{"id":22132030,"url":"https://github.com/phanakata/art_identification_using_cnn","last_synced_at":"2026-04-16T12:02:06.798Z","repository":{"id":124135610,"uuid":"161371422","full_name":"phanakata/art_identification_using_CNN","owner":"phanakata","description":"Python package to indentify art painting with convolutional neural networks","archived":false,"fork":false,"pushed_at":"2018-12-18T18:27:49.000Z","size":31381,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-07-19T17:33:16.848Z","etag":null,"topics":["convolutional-neural-networks","indentifying-arts","tensorflow","tensorflow-models"],"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/phanakata.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":"2018-12-11T17:43:08.000Z","updated_at":"2022-04-13T12:19:00.000Z","dependencies_parsed_at":"2023-07-10T08:00:50.135Z","dependency_job_id":null,"html_url":"https://github.com/phanakata/art_identification_using_CNN","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/phanakata/art_identification_using_CNN","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phanakata%2Fart_identification_using_CNN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phanakata%2Fart_identification_using_CNN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phanakata%2Fart_identification_using_CNN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phanakata%2Fart_identification_using_CNN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/phanakata","download_url":"https://codeload.github.com/phanakata/art_identification_using_CNN/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phanakata%2Fart_identification_using_CNN/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31884929,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-16T11:36:10.202Z","status":"ssl_error","status_checked_at":"2026-04-16T11:36:09.652Z","response_time":69,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["convolutional-neural-networks","indentifying-arts","tensorflow","tensorflow-models"],"created_at":"2024-12-01T18:38:59.975Z","updated_at":"2026-04-16T12:02:06.771Z","avatar_url":"https://github.com/phanakata.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# art_identifcation_using_CNN\nCodes for identifying arts using convolutional neural networks (CNN). In this package we provide codes for preprocessing purposes such as, resizing images and relabeling data, and CNN models implemented in TensorFlow. \n\n## Data\nWe used art paintings provided Painter by Numbers competionKaggle competion https://www.kaggle.com/c/painter-by-numbers/data. \n\n\n## General usage\n1. The helper functions can be found in `tools/`\n2. A simple jupyter notebook to preprocess images and generate binary numpy files is  avalaible in `data/convert_images_to_numpy.ipynb`\n3. A simple jupyter notebook to perform classification with TensorFlow is avalaible in `models/CNN_VGGNet_for_classification.ipynb` \n\nThis package is still under development and more features will be added. \n\n## Authors:\nPaul Hanakata, Owen Howell, Varun Ursekar\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fphanakata%2Fart_identification_using_cnn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fphanakata%2Fart_identification_using_cnn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fphanakata%2Fart_identification_using_cnn/lists"}