Momus
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Multi Camera Live Object Tracking | 562 | 2 years ago | 22 | gpl-3.0 | Python | |||||
| Multi-camera live traffic and object counting with YOLO v4, Deep SORT, and Flask. | ||||||||||
| Ctai | 236 | a year ago | 2 | Python | ||||||
| 基于深度学习的肿瘤辅助诊断系统，以图像分割为核心，利用人工智能完成肿瘤区域的识别勾画并提供肿瘤区域的特征来辅助医生进行诊断。有完整的模型构建、后端架设和前端访问功能。 | ||||||||||
| Hiitpi | 92 | 3 years ago | mit | Python | ||||||
| A workout trainer Dash/Flask app that helps track your HIIT workouts by analyzing real-time video streaming from your sweet Pi using machine learning and Edge TPU.. | ||||||||||
| Phormatics | 79 | 3 years ago | 6 | Jupyter Notebook | ||||||
| Using A.I. and computer vision to build a virtual personal fitness trainer. (Most Startup-Viable Hack - HackNYU2018) | ||||||||||
| Live Stream Face Detection | 78 | a year ago | 2 | mit | Python | |||||
| Live Streaming and Face Detection with Flask in Browser | ||||||||||
| Automatic_number_plate_recognition_yolo_ocr | 76 | a year ago | 4 | mit | Python | |||||
| Automatic number plate recognition using tech: Yolo, OCR, Scene text detection, scene text recognation, flask, torch | ||||||||||
| Ocr Tesseract Docker | 69 | 2 years ago | 5 | HTML | ||||||
| OCR using Python, Tesseract and OpenCV in a Docker container | ||||||||||
| Opencv Rest Api | 65 | 2 years ago | 1 | Python | ||||||
| Learn to create a REST API microservice for extracting faces from images using OpenCV, OpenCV-python, Flask, Docker, and Heroku | ||||||||||
| Flask_face_detection | 64 | 2 years ago | mit | Python | ||||||
| Face detection example in Python 3 based on OpenCV and Flask | ||||||||||
| Attendance Portal | 61 | a year ago | 2 | gpl-3.0 | JavaScript | |||||
| We have developed a cutting-edge attendance recorder. Using face recognition, you can easily record attendance and have access to in-depth analysis and a wide range of functionalities. Because of the covid-19 pandemic, stringent guidelines have been established, and precautions must be made to minimise unnecessary physical encounters. As a result, our method has shown to be effective in eliminating the requirement for any type of physical interaction while collecting and analysing attendance. | ||||||||||
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