<!----------------------------------------------------------------------->
<a name="readme-top"></a>
<!----------------------------------------------------------------------->
<table width="100%" style="border: none;">
<tr>
<td align="left" style="border: none;"><b>LE GOURRIEREC Titouan</b></td>
<td align="left" style="border: none;"></td>
<td align="right" style="border: none;">
<a href="https://www.linkedin.com/in/titouanlegourrierec"><img src="https://img.shields.io/badge/linkedin-%230077B5.svg?style=for-the-badge&logo=linkedin&logoColor=white" alt="LinkedIn"></a>
<a href="mailto:titouanlegourrieræec@icloud.com"><img src="https://img.shields.io/badge/email-%23339933.svg?style=for-the-badge&logo=mail.ru&logoColor=white" alt="Mail"></a>
</td>
</tr>
</table>
<!----------------------------------------------------------------------->
<!----------------------------------------------------------------------->
<!-- PROJECT LOGO -->
<br />
<div align="center">
<h3 align="center">EasIlastik </h3>
<p align="center">
A package to facilitate the use of image segmentation model trained on Ilastik in Python
<br />
<a href="https://github.com/titouanlegourrierec/EasIlastik/wiki"><strong>Explore the docs »</strong></a>
<br />
<a href="https://github.com/titouanlegourrierec/EasIlastik/issues">Report a bug · Request Feature</a>
</p>
<p align="center">
<a href="https://pypi.org/project/EasIlastik/">
<img src="https://img.shields.io/pypi/v/EasIlastik.svg" alt="PyPI Version">
</a>
</a>
<a href="https://pepy.tech/project/EasIlastik">
<img src="https://pepy.tech/badge/EasIlastik" alt="Downloads">
</a>
<a href="https://github.com/psf/black">
<img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Code Style: Black">
</a>
<a href="https://github.com/titouanlegourrierec/EasIlastik/blob/main/LICENSE">
<img src="https://img.shields.io/github/license/titouanlegourrierec/EasIlastik.svg" alt="License">
</p>
</div>
<!-- TABLE OF CONTENTS -->
<details>
<summary>Table of Contents</summary>
<ol>
<li>
<a href="#about-the-project">About The Project 📖</a>
<ul>
<li><a href="#built-with">Built With 🛠️</a></li>
</ul>
</li>
<li>
<a href="#getting-started">Getting Started</a>
<ul>
<li><a href="#prerequisites">Prerequisites</a></li>
</ul>
</li>
<li><a href="#usage">Usage</a></li>
<li><a href="#license">License</a></li>
<li><a href="#contact">Contact</a></li>
<li><a href="#acknowledgments">Acknowledgments</a></li>
</ol>
</details>
<!----------------------------------------------------------------------->
<!----------------------------------------------------------------------->
## About The Project
<p align="center">
<img src="https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/img.png" width="100%">
</p>
This package provides seamless integration of pre-trained image segmentation models from Ilastik into Python workflows, empowering users with efficient and intuitive image segmentation capabilities for diverse applications.
<!----------------------------------------------------------------------->
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!----------------------------------------------------------------------->
### Built With
* [![Python][Python-badge]][Python-url]
* [![OpenCV][OpenCV-badge]][OpenCV-url]
* ![Shell Script][ShellScript-badge]
<!----------------------------------------------------------------------->
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!----------------------------------------------------------------------->
## Getting Started
### Prerequisites
* **Ilastik software**: To train your own model for image segmentation, please download the Ilastik software tailored to your computer's operating system from: https://www.ilastik.org/download.
### Train a model
* To train your own model on Ilastik and properly adjust the different parameters, please refer to [this documentation](https://github.com/titouanlegourrierec/EasIlastik/wiki/Train-a-model-on-Ilastik).
<!----------------------------------------------------------------------->
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!----------------------------------------------------------------------->
## Usage
For usage examples of this package, please refer to the [Example Notebook](https://github.com/titouanlegourrierec/EasIlastik/blob/1be43ebb76bccec6917e05367fbb7e48b184efdc/Examples/example-notebook.ipynb).
