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master_thesis_models
13hannes11/master_thesis_models
master_thesis_models is a machine learning model from 13hannes11. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
<a href="https://pytorch.org/get-started/locally/"<img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white"</a<a href="https://pytorchlightning.ai/" <img alt="Lightning" src="ht…
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Updated Jun 28, 2022
Repo size
76.7 GB
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Repo makeup
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.ckpt1.3 GB · 92%
At a glance
- License
- mit
- Access
- Public
- Created
- Mar 8, 2022
- Updated
- Jun 28, 2022
- SHA
- 3ed3f87a
Model card
From the Hugging Face model README
K-POP: Predicting Distance to Focal Plane for Kato-Katz Prepared Microscopy Slides Using Deep Learning
<a href="https://pytorch.org/get-started/locally/"><img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white"></a><a href="https://pytorchlightning.ai/"> <img alt="Lightning" src="https://img.shields.io/badge/-Lightning-792ee5?logo=pytorchlightning&logoColor=white"></a> <a href="https://hydra.cc/"><img alt="Config: Hydra" src="https://img.shields.io/badge/Config-Hydra-89b8cd"></a>
Description
This repository contains the models and training pipeline for my master thesis. The main repository is hosted on GitHub.
The project structure is based on the template by ashleve.
The metadata is stored in data/focus150/. The relevant files are test_metadata.csv, train_metadata.csv and validation_metadata.csv. Image data (of 150 x 150 px images) is not published together with this repository therefore training runs are not possible to do without it. The layout of the metadata files is as follows
,image_path,scan_uuid,study_id,focus_height,original_filename,stack_id,obj_name
0,31/b0d4005e-57d0-4516-a239-abe02a8d0a67/I02413_X009_Y014_Z5107_750_300.jpg,b0d4005e-57d0-4516-a239-abe02a8d0a67,31,-0.013672000000000017,I02413_X009_Y014_Z5107.jpg,1811661,schistosoma
1,31/274d8969-aa7c-4ac0-be60-e753579393ad/I01981_X019_Y014_Z4931_450_0.jpg,274d8969-aa7c-4ac0-be60-e753579393ad,31,-0.029296999999999962,I01981_X019_Y014_Z4931.jpg,1661371,schistosoma
...
How to run
Train model with chosen experiment configuration from configs/experiment/
python train.py experiment=focusResNet_150
Train with hyperparameter search from configs/hparams_search/
python train.py -m hparams_search=focusResNetMSE_150
You can override any parameter from command line like this
python train.py trainer.max_epochs=20 datamodule.batch_size=64
Jupyter notebooks
Figures and other evaluation code was run in Jupyter notebooks. These are available at notebooks/
- License
- mit
- Created
- Mar 8, 2022
- Updated
- Jun 28, 2022