{"id":23146588,"url":"https://github.com/rcode879/handwritten-digit-detector","last_synced_at":"2026-05-19T10:35:07.748Z","repository":{"id":219811522,"uuid":"749997670","full_name":"Rcode879/Handwritten-digit-detector","owner":"Rcode879","description":"A school machine learning project based on the Knearest neighbours model","archived":false,"fork":false,"pushed_at":"2024-01-30T13:22:16.000Z","size":2784,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-03T23:37:46.443Z","etag":null,"topics":["csv-files","knearest-neighbor-algorithm","knearest-neighbor-classification","knearest-neighbor-classifier","machine-learning","opencv","python3","tkinter","tkinter-gui"],"latest_commit_sha":null,"homepage":"","language":"Python","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/Rcode879.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":"2024-01-29T19:47:13.000Z","updated_at":"2024-11-27T19:56:26.000Z","dependencies_parsed_at":"2024-12-17T16:31:33.944Z","dependency_job_id":"a5f657ba-3f21-47d6-b852-965d4e56e9a9","html_url":"https://github.com/Rcode879/Handwritten-digit-detector","commit_stats":null,"previous_names":["rcode879/handwritten-digit-detector"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Rcode879/Handwritten-digit-detector","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rcode879%2FHandwritten-digit-detector","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rcode879%2FHandwritten-digit-detector/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rcode879%2FHandwritten-digit-detector/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rcode879%2FHandwritten-digit-detector/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Rcode879","download_url":"https://codeload.github.com/Rcode879/Handwritten-digit-detector/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rcode879%2FHandwritten-digit-detector/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266854500,"owners_count":23995486,"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":"2025-07-24T02:00:09.469Z","response_time":99,"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":["csv-files","knearest-neighbor-algorithm","knearest-neighbor-classification","knearest-neighbor-classifier","machine-learning","opencv","python3","tkinter","tkinter-gui"],"created_at":"2024-12-17T16:31:14.468Z","updated_at":"2026-05-19T10:35:07.702Z","avatar_url":"https://github.com/Rcode879.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Handwritten-digit-detector\nA python program that trains a Knearest neighbours model on the MNIST data set(which is in the form of a CSV file) to recognise handwritten digits.\nImplemented into a TKinter GUI which had a button to train the model, a button to load in your own png file with a handwritten digit and a button to output the model accuracy.\n\n## Required packages: \n-CSV \n\n-Tkinter \n\n-OpenCV \n\n-Scikit.learn\n\n\n## Warning:\n- line 16 with variable named \"mnist_train.csv\", is the csv file file containing the mnist data set to train the model, the file was too large to upload to the repository\n- line 96 is the background image of the gui - \"gui.png\" - you can add your own peronal image by downloading one of your choice and renaming it\n- If you wish to test your own image(png), it must be 28 by 28 pixels with a black background and the number written in white\n- This model is NOT the most accurate and would most likely be more accurate in a neural network so do not expect perfect predicitons\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frcode879%2Fhandwritten-digit-detector","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frcode879%2Fhandwritten-digit-detector","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frcode879%2Fhandwritten-digit-detector/lists"}