{"id":13654292,"url":"https://github.com/ualsg/Road-Network-Classification","last_synced_at":"2025-04-23T08:32:03.270Z","repository":{"id":113709549,"uuid":"363924185","full_name":"ualsg/Road-Network-Classification","owner":"ualsg","description":null,"archived":false,"fork":false,"pushed_at":"2024-05-16T11:23:44.000Z","size":22802,"stargazers_count":40,"open_issues_count":0,"forks_count":12,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-04-12T02:04:05.488Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/ualsg.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2021-05-03T12:35:48.000Z","updated_at":"2025-03-17T14:15:05.000Z","dependencies_parsed_at":null,"dependency_job_id":"37ce6157-f0e4-4b98-87c7-b3dd3b27a607","html_url":"https://github.com/ualsg/Road-Network-Classification","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/ualsg%2FRoad-Network-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ualsg%2FRoad-Network-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ualsg%2FRoad-Network-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ualsg%2FRoad-Network-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ualsg","download_url":"https://codeload.github.com/ualsg/Road-Network-Classification/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250399525,"owners_count":21424197,"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":[],"created_at":"2024-08-02T02:01:26.605Z","updated_at":"2025-04-23T08:31:58.255Z","avatar_url":"https://github.com/ualsg.png","language":"Jupyter Notebook","readme":"\n# Classification of Urban Morphology with Deep Learning: Application on Urban Vitality\n\n![Graphical Abstract](./grabs.jpg)\n\nThis repository is the official implementation of [Classification of Urban Morphology with Deep Learning: Application on Urban Vitality](https://www.sciencedirect.com/science/article/abs/pii/S0198971521001137). It includes the major codes (written in Python) involved in the paper. We also offer some tractable tutorials in Notebook to show how to use our two modules, `CRHD generator` and `Morphoindex generator`. `CRHD generator` can automatically produce Colored Road Hierarchy Diagram (CRHD) for a given urban area. `Morphoindex generator` can automatically generate both traditional morphological indices based on built environment Shapefiles and road network class probabilities based on our road network classification model.\n\n## Requirements\n\nTo use `CRHD generator`, you need to install the requirements:\n\n```setup\npip install osmnx\npip install geopandas\npip install matplotlib\n```\nTo use `Morphoindex generator`, you need to install the additional requirements:\n\n```setup\npip install tensorflow\npip install keras\npip install cv2\npip install numpy\n```\nIf you want to use our Morphoindex generator to calculate road network class probabilities, you should also download `config.py`, `MODEL.py` and `Build_model.py` togehther with `morphoindex_generator.py`, and put them in the same filepath. Also, make sure you have downloaded our pretrained model which you can find below.\n\n## Tutorials\nTo let you quickly understand how to use our tools, we prepared some easy tutorials for you to have a glance:\n\n[CRHD generator tutorial](https://github.com/ualsg/Road-Network-Classification/blob/main/tutorials/crhd_generator_tutorial.ipynb)\n\n[Morphoindex generator tutorial](https://github.com/ualsg/Road-Network-Classification/blob/main/tutorials/mophoindex_generator_tutorial.ipynb)\n\n## Pre-trained Model\n\nYou can download our pretrained models here:\n\n- [Road network classification model](https://drive.google.com/file/d/1N7T9lN4TL5r8EqduZfWv22ROZO4zp_FN/view?usp=sharing) trained on our labelled image set using ResNet-34 architecture, learning rate as 0.0005, batch size as 2. \n\n\n## Results\n\nOur model achieves the following performance on the testing set:\n\n**Confusion matrix and ROC curves:**\n\n![image](https://github.com/ualsg/Road-Network-Classification/blob/main/images/results.png)\n\n## Paper\n\nA [paper](https://doi.org/10.1016/j.compenvurbsys.2021.101706) about the work is available.\n\nIf you use this work in a scientific context, please cite this article.\n\nChen W, Wu AN, Biljecki F (2021): Classification of Urban Morphology with Deep Learning: Application on Urban Vitality. Computers, Environment and Urban Systems 90: 101706.\n\n```\n@article{2021_ceus_dl_morphology,\n  author = {Wangyang Chen and Abraham Noah Wu and Filip Biljecki},\n  doi = {10.1016/j.compenvurbsys.2021.101706},\n  journal = {Computers, Environment and Urban Systems},\n  pages = {101706},\n  title = {Classification of Urban Morphology with Deep Learning: Application on Urban Vitality},\n  url = {https://doi.org/10.1016/j.compenvurbsys.2021.101706},\n  volume = {90},\n  year = 2021\n}\n```\n\n## Contact\n\n[Chen Wangyang](https://ual.sg/authors/wangyang/), [Urban Analytics Lab](https://ual.sg), National University of Singapore, Singapore\n\n","funding_links":[],"categories":["awesome-open-transport"],"sub_categories":["7. 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