{"id":27437485,"url":"https://github.com/denatajp/smiledetection","last_synced_at":"2026-05-19T04:36:11.674Z","repository":{"id":286056406,"uuid":"852589747","full_name":"denatajp/smileDetection","owner":"denatajp","description":"A real-time face and smile detection application using the OpenCV library. By utilizing the webcam, the program automatically detects faces and smiles, drawing boxes around the detected areas. 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It uses Haar Cascades for face, eye, and smile detection.\n\n# Features\n- Real-time face detection.\n- Smile detection within detected faces.\n- Visualizes detections by drawing rectangles around faces and smiles.\n\n# Requirements\nTo run this project, you need to have the following installed:\n- Python 3.x\n- OpenCV (`cv2`)\n\n# How to Run\n1. Clone this repository to your local machine.\nEnsure you have OpenCV installed using the command:\n``` bash\npip install opencv-python\n```\n2. Run the script:\n``` bash\npython smileDetection.py\n```\nThe program will open a video stream using your webcam. To stop the video stream, press the q key.\n\n# How It Works\n- The program captures video frames from the webcam in real-time.\n- Each frame is converted to grayscale and processed using the Haar Cascade Classifiers for face, eye, and smile detection.\n- Rectangles are drawn around detected faces and smiles to visualize the detections.\n  \n# Example\nWhen the program is running, it looks like this:\n- Faces are highlighted with a blue rectangle.\n- Smiles are highlighted with a red rectangle.\n![image](https://github.com/user-attachments/assets/6eb083bb-5a6d-4283-98c1-e0ef344ad3eb)\n\n\n# Acknowledgements\n- OpenCV Haar Cascades were used for face and smile detection.\n- The code was adapted from the OpenCV tutorials and examples.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenatajp%2Fsmiledetection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdenatajp%2Fsmiledetection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenatajp%2Fsmiledetection/lists"}