### Process a single image
```python
EasIlastik.run_ilastik(input_path = "path/to/your/image.jpg", # The path of the image to process
model_path = "path/to/your/model.ilp",
result_base_path = "path/to/your/output/folder/",
export_source = "Simple Segmentation",
output_format = "png")
```
<p align="center">
<img src="https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_image.png" alt="run_ilastik_image" width="50%">
</p>
### Process a folder of images
```python
EasIlastik.run_ilastik(input_path = "path/to/input/folder", # The path of the folder to process
model_path = "path/to/your/model.ilp",
result_base_path = "path/to/your/output/folder/",
export_source = "Simple Segmentation",
output_format = "png")
```
<p align="center">
<img src="https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_folder.png" alt="run_ilastik_folder" width="70%">
</p>
### Show probabilities
```python
EasIlastik.run_ilastik(input_path = "path/to/input/image",
model_path = "path/to/model.ilp",
result_base_path = "path/to/output/folder",
export_source="Probabilities", # Probabilities
output_format="hdf5") # hdf5 format
output_path = "path/to/output/image.h5"
image = EasIlastik.color_treshold_probabilities(output_path, threshold, below_threshold_color, channel_colors)
```
<p align="center">
<img src="https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_show_probabilities.png" alt="run_ilastik_probabilities" width="70%">
</p>
### Run with probabilities
```python
EasIlastik.run_ilastik_probabilities(input_path = "path/to/input/folder",
model_path = "path/to/model.ilp",
result_base_path = "path/to/output/folder",
threshold = 70, # threshold for the probabilities
below_threshold_color = [255, 0, 0], # color for the pixels below the threshold (red)
channel_colors = [[63, 63, 63], [127, 127, 127], ...] # colors for the different channels
)
```
<p align="center">
<img src="https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_run_probabilities.png" alt="run_ilastik_probabilities" width="70%">
</p>
<!----------------------------------------------------------------------->
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!----------------------------------------------------------------------->
<!-- ROADMAP -->
<!-- ## Roadmap
- [x] Add Changelog
- [x] Add back to top links
- [ ] Add Additional Templates w/ Examples
- [ ] Add "components" document to easily copy & paste sections of the readme
- [ ] Multi-language Support
- [ ] Chinese
- [ ] Spanish
See the [open issues](https://github.com/othneildrew/Best-README-Template/issues) for a full list of proposed features (and known issues).
<p align="right">(<a href="#readme-top">back to top</a>)</p> -->
<!-- CONTRIBUTING -->
<!-- ## Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
<p align="right">(<a href="#readme-top">back to top</a>)</p> -->
## License
Distributed under the GNU License like the Ilastik software. See [`LICENSE`](https://github.com/titouanlegourrierec/EasIlastik/blob/1be43ebb76bccec6917e05367fbb7e48b184efdc/LICENCE) for more information.
<!----------------------------------------------------------------------->
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!----------------------------------------------------------------------->
## Contact
LE GOURRIEREC Titouan - [titouanlegourrierec@icloud.com](mailto:titouanlegourrierec@icloud.com)
Repository Link: [https://github.com/titouanlegourrierec/EasIlastik](https://github.com/titouanlegourrierec/EasIlastik)
Pypi Link : [https://pypi.org/project/EasIlastik/](https://pypi.org/project/EasIlastik/)
<!----------------------------------------------------------------------->
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!----------------------------------------------------------------------->
## Acknowledgments
* [Ilastik Software](https://www.ilastik.org) : An interactive interface to annotate images to segment.
<!----------------------------------------------------------------------->
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!----------------------------------------------------------------------->
<!-- MARKDOWN LINKS & IMAGES -->
[Python-badge]: https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54
[Python-url]: https://www.python.org
[OpenCV-badge]: https://img.shields.io/badge/opencv-%23white.svg?style=for-the-badge&logo=opencv&logoColor=white
[OpenCV-url]: https://opencv.org
[ShellScript-badge]: https://img.shields.io/badge/shell_script-%23121011.svg?style=for-the-badge&logo=gnu-bash&logoColor=white
