{"id":48987634,"url":"https://github.com/wishercarts/face-recognition-system","last_synced_at":"2026-04-18T13:13:14.223Z","repository":{"id":337004472,"uuid":"1151981185","full_name":"WISHERCARTs/face-recognition-system","owner":"WISHERCARTs","description":"AI Face Recognition System using Python \u0026 Streamlit","archived":false,"fork":false,"pushed_at":"2026-02-07T14:14:31.000Z","size":12,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-02-07T17:39:57.653Z","etag":null,"topics":["machine-learning","python","streamlit"],"latest_commit_sha":null,"homepage":"https://wishercarts-face-recognition-system-app-vti7zr.streamlit.app/","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/WISHERCARTs.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,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-02-07T07:03:35.000Z","updated_at":"2026-02-07T14:14:35.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/WISHERCARTs/face-recognition-system","commit_stats":null,"previous_names":["wishercarts/face-recognition-system"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/WISHERCARTs/face-recognition-system","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/WISHERCARTs%2Fface-recognition-system","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/WISHERCARTs%2Fface-recognition-system/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/WISHERCARTs%2Fface-recognition-system/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/WISHERCARTs%2Fface-recognition-system/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/WISHERCARTs","download_url":"https://codeload.github.com/WISHERCARTs/face-recognition-system/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/WISHERCARTs%2Fface-recognition-system/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31970100,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-18T00:39:45.007Z","status":"online","status_checked_at":"2026-04-18T02:00:07.018Z","response_time":103,"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":["machine-learning","python","streamlit"],"created_at":"2026-04-18T13:13:08.953Z","updated_at":"2026-04-18T13:13:14.211Z","avatar_url":"https://github.com/WISHERCARTs.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Face Recognition System 🧠\n\nโปรเจกต์ระบบจำแนกใบหน้าโดยใช้ Machine Learning\n\n[![Open in Streamlit](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://wishercarts-face-recognition-system-app-vti7zr.streamlit.app/)\n\n👉 **[Live Demo](https://wishercarts-face-recognition-system-app-vti7zr.streamlit.app/)**\n\n## ทำอะไร?\n\nระบบนี้ใช้ **PCA** ลดขนาดข้อมูลรูปภาพ แล้วใช้ **SVM** จำแนกว่าเป็นใบหน้าของใคร\n\n## Dataset\n\nใช้ชุดข้อมูล **LFW (Labeled Faces in the Wild)** จาก sklearn\n\n- รูปใบหน้าคนดัง\n- ขนาด 62x47 pixels\n\n## วิธีรัน\n\n```bash\n# ติดตั้ง dependencies\npip install -r requirements.txt\n\n# รัน training script\npython Faces.py\n\n# รัน dashboard\nstreamlit run app.py\n```\n\n## ไฟล์ในโปรเจกต์\n\n| ไฟล์               | อธิบาย                     |\n| ------------------ | -------------------------- |\n| `Faces.py`         | โค้ดหลักสำหรับ train model |\n| `app.py`           | Dashboard แสดงผลลัพธ์      |\n| `requirements.txt` | รายการ library ที่ใช้      |\n\n## เทคนิคที่ใช้\n\n1. **PCA** - ลด features จาก ~3000 เหลือ 150\n2. **SVM (RBF kernel)** - จำแนกใบหน้า\n3. **GridSearchCV** - หาค่า parameter ที่ดีที่สุด\n\n## ผลลัพธ์\n\n- Accuracy ประมาณ 85-90%\n- แสดง Confusion Matrix และ Pie Chart\n\n## สิ่งที่เรียนรู้\n\n- การใช้ PCA สำหรับ dimensionality reduction\n- การ train SVM classifier\n- การปรับจูน hyperparameters ด้วย GridSearchCV\n- การ visualize ผลลัพธ์ด้วย matplotlib และ seaborn\n\n---\n\n# 🌐 English Version\n\n## What is this?\n\nA Face Recognition System using Machine Learning techniques: **PCA** for dimensionality reduction and **SVM** for classification.\n\n[![Open in Streamlit](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://wishercarts-face-recognition-system-app-vti7zr.streamlit.app/)\n\n👉 **[Live Demo](https://wishercarts-face-recognition-system-app-vti7zr.streamlit.app/)**\n\n## Dataset\n\nUsing **LFW (Labeled Faces in the Wild)** dataset from sklearn:\n\n- Celebrity face images\n- Image size: 62x47 pixels\n\n## How to Run\n\n```bash\n# Install dependencies\npip install -r requirements.txt\n\n# Run training script\npython Faces.py\n\n# Run dashboard\nstreamlit run app.py\n```\n\n## Project Files\n\n| File               | Description                     |\n| ------------------ | ------------------------------- |\n| `Faces.py`         | Main training script            |\n| `app.py`           | Streamlit dashboard for results |\n| `requirements.txt` | List of required libraries      |\n\n## Techniques Used\n\n1. **PCA (Principal Component Analysis)** - Reduce features from ~3000 to 150 components\n2. **SVM (Support Vector Machine with RBF kernel)** - Face classification\n3. **GridSearchCV** - Hyperparameter tuning to find optimal parameters\n\n## Results\n\n- Accuracy: approximately **85-90%**\n- Visualization: Confusion Matrix and Pie Chart\n\n## What I Learned\n\n- Implementing PCA for dimensionality reduction\n- Training SVM classifier for multi-class classification\n- Hyperparameter tuning with GridSearchCV\n- Data visualization with matplotlib and seaborn\n- Building interactive dashboards with Streamlit\n\n---\n\nMade by **Wish Nakthong** | 📧 Contact: [GitHub](https://github.com/WISHERCARTs)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwishercarts%2Fface-recognition-system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwishercarts%2Fface-recognition-system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwishercarts%2Fface-recognition-system/lists"}