{"id":24493016,"url":"https://github.com/fastmachinelearning/ml4fg","last_synced_at":"2025-04-14T01:40:32.197Z","repository":{"id":221242614,"uuid":"717857774","full_name":"fastmachinelearning/ml4fg","owner":"fastmachinelearning","description":"Machine Learning on frame grabbers for ultra-low latency in situ inference","archived":false,"fork":false,"pushed_at":"2024-11-15T22:18:30.000Z","size":190453,"stargazers_count":5,"open_issues_count":0,"forks_count":4,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-03-27T15:52:14.962Z","etag":null,"topics":["dl","dnn","fpga","hls","imaging","inference","machine-learning","ml","vivado","vivado-hls"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/fastmachinelearning.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2023-11-12T20:13:08.000Z","updated_at":"2024-11-15T22:25:55.000Z","dependencies_parsed_at":"2024-09-17T19:17:23.836Z","dependency_job_id":"682bf3fa-88e2-4289-9964-a70f99097b90","html_url":"https://github.com/fastmachinelearning/ml4fg","commit_stats":null,"previous_names":["m3-learning/hls4ml-frame-grabbers","fastmachinelearning/hls4ml-frame-grabbers"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fml4fg","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fml4fg/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fml4fg/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fml4fg/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fastmachinelearning","download_url":"https://codeload.github.com/fastmachinelearning/ml4fg/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248809039,"owners_count":21164893,"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":["dl","dnn","fpga","hls","imaging","inference","machine-learning","ml","vivado","vivado-hls"],"created_at":"2025-01-21T19:18:53.790Z","updated_at":"2025-04-14T01:40:32.179Z","avatar_url":"https://github.com/fastmachinelearning.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n   \u003cimg src=\"logos/ml4fg_logo_color.svg\" alt=\"ml4fg\" width=\"400\"/\u003e\n\u003c/p\u003e\n\n# Machine Learning for Frame Grabbers\n\n### Getting Started\n\nA tutorial and reference design for machine learning inference on FPGA-based frame grabber devices in high-throughput imaging applications. This tutorial leverages the hls4ml package and the CustomLogic toolkit to deploy neural networks to Euresys frame grabber devices. Refer to ```hls4ml-frame-grabber-tutorial.ipynb``` to get started. See ```part9_FOLO_frame_grabbers_advanced_features.ipynb``` for a more advanced guide on implementing a YOLO-style model and taking advantage of the suite of optimizations hls4ml provides.\n\n\nTo install ```hls4ml_frame_grabber``` conda environment\n\n- ```conda env create -f environment.yml```\n\n- ```conda activate hls4ml_frame_grabber```\n\n- ```ipython kernel install --user --name=hls4ml_frame_grabber```\n\n### Medium article\n\nWe have also released ```hls4ml-frame-grabber-tutorial.ipynb``` in a medium article format which can be found [here](https://medium.com/@forelliryan/deploying-neural-networks-for-in-situ-inference-on-frame-grabber-fpgas-in-high-speed-imaging-6201557fdabc).\n\n\n### Acknowledgement\n\nPrimary development was completed by Fermi National Accelerator Laboratory, Northwestern University, and Drexel University. This work resulted from the implementation described in this paper: https://arxiv.org/abs/2312.00128. Deepest thanks to Euresys and the Columbia University HBT-EP group for their assistance and contribution to this development.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffastmachinelearning%2Fml4fg","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffastmachinelearning%2Fml4fg","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffastmachinelearning%2Fml4fg/lists"}