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"description": "<!----------------------------------------------------------------------->\n<a name=\"readme-top\"></a>\n<!----------------------------------------------------------------------->\n\n<table width=\"100%\" style=\"border: none;\">\n <tr>\n <td align=\"left\" style=\"border: none;\"><b>LE GOURRIEREC Titouan</b></td>\n <td align=\"left\" style=\"border: none;\"></td>\n <td align=\"right\" style=\"border: none;\">\n <a href=\"https://www.linkedin.com/in/titouanlegourrierec\"><img src=\"https://img.shields.io/badge/linkedin-%230077B5.svg?style=for-the-badge&logo=linkedin&logoColor=white\" alt=\"LinkedIn\"></a>\n <a href=\"mailto:titouanlegourrier\u00e6ec@icloud.com\"><img src=\"https://img.shields.io/badge/email-%23339933.svg?style=for-the-badge&logo=mail.ru&logoColor=white\" alt=\"Mail\"></a>\n </td>\n </tr>\n</table>\n\n<!----------------------------------------------------------------------->\n<!----------------------------------------------------------------------->\n\n<!-- PROJECT LOGO -->\n<br />\n<div align=\"center\">\n <h3 align=\"center\">EasIlastik </h3>\n\n <p align=\"center\">\n A package to facilitate the use of image segmentation model trained on Ilastik in Python\n <br />\n <a href=\"https://github.com/titouanlegourrierec/EasIlastik/wiki\"><strong>Explore the docs \u00bb</strong></a>\n <br />\n <a href=\"https://github.com/titouanlegourrierec/EasIlastik/issues\">Report a bug \u00b7 Request Feature</a>\n </p>\n <p align=\"center\">\n <a href=\"https://pypi.org/project/EasIlastik/\">\n <img src=\"https://img.shields.io/pypi/v/EasIlastik.svg\" alt=\"PyPI Version\">\n </a>\n </a>\n <a href=\"https://pepy.tech/project/EasIlastik\">\n <img src=\"https://pepy.tech/badge/EasIlastik\" alt=\"Downloads\">\n </a>\n <a href=\"https://github.com/psf/black\">\n <img src=\"https://img.shields.io/badge/code%20style-black-000000.svg\" alt=\"Code Style: Black\">\n </a>\n <a href=\"https://github.com/titouanlegourrierec/EasIlastik/blob/main/LICENSE\">\n <img src=\"https://img.shields.io/github/license/titouanlegourrierec/EasIlastik.svg\" alt=\"License\">\n </p>\n</div>\n\n\n\n<!-- TABLE OF CONTENTS -->\n<details>\n <summary>Table of Contents</summary>\n <ol>\n <li>\n <a href=\"#about-the-project\">About The Project \ud83d\udcd6</a>\n <ul>\n <li><a href=\"#built-with\">Built With \ud83d\udee0\ufe0f</a></li>\n </ul>\n </li>\n <li>\n <a href=\"#getting-started\">Getting Started</a>\n <ul>\n <li><a href=\"#prerequisites\">Prerequisites</a></li>\n </ul>\n </li>\n <li><a href=\"#usage\">Usage</a></li>\n <li><a href=\"#license\">License</a></li>\n <li><a href=\"#contact\">Contact</a></li>\n <li><a href=\"#acknowledgments\">Acknowledgments</a></li>\n </ol>\n</details>\n\n<!----------------------------------------------------------------------->\n<!----------------------------------------------------------------------->\n\n## About The Project\n\n<p align=\"center\">\n <img src=\"https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/img.png\" width=\"100%\">\n</p>\n\nThis package provides seamless integration of pre-trained image segmentation models from Ilastik into Python workflows, empowering users with efficient and intuitive image segmentation capabilities for diverse applications.\n\n<!----------------------------------------------------------------------->\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\n<!----------------------------------------------------------------------->\n\n\n### Built With\n* [![Python][Python-badge]][Python-url]\n* [![OpenCV][OpenCV-badge]][OpenCV-url]\n* ![Shell Script][ShellScript-badge]\n\n\n<!----------------------------------------------------------------------->\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\n<!----------------------------------------------------------------------->\n\n## Getting Started\n### Prerequisites \n\n* **Ilastik software**: To train your own model for image segmentation, please download the Ilastik software tailored to your computer's operating system from: https://www.ilastik.org/download.\n\n### Train a model\n\n* To train your own model on Ilastik and properly adjust the different parameters, please refer to [this documentation](https://github.com/titouanlegourrierec/EasIlastik/wiki/Train-a-model-on-Ilastik).\n\n\n\n\n<!----------------------------------------------------------------------->\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\n<!----------------------------------------------------------------------->\n\n\n## Usage\n\nFor usage examples of this package, please refer to the [Example Notebook](https://github.com/titouanlegourrierec/EasIlastik/blob/1be43ebb76bccec6917e05367fbb7e48b184efdc/Examples/example-notebook.ipynb).