate qlife-cellpose
-conda install pytorch==1.12.0 cudatoolkit=11.3 -c pytorch
-pip uninstall torch
-pip install 'cellpose[gui]'
-pip install notebook==6.1.5 scikit-image matplotlib
-```
-
-Launch the jupyter notebook
-
-```
-setconda
-conda activate qlife25-cellpose
+conda activate /users/bioensei/mphan/.conda/envs/qlife25-cellpose
 jupyter notebook
 ```
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README.md

-# 2025_qlife_psl_dl_course
+# PSL Qlife Quantitative Biology Spring School 2025
 
-Materials for the course cellular segmentation with deep learning.
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+Materials for the course *cellular segmentation with deep learning*. 
+
+The course is organized in two parts:
+
+- Part 1: Semantic segmentation with U-Net.
+- Part 2: Instance segmentation with Cellpose.
+
+Please download and unzip this repo to your local.
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