Micrograph Segmentation using PixelPick

This repository implements PixelPick for low-annotation micrograph segmentation. The code is based on the original PixelPick paper (https://arxiv.org/abs/2104.06394).

Setup

pip install -r requirements.txt

PixelPick query configuration

A sample query configuration can be found in configs/uhcs/default.yaml. The parameters for making queries are:

• max_pixels: maximum number of pixels to query excluding the starting pixels
• n_pixels_per_round: number of pixels to query in each round for each class
• n_init_pixels_per_class: number of pixels to query for each class at the beginning
• query_strategy: the query strategy to use, can be random, entropy, margin, least_confidence.
• top_n_percent: the top n percent of pixels to randomly sample from using the query strategy. For example, if top_n_percent is 0.05 and query_strategy is entropy, then the top 5% pixels with the highest entropy will be randomly sampled from.

Data preparation and training configuration

The details of data preparation and training configuration can be found at https://github.com/leibo-cmu/MatSeg.

Training

The following command trains segmentation models with incremental queries using the entropy query strategy:

python train_pixelpick.py --config entropy.yaml