{"id":15681439,"url":"https://github.com/angusg/truth-and-crop","last_synced_at":"2025-05-07T12:13:23.861Z","repository":{"id":87480069,"uuid":"79165153","full_name":"AngusG/truth-and-crop","owner":"AngusG","description":"Application for ground-truthing semantic segmentation datasets in PyQt4/OpenCV. ","archived":false,"fork":false,"pushed_at":"2017-08-15T17:54:01.000Z","size":5808,"stargazers_count":11,"open_issues_count":0,"forks_count":3,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-05-07T12:13:18.951Z","etag":null,"topics":["crop","labeled-data","labelme","machine-learning","opencv","pyqt4"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AngusG.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":"2017-01-16T22:24:10.000Z","updated_at":"2024-03-28T01:04:10.000Z","dependencies_parsed_at":null,"dependency_job_id":"10c94211-5774-4943-a620-ddab7a47e384","html_url":"https://github.com/AngusG/truth-and-crop","commit_stats":null,"previous_names":[],"tags_count":14,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AngusG%2Ftruth-and-crop","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AngusG%2Ftruth-and-crop/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AngusG%2Ftruth-and-crop/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AngusG%2Ftruth-and-crop/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AngusG","download_url":"https://codeload.github.com/AngusG/truth-and-crop/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252873889,"owners_count":21817715,"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":["crop","labeled-data","labelme","machine-learning","opencv","pyqt4"],"created_at":"2024-10-03T16:54:42.079Z","updated_at":"2025-05-07T12:13:23.842Z","avatar_url":"https://github.com/AngusG.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# truth-and-crop\n\nConvenient GUI application for quickly ground-truthing semantic segmentation datasets in Python/OpenCV. Original dataset used with the tool can be downloaded from: https://dataverse.scholarsportal.info/dataset.xhtml?persistentId=doi:10.5683/SP/NTUOK9\n\n![sample](images/sample.png)\n\n### Dependencies\n\n+ `python 3.4`\n+ `pyqt 4.x`\n+ `opencv 3.x`\n+ `numpy 1.11.x`\n+ `colorama 0.3`\n+ `natsort=5.0.x`\n+ `scikit-image 0.12.x`\n\nIf using Anaconda, you can use the provided `environment.yml` file with `conda env create -f environment.yml`, which will create a virtual environment `tnc-py34`.\n\n### Usage\n\n```bash\nsource activate tnc-py34\npython truth_and_crop.py\n```\n\n### Buttons\n\n+ __Input File__ - Browse to image file to load.\n+ __Output Path__ - Browse to root folder where output should be saved. Three subfolders are automatically created here.\n+ __Previous/Next Image__ - If other images were found in same folder as Input File, you can jump between images with these buttons.\n+ __Refresh__ - Discards changes.\n+ __Crop__ - Switch between annotation mode and cropping mode.\n+ __Toggle__ - Toggle annotations on and off to make it easier to see raw image. SLIC is only run on the image for the first toggle, subsequent toggles are much faster.\n+ __Save__ - To write all cropped images and masks into appropriate subfolders under the path specified by 'Output Path'.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fangusg%2Ftruth-and-crop","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fangusg%2Ftruth-and-crop","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fangusg%2Ftruth-and-crop/lists"}