{"id":17596218,"url":"https://github.com/lamm-mit/dyfranet","last_synced_at":"2025-04-30T04:51:01.433Z","repository":{"id":153541492,"uuid":"533312415","full_name":"lamm-mit/DyFraNet","owner":"lamm-mit","description":null,"archived":false,"fork":false,"pushed_at":"2022-11-15T20:12:07.000Z","size":5030,"stargazers_count":7,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-30T12:41:41.520Z","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/lamm-mit.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","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":"2022-09-06T12:26:44.000Z","updated_at":"2025-01-18T16:32:15.000Z","dependencies_parsed_at":null,"dependency_job_id":"fd608deb-8502-4e8b-9f04-fd46b1c6e12e","html_url":"https://github.com/lamm-mit/DyFraNet","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/lamm-mit%2FDyFraNet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lamm-mit%2FDyFraNet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lamm-mit%2FDyFraNet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lamm-mit%2FDyFraNet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lamm-mit","download_url":"https://codeload.github.com/lamm-mit/DyFraNet/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251644827,"owners_count":21620630,"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":"2024-10-22T08:24:24.567Z","updated_at":"2025-04-30T04:51:01.406Z","avatar_url":"https://github.com/lamm-mit.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DyFraNet\n\n![image](https://user-images.githubusercontent.com/101393859/202016081-178b33cc-6034-41b0-b656-83b56ae0ce83.png)\n\nReference: Yu-Chuan Hsu, Markus J. Buehler, DyFraNet: Forecasting and Backcasting Dynamic Fracture Mechanics in Space and Time Using a 2D-to-3D Deep Neural Network, in submission \n\n#### If you are using our dataset $immatrix\\\\_2D.npy$, you can simply run the python code to train the model by:\npython3 main.py --batch_size 32 \n\n#### If you are using your own dataset, you might need to specify the number of frames, $N$, for the input to train the model by:\npython3 main.py --batch_size 32\n                --numframe N\n\n#### To download our pre-trained model, please download and unzip it to the currnet folder from the link below:\n\nhttps://www.dropbox.com/s/9phk9osmzzpbh66/model.zip?dl=0\n\n#### and then run $prediction.ipynb$ to explore the model with your own input.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flamm-mit%2Fdyfranet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flamm-mit%2Fdyfranet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flamm-mit%2Fdyfranet/lists"}