{"id":18614567,"url":"https://github.com/minar09/dataset-cfpd-windows","last_synced_at":"2025-08-31T20:12:09.207Z","repository":{"id":67769906,"uuid":"163599598","full_name":"minar09/dataset-CFPD-windows","owner":"minar09","description":"CFPD | Colorful Fashion Parsing Data for Windows OS","archived":false,"fork":false,"pushed_at":"2020-05-24T15:41:02.000Z","size":460,"stargazers_count":8,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-07-07T19:21:23.162Z","etag":null,"topics":["cfpd","clothing-parsing","colorful-fashion","dataset","fashion-dataset","fashion-parsing","windows"],"latest_commit_sha":null,"homepage":"https://github.com/hrsma2i/dataset-CFPD","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/minar09.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":"2018-12-30T16:01:18.000Z","updated_at":"2024-04-01T10:00:28.000Z","dependencies_parsed_at":null,"dependency_job_id":"3602b5bd-a3ce-4c67-ae0f-86b944978c0b","html_url":"https://github.com/minar09/dataset-CFPD-windows","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/minar09/dataset-CFPD-windows","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minar09%2Fdataset-CFPD-windows","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minar09%2Fdataset-CFPD-windows/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minar09%2Fdataset-CFPD-windows/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minar09%2Fdataset-CFPD-windows/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/minar09","download_url":"https://codeload.github.com/minar09/dataset-CFPD-windows/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minar09%2Fdataset-CFPD-windows/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273032934,"owners_count":25034067,"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","status":"online","status_checked_at":"2025-08-31T02:00:09.071Z","response_time":79,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["cfpd","clothing-parsing","colorful-fashion","dataset","fashion-dataset","fashion-parsing","windows"],"created_at":"2024-11-07T03:26:04.095Z","updated_at":"2025-08-31T20:12:09.191Z","avatar_url":"https://github.com/minar09.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Disclaimer\nThis is a modified repository from [dataset-CFPD](https://github.com/hrsma2i/dataset-CFPD). Please refer to the original repository for more details.\n\n# CFPD | Colorful Fashion Parsing Data\n\nThis dataset is used in the paper, [(S. Liu, J. Feng, C. Domokos, H. Xu, J. Huang, Z. Hu, \u0026 S. Yan. 2014) CFPD | Fashion parsing with weak color-category labels.](https://sites.google.com/site/fashionparsing/home)\n\n## Details\n\n- 2,682 images\n- 600 x 400 (height, width)\n- pixel-level annotated (segmentation map)\n\t- 23 categories\n\t- 13 **colors**\n- `make_label.py` makes the followings from `fashon_parsing_data.mat`.\n\t- `label/bbox.json`: **bounding box** (for object detection not semantic segmentation).\n\t- `label/categories.tsv`\n\t\t- `category_id`\n\t\t- `category`\n- `label/main_categories.tsv` is selected from `categories.tsv` for object detection.\n\n## Setup Dataset\n\n```\n1. install the requirements\npip install -r requirements.txt\n\n2. download zip file (name) from author's GoogleDrive\ndownload.sh\n\n3. rename \"data\" file manually to \"data.zip\" or run the command below:\nrename data data.zip\n\n4. unzip data.zip manually or follow instructions from here (http://stahlworks.com/dev/index.php?tool=zipunzip) to unzip from cmd\n\n5. make label/categories.tsv, label/bbox.json from fashon_parsing_data.mat\npython make_label.py\n\n6. Convert .mat to hdf5(.h5), run convert_tmm_to_hdf5.m with matlab\n\n7. Convert .hdf5 files into images with annotations and lists\npython export.py\n```\n\n## fashon_parsing_data.mat\n\n### structure\n\n- #refs#\n\t- 0, 0A~zz: 2,719 groups (each record may be a image info)\n\t\t- category_label\n\t\t\t- np.array, float64(actually int), (1, 425)\n\t\t\t- map: super-pix id (1~425) -\u003e fine category id (1~117)\n\t\t- color_label\n\t\t\t- np.array, float64(actually int), (1,425)\n\t\t\t- map: super-pix id (1~425) -\u003e fine color id (1~60)\n\t\t- ?img_name\n\t\t\t- np.array, uint16, (2~9 etc, 1)\n\t\t\t- range: 59~108 etc\n\t\t\t- ???\n\t\t- segmentation\n\t\t\t- np.array, float32, (400, 600)\n\t\t\t- map: img pix loc (w, h) -\u003e super-pix id (1~425)\n\t\t\t- (height, width) (transposing this) is the right orientation.\n\t- b~x: 23 datasets (each record means category id)\n\t\t- np.array, uint16, (1, #fine_category)\n\t\t- range: 1~117\n\t\t- fine categories's ids under the cateogry.\n\t- y,z,A~K: 13 datasets (each record means color id)\n\t\t- np.array, uint16, (1, #fine_color)\n\t\t- range: 1~60\n\t\t- fine color's ids under the color.\n- all_category_name\n\t- np.array, h5py.h5r.Reference, (1, 23)\n\t- Each reference correspods the above cateogory keys under #refs#.\n- all_color_name \n\t- np.array, h5py.h5r.Reference, (1, 13)\n\t- Each reference correspods the above color keys under #refs#.\n\n\n## Dataset Problem\n\n- Mentioned in this paper's Figure 7, [(P. Tangseng, Z. Wu, \u0026 K. Yamaguchi. 2017) Looking at Outfit to Parse Clothing.](https://arxiv.org/pdf/1703.01386.pdf).\n- [This repository](https://github.com/hrsma2i/fashion-parsing/tree/master/data/tmm_dataset_sharing) is the code of the above paper. This code deals with CFPD.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminar09%2Fdataset-cfpd-windows","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fminar09%2Fdataset-cfpd-windows","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminar09%2Fdataset-cfpd-windows/lists"}