Challenge resolution by appling segmentation techniques.
Directories layout:
particle-ViT-segmentation
├── Config
│ └── ...
├── Dataset
│ └── install_dataset.py
├── preprocessing
│ ├── analyser.py
│ ├── creation.py
│ ├── Dataset.py
│ └── segmentation.py
├── techniques
│ ├── unet
│ └── vit
├── ut
│ └── ...
├── utils
│ └── ...
├── main.py
├── create_dataset.py
├── requirements.txt
└── README.md
Make sure you have all the necessary requirements to use this repo.
git clone https://github.com/AngeloDamante/particle-ViT-segmentation.git
cd particle-ViT-segmentation
pip3 install -r requirements.txt
The starting datasets for challenge can be found here. For your convenience, it can be easily downloaded.
# in particle-ViT-segmentation directory
python3 Dataset/install_dataset.pyThe dataset was generated by performing convolution between a black image with white points centered in the groundtruth values and a Gaussian filter.
To generate raw data, we have written create_dataset.py script that you can use with input json file for config settings.
usage: create_dataset.py [-h] [-C CONFIG]
optional arguments:
-h, --help show this help message and exit
-C CONFIG, --config CONFIG name of config in CONFIG_DIR
The raw data generated have the structure below:
[
img:np.ndarray,
target:np.ndarray,
gth:List[Particle],
snr:SNR,
density:Density,
t:int
]
TODO
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