{"id":26769572,"url":"https://github.com/abhayy-kumar/food-image-classification","last_synced_at":"2026-04-25T11:36:32.859Z","repository":{"id":283607912,"uuid":"952326777","full_name":"Abhayy-Kumar/Food-Image-Classification","owner":"Abhayy-Kumar","description":"A deep learning technique that leverages transfer learning to classify images into different food categories.","archived":false,"fork":false,"pushed_at":"2025-03-21T05:22:12.000Z","size":524,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-02T00:29:35.922Z","etag":null,"topics":["deep-learning","image-classification","mobilenetv2","tensorflow","trasfer-learning"],"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/Abhayy-Kumar.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":"2025-03-21T05:18:17.000Z","updated_at":"2025-03-21T05:24:01.000Z","dependencies_parsed_at":"2025-03-21T06:24:32.148Z","dependency_job_id":"668815c0-c714-4991-8b56-5a0a65a076ad","html_url":"https://github.com/Abhayy-Kumar/Food-Image-Classification","commit_stats":null,"previous_names":["abhayy-kumar/food-image-classification"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Abhayy-Kumar/Food-Image-Classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhayy-Kumar%2FFood-Image-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhayy-Kumar%2FFood-Image-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhayy-Kumar%2FFood-Image-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhayy-Kumar%2FFood-Image-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Abhayy-Kumar","download_url":"https://codeload.github.com/Abhayy-Kumar/Food-Image-Classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhayy-Kumar%2FFood-Image-Classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32261117,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-25T09:15:33.318Z","status":"ssl_error","status_checked_at":"2026-04-25T09:15:31.997Z","response_time":59,"last_error":"SSL_read: 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":["deep-learning","image-classification","mobilenetv2","tensorflow","trasfer-learning"],"created_at":"2025-03-28T22:33:52.283Z","updated_at":"2026-04-25T11:36:27.849Z","avatar_url":"https://github.com/Abhayy-Kumar.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Food Image Classification\n\nThis repository contains a deep learning project that classifies images of 101 different foods. The project utilizes a pretrained MobileNetV2 model from TensorFlow/Keras and fine-tunes it with additional dense layers to achieve accurate food category predictions.\n\n## Overview\nThe objective of this project is to build an image classification system that identifies the food present in a given image. We employ a TensorFlow/Keras pretrained MobileNetV2 model, which is further fine-tuned with additional fully connected layers to classify images into 101 food categories. The project also includes steps for data preparation, train-test splitting, model training with early stopping, and evaluation using confusion matrices and classification reports.\n\n## Features\n- **Data Preparation:** \n  - Downloads the Food-41 dataset from Kaggle.\n  - Unzips and organizes images into a structured DataFrame.\n- **Data Splitting \u0026 Augmentation:** \n  - Splits the dataset into training, validation, and testing sets.\n  - Uses TensorFlow's `ImageDataGenerator` with MobileNetV2 preprocessing.\n- **Modeling \u0026 Transfer Learning:** \n  - Leverages MobileNetV2 as a feature extractor (with frozen weights).\n  - Adds two Dense layers and a softmax output layer to classify 101 food categories.\n- **Training \u0026 Early Stopping:** \n  - Uses the Adam optimizer and categorical crossentropy loss.\n  - Incorporates early stopping to prevent overfitting.\n- **Evaluation \u0026 Visualization:** \n  - Evaluates the model on a test set.\n  - Generates confusion matrices and classification reports.\n  - Visualizes the confusion matrix using Seaborn and Matplotlib.\n\n\n### Dataset link - https://www.kaggle.com/datasets/kmader/food41\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhayy-kumar%2Ffood-image-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhayy-kumar%2Ffood-image-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhayy-kumar%2Ffood-image-classification/lists"}