\n\n### Process a single image\n```python\nEasIlastik.run_ilastik(input_path = \"path/to/your/image.jpg\", # The path of the image to process\n model_path = \"path/to/your/model.ilp\",\n result_base_path = \"path/to/your/output/folder/\",\n export_source = \"Simple Segmentation\",\n output_format = \"png\")\n```\n<p align=\"center\">\n <img src=\"https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_image.png\" alt=\"run_ilastik_image\" width=\"50%\">\n</p>\n\n### Process a folder of images\n```python\nEasIlastik.run_ilastik(input_path = \"path/to/input/folder\", # The path of the folder to process\n model_path = \"path/to/your/model.ilp\",\n result_base_path = \"path/to/your/output/folder/\",\n export_source = \"Simple Segmentation\",\n output_format = \"png\")\n```\n<p align=\"center\">\n <img src=\"https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_folder.png\" alt=\"run_ilastik_folder\" width=\"70%\">\n</p>\n\n### Show probabilities\n```python\nEasIlastik.run_ilastik(input_path = \"path/to/input/image\",\n model_path = \"path/to/model.ilp\",\n result_base_path = \"path/to/output/folder\",\n export_source=\"Probabilities\", # Probabilities\n output_format=\"hdf5\") # hdf5 format\n\noutput_path = \"path/to/output/image.h5\"\nimage = EasIlastik.color_treshold_probabilities(output_path, threshold, below_threshold_color, channel_colors)\n```\n<p align=\"center\">\n <img src=\"https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_show_probabilities.png\" alt=\"run_ilastik_probabilities\" width=\"70%\">\n</p>\n\n### Run with probabilities\n```python\nEasIlastik.run_ilastik_probabilities(input_path = \"path/to/input/folder\",\n model_path = \"path/to/model.ilp\",\n result_base_path = \"path/to/output/folder\",\n threshold = 70, # threshold for the probabilities\n below_threshold_color = [255, 0, 0], # color for the pixels below the threshold (red)\n channel_colors = [[63, 63, 63], [127, 127, 127], ...] # colors for the different channels\n )\n```\n<p align=\"center\">\n <img src=\"https://raw.githubusercontent.com/titouanlegourrierec/EasIlastik/main/assets/run_ilastik_run_probabilities.png\" alt=\"run_ilastik_probabilities\" width=\"70%\">\n</p>\n\n\n<!----------------------------------------------------------------------->\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\n<!----------------------------------------------------------------------->\n\n\n\n<!-- ROADMAP -->\n<!-- ## Roadmap\n\n- [x] Add Changelog\n- [x] Add back to top links\n- [ ] Add Additional Templates w/ Examples\n- [ ] Add \"components\" document to easily copy & paste sections of the readme\n- [ ] Multi-language Support\n - [ ] Chinese\n - [ ] Spanish\n\nSee the [open issues](https://github.com/othneildrew/Best-README-Template/issues) for a full list of proposed features (and known issues).\n\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p> -->\n\n\n\n<!-- CONTRIBUTING -->\n<!-- ## Contributing\n\nContributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.\n\nIf you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag \"enhancement\".\nDon't forget to give the project a star! Thanks again!\n\n1. Fork the Project\n2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)\n3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)\n4. Push to the Branch (`git push origin feature/AmazingFeature`)\n5. Open a Pull Request\n\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p> -->\n\n\n## License\n\nDistributed under the GNU License like the Ilastik software. See [`LICENSE`](https://github.com/titouanlegourrierec/EasIlastik/blob/1be43ebb76bccec6917e05367fbb7e48b184efdc/LICENCE) for more information.\n\n<!----------------------------------------------------------------------->\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\n<!----------------------------------------------------------------------->\n\n## Contact\n\nLE GOURRIEREC Titouan - [titouanlegourrierec@icloud.com](mailto:titouanlegourrierec@icloud.com)\n\nRepository Link: [https://github.com/titouanlegourrierec/EasIlastik](https://github.com/titouanlegourrierec/EasIlastik) \nPypi Link : [https://pypi.org/project/EasIlastik/](https://pypi.org/project/EasIlastik/)\n\n\n<!----------------------------------------------------------------------->\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\n<!----------------------------------------------------------------------->\n\n\n## Acknowledgments\n\n* [Ilastik Software](https://www.ilastik.org) : An interactive interface to annotate images to segment.\n\n<!----------------------------------------------------------------------->\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\n<!----------------------------------------------------------------------->\n\n\n\n<!-- MARKDOWN LINKS & IMAGES -->\n\n\n[Python-badge]: https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54\n[Python-url]: https://www.python.org\n\n[OpenCV-badge]: https://img.shields.io/badge/opencv-%23white.svg?style=for-the-badge&logo=opencv&logoColor=white\n[OpenCV-url]: https://opencv.org\n\n[ShellScript-badge]: https://img.shields.io/badge/shell_script-%23121011.svg?style=for-the-badge&logo=gnu-bash&logoColor=white\n",
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