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tooth-detection

(★ 228)

🦷 Detection of restorations and treatments on dental x-rays in Tensorflow, using Faster-RCNN

파일 탐색기

최종 버전 다운로드 (.zip)

- - cloud.yml
- - index.config
  - index_local.config
- - colab.config
  - faster_rcnn_resnet101_coco.config
  - faster_rcnn_resnet50_coco.config
  - ssd.config
  - tpu.config
- - 1.png
  - 2.png
  - 3.png
- merge_datasets.py
- vott.py
- train.py
.gitignore
commands.md
data_preprocessing.py
inference.py
LICENSE
README.md
requirements.txt

# 설치 가이드

1. 코드 내려받기

git clone https://github.com/clemkoa/tooth-detection

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd tooth-detection

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. Python

쉬움 추천

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
Python 3 설치 시 'Add Python to PATH' 옵션을 꼭 체크하세요 (Windows).

pip install -r requirements.txt

requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.

✅ 에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.

이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.

// repository documentation

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# Teeth detector

![Image 1](https://raw.githubusercontent.com/clemkoa/tooth-detection/master/public/images/1.png "Image 1")
![Image 2](https://raw.githubusercontent.com/clemkoa/tooth-detection/master/public/images/2.png "Image 2")
![Image 3](https://raw.githubusercontent.com/clemkoa/tooth-detection/master/public/images/3.png "Image 3")

⚠️ Dataset is private at the moment. For privacy reasons it can't be shared. We are trying to get approval from hospitals and patients included in this dataset but this a work in progress. For the same privacy reasons the trained model can't be shared at the moment.

The dataset was made with a stomatologist surgeon using VoTT for labeling. The export was made under the `Tensorflow Pascal VOC` format

The project is divided into two tasks:
1. Detect tooth restoration, endodontic treatment and implants (models/treatment)
2. Detect teeth and identify their ISO Dental Notation (models/index)

## Installation

- Download the datasets from the google drive (datasets are private at the moment)
- Install tensorflow object detection: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md
- Install Cloud SDK to run on google cloud https://cloud.google.com/sdk/

```
pip install -r requirements.txt

# Tensorflow Object Detection API
git clone git@github.com:tensorflow/models.git

git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
make
cp -r pycocotools <path_to_tensorflow>/models/research/

# From tensorflow/models/research/
export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim
```

## Training

```
python <path_to_tensorflow>/models/research/object_detection/model_main.py \
    --pipeline_config_path=<path_to_tooth-detection>/tooth-detection/models/treatment/faster_rcnn_resnet50_coco.config \
    --model_dir=<path_to_tooth-detection>/tooth-detection/models/treatment/model \
    --num_train_steps=100000 \
    --alsologtostderr
```

## Inference

```
python inference.py \
    --PATH_TO_FROZEN_GRAPH=<path_to_tooth-detection>/<path_to_frozen_graph>/frozen_inference_graph.pb \
    --PATH_TO_TEST_IMAGES_DIR=<path_to_tooth-detection>/data/iran_index/JPEGImages \
    --PATH_TO_LABELS=<path_to_tooth-detection>/data/pascal_label_map_index.pbtxt
```