{"id":15195551,"url":"https://github.com/ugnelis/find-path","last_synced_at":"2025-10-02T11:31:16.051Z","repository":{"id":164098974,"uuid":"73490190","full_name":"ugnelis/find-path","owner":"ugnelis","description":"Find path by using Semantic Segmentation.","archived":true,"fork":false,"pushed_at":"2017-09-26T17:21:48.000Z","size":4224,"stargazers_count":10,"open_issues_count":0,"forks_count":5,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-17T01:12:17.362Z","etag":null,"topics":["dataset","dataset-maker","fcn-16s","ipynb","semantic-segmentation","tensorflow","vgg16"],"latest_commit_sha":null,"homepage":"","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/ugnelis.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":"2016-11-11T15:46:06.000Z","updated_at":"2023-01-28T05:05:25.000Z","dependencies_parsed_at":"2023-07-24T02:50:34.416Z","dependency_job_id":null,"html_url":"https://github.com/ugnelis/find-path","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/ugnelis%2Ffind-path","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ugnelis%2Ffind-path/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ugnelis%2Ffind-path/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ugnelis%2Ffind-path/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ugnelis","download_url":"https://codeload.github.com/ugnelis/find-path/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234983162,"owners_count":18917425,"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":["dataset","dataset-maker","fcn-16s","ipynb","semantic-segmentation","tensorflow","vgg16"],"created_at":"2024-09-27T23:41:17.705Z","updated_at":"2025-10-02T11:31:15.723Z","avatar_url":"https://github.com/ugnelis.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# find-path\nFind Path project finds humans paths and routes, such as sidewalks, park ways, forest paths. This project implements semantic segmentation approach. It uses VGG16 pretrained model.\n\n[![Semantic Segmentation - Ugnius Malūkas](https://img.youtube.com/vi/jTj_mzeoVm0/0.jpg)](https://www.youtube.com/watch?v=jTj_mzeoVm0)\n\n## Path Finding \n### Installation \nTODO\n\n### Training\nGo to *calculations* folder.\n```bash\n$ cd calculations\n```\nRun training.\n```bash\n$ python train.py\n```\n### Run Trained Model\nCheck for examples in *calculations/demo.py*, *calculations/demo.ipynb*, *calclulations/video_demo.ipynb* files.\n\n## Dataset Maker\nFor making dataset, web based application was made which uses just JavaScript without any framework.\n\n### Installation\nBefore installation, make sure that NodeJS, npm and bower are installed.\n```bash\n$ cd dataset_maker\n$ bower install\n```\n\n### Launching\nOpen *index.html* and have fun.\n\n## Dataset\nAll dataset images have 320 width, 180 height and contain 3 channels. Every image has own *.json* file which describes object in the image. In this project only 3 classes are observed: **boundaries** (everything arround path), **paths / ways** and **obstacles** (things that are on path - eg. human, road pit and etc.). Dataset contains 300 images (I'll put a bit later).\n\n## Path Finding with OpenCV\nCheck *calculations/cv/* folder.\n\n## Code References\nhttps://github.com/MarvinTeichmann/tensorflow-fcn\nhttps://github.com/shelhamer/fcn.berkeleyvision.org\nhttps://github.com/machrisaa/tensorflow-vgg\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fugnelis%2Ffind-path","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fugnelis%2Ffind-path","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fugnelis%2Ffind-path/lists"}