acne_detection

acne_detection

https://github.com/wenh06/acne_detection

Science Score: 13.0%

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    Found 1 DOI reference(s) in README
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    Low similarity (4.0%) to scientific vocabulary
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Repository

acne_detection

Basic Info
  • Host: GitHub
  • Owner: wenh06
  • License: mit
  • Language: Python
  • Default Branch: master
  • Size: 129 MB
Statistics
  • Stars: 4
  • Watchers: 2
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Created over 6 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

acne_detection

acne_detection

ran in python 3.6.8

Requirements

  • tensorflow == 1.13.1

Training

```shell export PYTHONPATH=$PYTHONPATH:/PATHTOTHE_PROJECT/slim/

nohup python3.6 objectdetection/modelmain.py --pipelineconfigpath=fasterrcnnresnet101coco.config --modeldir=./savedmodels/ --numtrainsteps=20000 --numevalsteps=2000 --alsologtostderr > acnetrain.log & ```

Exporting the model

shell python3.6 object_detection/export_inference_graph.py --input_type image_tensor --pipeline_config_path faster_rcnn_resnet101_coco.config --trained_checkpoint_prefix ./saved_models/model.ckpt-xxxxx --output_directory ./latest_models/

Pretrained model

A pretrained model (fasterrcnnresnet101) can be found at MEGA, another (fasterrcnninception_v2) at MEGA.

P.S. MEGA is the best cloud drive I've ever used. Strong recommendation for it.

Citation

latex @article{thc_2022_acne_detection, title = {{Acne Detection and Severity Evaluation with Interpretable Convolutional Neural Network Models}}, author = {Wen, Hao and Yu, Wenjian and Wu, Yuanqing and Zhao, Jun and Liu, Xiaolong and Kuang, Zhexiang and Fan, Rong}, journal = {Technology and Health Care}, doi = {10.3233/thc-228014}, issn = {1878-7401}, year = {2022}, month = {2}, publisher = {{IOS Press}}, volume = {30}, pages = {143--153} }

Owner

  • Name: WEN Hao
  • Login: wenh06
  • Kind: user
  • Location: Beijing
  • Company: Tsinghua University

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Dependencies

object_detection/dockerfiles/android/Dockerfile docker
  • tensorflow/tensorflow nightly-devel build