{"id":19973355,"url":"https://github.com/moonshallow5/food_vision_mini","last_synced_at":"2026-05-09T07:37:43.307Z","repository":{"id":256435359,"uuid":"851829661","full_name":"Moonshallow5/Food_Vision_mini","owner":"Moonshallow5","description":"A program which can detect if an image contains either a pizza, sushi or steak: Has now been deployed on Flutter :)","archived":false,"fork":false,"pushed_at":"2024-09-22T03:46:56.000Z","size":61767,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-01T18:31:09.394Z","etag":null,"topics":["huggingface","matplotlib","numpy","pytorch"],"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/Moonshallow5.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":"2024-09-03T19:10:53.000Z","updated_at":"2024-09-22T03:46:58.000Z","dependencies_parsed_at":null,"dependency_job_id":"4838148b-8bf7-43af-affe-b4c7f3a907df","html_url":"https://github.com/Moonshallow5/Food_Vision_mini","commit_stats":null,"previous_names":["moonshallow5/food_vision_mini"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Moonshallow5/Food_Vision_mini","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Moonshallow5%2FFood_Vision_mini","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Moonshallow5%2FFood_Vision_mini/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Moonshallow5%2FFood_Vision_mini/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Moonshallow5%2FFood_Vision_mini/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Moonshallow5","download_url":"https://codeload.github.com/Moonshallow5/Food_Vision_mini/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Moonshallow5%2FFood_Vision_mini/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32811655,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-08T08:22:46.396Z","status":"online","status_checked_at":"2026-05-09T02:00:06.633Z","response_time":123,"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":["huggingface","matplotlib","numpy","pytorch"],"created_at":"2024-11-13T03:11:18.535Z","updated_at":"2026-05-09T07:37:43.275Z","avatar_url":"https://github.com/Moonshallow5.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Food_Vision_mini\n\n\n## 💭 What this project does\n\nI wanted to have a more hands-on experience in machine learning, so I decided to make a food image classification program. My program can take an image of either a \"sushi\", \"pizza\" or a \"steak\" and would be able to return a conclusion on what that image actually is\n\n## 💡 What I implemented\n\nIn this program I implemented multiple different models to test which model has the highest accuracy in classifying if an image contains either a sushi, pizza or steak.\n\nMy test results are shown on \u003ca href=\"https://github.com/Moonshallow5/Food_Vision_mini/blob/main/results.txt\"\u003e results.txt\u003c/a\u003e, where I used pre-trained pytorch models of efficinentnetb2 and resnet50, as well as my own model which has a much lower accuracy.\n\nFurthermore, I also implemented my own custom implementation in \u003ca href=\"https://github.com/Moonshallow5/Food_Vision_mini/blob/main/model_architecture.py\"\u003emodel_architecture.py\u003c/a\u003e, where a TinyVGG and VGG16 is implemented, which has much lower test accuracy as it isn't a pre-trained model and i have a small selection of datasets\n\nHere are \u003ca href=\"https://github.com/Moonshallow5/Food_Vision_mini/blob/main/effnet_b2_7_epochs_without_aug.png\"\u003eEffnet_b2\u003c/a\u003e and \u003ca href=\"https://github.com/Moonshallow5/Food_Vision_mini/blob/main/resnet50_7_epochs_without_aug.png\"\u003eresnet50\u003c/a\u003e test results on 7 epochs without any data augmentation \n\n\nLearn about MLflow as well as Nsight systems to optimize my program and see for any potential bottlenecks as well\n\n## 👀Live preview\n\nI wanted to show my project in live-action so I made a link to my \u003ca href=\"https://huggingface.co/spaces/Moonshallow5/FoodVision_mini?logs=container\"\u003eHuggingFace\u003c/a\u003e account where there is already an app running on gradio for anyone to use. The model used in HuggingFace and in my \u003ca href=\"https://github.com/Moonshallow5/Food_Vision_Flutter\"\u003eFlutter project\u003c/a\u003e  are models which were trained in this repo.\n\n## 🔧Further implementations \n\n- [x] I want to turn this program into a Flutter API for anyone to use it on their mobile phones, but this would take me some time to lern Dart documentations\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoonshallow5%2Ffood_vision_mini","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmoonshallow5%2Ffood_vision_mini","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoonshallow5%2Ffood_vision_mini/lists"}