{"id":24001801,"url":"https://github.com/laknath1996/deepphaseunwrap","last_synced_at":"2025-04-14T23:10:23.221Z","repository":{"id":129505804,"uuid":"373395816","full_name":"Laknath1996/DeepPhaseUnwrap","owner":"Laknath1996","description":"This repository Introduces a joint convolutional and spatial quad-directional LSTM (SQD-LSTM) network for phase unwrapping in 2D images (ICASSP 2021)","archived":false,"fork":false,"pushed_at":"2024-10-31T21:59:47.000Z","size":15729,"stargazers_count":41,"open_issues_count":3,"forks_count":5,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-28T11:11:32.967Z","etag":null,"topics":["cnn","deep-learning","lstm","phase-unwrapping"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Laknath1996.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-06-03T05:51:32.000Z","updated_at":"2025-02-21T06:40:56.000Z","dependencies_parsed_at":"2023-03-13T11:21:54.615Z","dependency_job_id":null,"html_url":"https://github.com/Laknath1996/DeepPhaseUnwrap","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Laknath1996%2FDeepPhaseUnwrap","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Laknath1996%2FDeepPhaseUnwrap/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Laknath1996%2FDeepPhaseUnwrap/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Laknath1996%2FDeepPhaseUnwrap/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Laknath1996","download_url":"https://codeload.github.com/Laknath1996/DeepPhaseUnwrap/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248975316,"owners_count":21192210,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cnn","deep-learning","lstm","phase-unwrapping"],"created_at":"2025-01-08T00:38:20.040Z","updated_at":"2025-04-14T23:10:23.214Z","avatar_url":"https://github.com/Laknath1996.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"A Joint Convolutional and Space Quad-Directional LSTM Network for Phase Unwrapping\n==============================\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/Laknath1996/DeepPhaseUnwrap/blob/main/reports/figures/summary.jpg\"\u003e\n\u003c/p\u003e\n\n[![Conference](https://img.shields.io/badge/Conference-ICASSP%202021-brightgreen)](https://2021.ieeeicassp.org/) [![Paper](https://img.shields.io/badge/Paper-IEEEXplore-blue)](https://ieeexplore.ieee.org/document/9414748)\n\nThis repository contains the source code for the deep neural arcihetcure proposed by the ICASSP 2021 paper titled [\"A Joint Convolutional and Space Quad-Directional LSTM Network for Phase Unwrapping\"](https://ieeexplore.ieee.org/document/9414748). \n\nIf you use this code/paper for your research, please consider citing,\n\n```\n@INPROCEEDINGS{9414748,  \nauthor={Perera, Malsha V. and De Silva, Ashwin},  \nbooktitle={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},   \ntitle={A Joint Convolutional and Spatial Quad-Directional LSTM Network for Phase Unwrapping},   \nyear={2021},  \nvolume={},  \nnumber={},  \npages={4055-4059},  \ndoi={10.1109/ICASSP39728.2021.9414748}}\n```\n\nProject Organization\n------------\n\n    ├── LICENSE\n    ├── README.md          \u003c- The top-level README for developers using this project.\n    ├── data               \u003c- Datasets created/ used by the project   \n    ├── models             \u003c- Trained and serialized models\n    │\n    ├── notebooks          \u003c- A tutorial on the project \n    │\n    ├── reports            \n    │   └── figures        \u003c- Generated graphics and figures\n    ├── requirements.txt   \u003c- The requirements file for reproducing the analysis environment\n    │\n    ├── src                \u003c- Source code for use in this project.\n    │   ├── __init__.py    \u003c- Makes src a Python module\n    │   │\n    │   ├── data           \u003c- Scripts to generate data\n    │   ├── models         \u003c- Scripts to define models and losses.\n    |   └── visualization  \u003c- Scripts to create plots\n    ├── create_synthetic_phase_dataset.py \u003c- Create datasets\n    ├── train_model.py                    \u003c- Train models\n    └── test_model.py                     \u003c- Test models\n--------\n\n## Installation Guide\n\n### Step 1 : Clone the Repository\n\nClone the repository using the following command.\n\n````\n$ git clone https://github.com/Laknath1996/DeepPhaseUnwrap.git\n````\n\n### Step 2 : Install Dependencies\n\nUse the `requirements.txt` file given in the repository to install the dependencies via `pip`.\n\n````\n$ pip install -r requirements.txt \n````\n\n### Step 3 : Install Dependencies\n\nUse the `create_synthetic_phase_dataset.py`, `train_model.py` and `test_model.py` files to create phase datasets, train models, and validate them, respectively.          \n\n## Tutorial\n\n`notebooks/tutorial.ipynb` describes the specifics and the execution steps of the network. \n\n## Authors\n\n* **Ashwin De Silva** - ashwindesilva@yahoo.com\n* **Malsha Perera** - malshaperera14@gmail.com\n\nAt the time of this work, both the authors were with the Department of Electronics and Telecommunication Engineering, University of Moratuwa, Sri Lanka. Feel free to contact the authors regarding this work.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details\n\n## Acknowledgments\n\n* Biomedical Engineering Laboratory, Dept. of Electronic and Telecommunication Eng., University of Moratuwa, Sri Lanka.\n\n## References\n\n[1] M. V. Perera and A. De Silva, \"A Joint Convolutional and Spatial Quad-Directional LSTM Network for Phase Unwrapping,\" ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 4055-4059, doi: 10.1109/ICASSP39728.2021.9414748.\n\n\u003cp\u003e\u003csmall\u003eProject based on the \u003ca target=\"_blank\" href=\"https://drivendata.github.io/cookiecutter-data-science/\"\u003ecookiecutter data science project template\u003c/a\u003e. #cookiecutterdatascience\u003c/small\u003e\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flaknath1996%2Fdeepphaseunwrap","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flaknath1996%2Fdeepphaseunwrap","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flaknath1996%2Fdeepphaseunwrap/lists"}