{"id":33252522,"url":"https://github.com/zzhanghub/eval-co-sod","last_synced_at":"2025-11-21T18:02:01.610Z","repository":{"id":106691606,"uuid":"284910271","full_name":"zzhanghub/eval-co-sod","owner":"zzhanghub","description":"PyTorch-Based Evaluation Tool for Co-Saliency Detection","archived":false,"fork":false,"pushed_at":"2020-12-12T08:31:17.000Z","size":67,"stargazers_count":92,"open_issues_count":0,"forks_count":28,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-05-29T09:01:15.317Z","etag":null,"topics":["auc","average-precision","co-saliency","e-measure","evaluation","f-measure","mae","mean-absolute-error","pr-curve","python","pytorch","roc-curve","s-measure","salient-object-detection"],"latest_commit_sha":null,"homepage":"http://zhaozhang.net/coca.html","language":"Python","has_issues":false,"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/zzhanghub.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":"2020-08-04T07:35:01.000Z","updated_at":"2024-04-23T08:15:54.000Z","dependencies_parsed_at":null,"dependency_job_id":"d1d0a528-45b4-4b2d-8db0-f09a3c74898b","html_url":"https://github.com/zzhanghub/eval-co-sod","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/zzhanghub/eval-co-sod","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zzhanghub%2Feval-co-sod","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zzhanghub%2Feval-co-sod/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zzhanghub%2Feval-co-sod/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zzhanghub%2Feval-co-sod/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zzhanghub","download_url":"https://codeload.github.com/zzhanghub/eval-co-sod/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zzhanghub%2Feval-co-sod/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":285663883,"owners_count":27210636,"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":"2025-11-21T02:00:06.175Z","response_time":61,"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":["auc","average-precision","co-saliency","e-measure","evaluation","f-measure","mae","mean-absolute-error","pr-curve","python","pytorch","roc-curve","s-measure","salient-object-detection"],"created_at":"2025-11-17T00:00:46.078Z","updated_at":"2025-11-21T18:02:01.603Z","avatar_url":"https://github.com/zzhanghub.png","language":"Python","funding_links":[],"categories":["Saliency"],"sub_categories":["Co-Saliency"],"readme":"\u003c!-- PROJECT LOGO --\u003e\n\u003cbr /\u003e\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"http://zhaozhang.net/coca.html\"\u003e\n    \u003cimg src=\"img/eval_co-sod.png\" alt=\"Logo\" width=\"210\" height=\"100\"\u003e\n  \u003c/a\u003e\n\n  \u003ch3 align=\"center\"\u003ePyTorch-Based Evaluation Tool for Co-Saliency Detection\u003c/h3\u003e\n\n  \u003cp align=\"center\"\u003e\n    Automatically evaluate 8 metrics and draw 4 types of curves\n    \u003cbr /\u003e\n    \u003ca href=\"http://zhaozhang.net/coca.html\"\u003e\u003cstrong\u003e⭐ Project Home »\u003c/strong\u003e\u003c/a\u003e\n    \u003cbr /\u003e\n  \u003c/p\u003e\n\u003c/p\u003e\n\n\n***\n**Eval Co-SOD** is an extended version of [Evaluate-SOD](https://github.com/Hanqer/Evaluate-SOD) for **co-saliency detection task**.\nIt provides eight metrics and four curves:\n* Metrics:\n    * Mean Absolute Error (MAE)\n\t* Maximum F-measure (max-Fm)\n\t* Mean F-measure (mean-Fm)\n\t* Maximum E-measure (max-Em)\n\t* Mean E-measure (mean-Em)\n\t* S-measure (Sm)\n\t* Average Precision (AP)\n\t* Area Under Curve (AUC)\n* Curves:\n\t* Precision-Recall (PR) curve\n\t* Receiver Operating Characteristic (ROC) curve\n\t* F-measure curve\n\t* E-measure curve\n\n\n## Prerequisites\n* PyTorch \u003e= 1.0\n\n\n## Usage\n\n### 1. Prepare your data\nThe structure of `root_dir` should be organized as follows:\n```\n.\n├── gt\n│   ├── dataset1\n│   │   ├── accordion\n│   │   │   ├── 51499.png\n│   │   │   └── 186605.png\n│   │   └── alarm clock\n│   │       ├── 51499.png\n│   │       └── 186605.png\n│   ├── dataset2 ...\n│   └── dataset3 ...\n│ \n└── pred\n    └── method1\n    │   ├── dataset1\n    │   │   ├── accordion\n    │   │   │   ├── 51499.png\n    │   │   │   └── 186605.png\n    │   │   └── alarm clock\n    │   │       ├── 51499.png\n    │   │       └── 186605.png\n    │   ├── dataset2 ..\n    │   └── dataset3 ...\n    └──method2 ...\n```\n\n### 2. Evaluate on the 8 metrices\n1. Configure `eval.sh`\n```shell\n--methods method1+method2+method3 (Multiple items are connected with '+')\n--datasets dataset1+dataset2+dataset3\n--save_dir ./Result (Path to save results)\n--root_dir ../SalMaps\n```\n\n2. Run by\n```\nsh eval.sh\n```\n\n### 3. Draw the 4 types of curves\n1. Configure `plot_curve.sh`\n```shell\n--methods method1+method2+method3 (Multiple items are connected with '+')\n--datasets dataset1+dataset2+dataset3\n--out_dir ./Result/Curves (Path to save results)\n--res_dir ./Result/Detail\n```\n\n2. Run by\n```\nsh plot_curve.sh\n```\n\n## Citation\nIf you find this tool is useful for your research, please cite the following papers.\n```\n@inproceedings{zhang2020gicd,\n title={Gradient-Induced Co-Saliency Detection},\n author={Zhang, Zhao and Jin, Wenda and Xu, Jun and Cheng, Ming-Ming},\n booktitle={European Conference on Computer Vision (ECCV)},\n year={2020}\n}\n\n@inproceedings{fan2020taking,\n  title={Taking a Deeper Look at the Co-salient Object Detection}, \n  author={Fan, Deng-Ping and Lin, Zheng and Ji, Ge-Peng and Zhang, Dingwen and Fu, Huazhu and Cheng, Ming-Ming},   \n  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},\n  year={2020} \n} \n```\n\n## Contact\nIf you have any questions, feel free to contact me via `zzhang🥳mail😲nankai😲edu😲cn`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzzhanghub%2Feval-co-sod","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzzhanghub%2Feval-co-sod","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzzhanghub%2Feval-co-sod/lists"}