{"id":20380156,"url":"https://github.com/ammahmoudi/face-recognition","last_synced_at":"2026-06-11T09:31:36.806Z","repository":{"id":204351792,"uuid":"711636942","full_name":"ammahmoudi/Face-Recognition","owner":"ammahmoudi","description":"Face recognition using Eigen faces, PCA and support vector machines","archived":false,"fork":false,"pushed_at":"2023-10-29T21:34:30.000Z","size":2309,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-05T01:43:46.759Z","etag":null,"topics":["eigenfaces","face-recognition","machine-learning","ml","pca","svm"],"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/ammahmoudi.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}},"created_at":"2023-10-29T21:23:54.000Z","updated_at":"2023-10-29T21:35:07.000Z","dependencies_parsed_at":null,"dependency_job_id":"2843d750-edb6-4e43-88fb-eee09544e7e4","html_url":"https://github.com/ammahmoudi/Face-Recognition","commit_stats":null,"previous_names":["ammahmoudi/face-recognition"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ammahmoudi/Face-Recognition","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ammahmoudi%2FFace-Recognition","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ammahmoudi%2FFace-Recognition/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ammahmoudi%2FFace-Recognition/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ammahmoudi%2FFace-Recognition/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ammahmoudi","download_url":"https://codeload.github.com/ammahmoudi/Face-Recognition/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ammahmoudi%2FFace-Recognition/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34192870,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-11T02:00:06.485Z","response_time":57,"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":["eigenfaces","face-recognition","machine-learning","ml","pca","svm"],"created_at":"2024-11-15T02:06:17.928Z","updated_at":"2026-06-11T09:31:36.784Z","avatar_url":"https://github.com/ammahmoudi.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Face Classification by SVM on Eigenfaces\n\nWe are going to build a classifier (Face recognition using Eigen faces, PCA and support vector machines) to distinguish the faces of 40 people on a toy dataset. The dataset includes 400 pictures of 40 people faces, each by a 64*64 pixel picture.\n\n![samples of data](/samples.png)\n## Code Explanation\n\n### **Dataset and Visualization**:\n- The dataset consists of **400 pictures** of **40 people's faces**, each represented by a **64x64 pixel image**.\n- The code visualizes the first image of each class (person) using subplots.\n\n### **Train-Test Split**:\n- The data is split into train and test sets with a **70% train** and **30% test** split.\n- Dimensions of the sets are printed.\n\n### **Dimensionality Reduction (PCA)**:\n- Principal Component Analysis (PCA) is used to reduce dimensionality.\n- The number of components is chosen to keep **90% variance**.\n- Scree plot shows the proportion of variance explained by each component.\n\n### **Eigenfaces Visualization**:\n- Eigenfaces are the top eigenvectors from PCA.\n- The first 30 eigenfaces are plotted, showing facial features.\n\n    ![samples of data](/eigen.png)\n\n### **Transforming Data with PCA**:\n- Train and test features are transformed using PCA.\n\n### **SVM Classifier Training**:\n- An SVM classifier is trained on the transformed data.\n- Grid search is used for hyperparameter tuning.\n\n### **Model Evaluation**:\n- Model predictions are checked on test samples.\n- Precision-Recall tradeoff is visualized.\n- Decision threshold where recall equals precision is determined.\n\n### **ROC/AUC Comparison**:\n- A Random Forest classifier with 30 estimators is trained.\n- ROC curve and AUC are calculated for both SVM and Random Forest.\n- SVM has an AUC of 0.98, indicating good performance.\n\n### **Classification Report and Confusion Matrix**:\n- Classification report shows precision, recall, and F1-score for each class.\n- Confusion matrix visualizes true/false classifications per class.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fammahmoudi%2Fface-recognition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fammahmoudi%2Fface-recognition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fammahmoudi%2Fface-recognition/lists"}