{"id":23327814,"url":"https://github.com/axelseancp/cat_breed_classification","last_synced_at":"2026-05-07T00:38:35.891Z","repository":{"id":219314977,"uuid":"735520815","full_name":"AxelSeanCP/Cat_Breed_Classification","owner":"AxelSeanCP","description":"A machine learning project for image classification from dicoding machine learning course","archived":false,"fork":false,"pushed_at":"2024-04-21T13:36:21.000Z","size":36788,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-13T11:54:52.033Z","etag":null,"topics":["computer-vision","image-classification","machine-learning","python","tensorflow"],"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/AxelSeanCP.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":"2023-12-25T08:10:41.000Z","updated_at":"2024-04-21T13:36:21.000Z","dependencies_parsed_at":"2024-12-20T20:33:17.312Z","dependency_job_id":"52ac0c12-b3c9-4096-9c4d-b933f1a12609","html_url":"https://github.com/AxelSeanCP/Cat_Breed_Classification","commit_stats":null,"previous_names":["axelseancp/cat_breed_classification"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AxelSeanCP%2FCat_Breed_Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AxelSeanCP%2FCat_Breed_Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AxelSeanCP%2FCat_Breed_Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AxelSeanCP%2FCat_Breed_Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AxelSeanCP","download_url":"https://codeload.github.com/AxelSeanCP/Cat_Breed_Classification/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247615479,"owners_count":20967183,"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":["computer-vision","image-classification","machine-learning","python","tensorflow"],"created_at":"2024-12-20T20:33:12.226Z","updated_at":"2026-05-07T00:38:35.849Z","avatar_url":"https://github.com/AxelSeanCP.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Cat_Breed_Classification\nA machine learning image classification project to detect cat breeds from dicoding machine learning course\n\n![image of the model prediction result](predict_result.png)\n\n## Dataset\n* source : [oxford-iit-cats-extended-10k](https://www.kaggle.com/datasets/doctrinek/oxford-iiit-cats-extended-10k)\n* about : this dataset contains 12 differents cat breeds\n* samples : 10k images in total from 12 subfolders (class), all the images have different image resolution\n\n## Files\n- image_predict \u0026rarr; folder of the images used for prediction\n- old_code \u0026rarr; folder containing old files \n- predict_result \u0026rarr; result image file of the prediction\n- cat_breed_classification_2.ipynb \u0026rarr; notebook file for the project \n- cat_breed_classification_2.py \u0026rarr; python file for the project\n- vegs.tflite \u0026rarr; the saved model ready to be deployed to Android\n\n## Criteria\n- free dataset with **1000 images minimum**\n- dataset **has never been used** in previous machine learning class submissions\n- dataset is split into **80% train set** and **20% test set**\n- model should use **model sequential**\n- model should use **Conv2D Maxpooling layer**\n- accuracy on training and validation set is **80% minimum**\n- implement **callback**\n- create **plot** for model accuracy and loss\n- create code to save model in **TFLite** format\n\n## Optional criteria (5*)\n- dataset has minimum **10000 images** and **3 class**\n- image resolution in dataset is not constant (varies)\n- accuracy on training and validation set is **92% minimum**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faxelseancp%2Fcat_breed_classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faxelseancp%2Fcat_breed_classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faxelseancp%2Fcat_breed_classification/lists"}