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The project focuses on building a system to classify human emotions by analyzing facial expressions captured through images or video.

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samithcsachi/Emotion-detection-with-Python-OpenCV-and-Scikit-Learn

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Emotion Detection with Python, OpenCV, and Scikit Learn

This project focuses on building a system to classify human emotions by analyzing facial expressions, using images or video as input.

Authors

Problem Statement

Emotion detection is a computer vision and machine learning project using Python libraries to identify and classify human emotions—such as happy, sad, angry, surprised, or neutral—from facial expressions. The workflow includes face detection, feature extraction, and emotion classification using machine learning models.

Features

  • Face Detection: Utilizes OpenCV to detect faces in images or live video.
  • Feature Extraction: Processes detected faces to extract relevant features for emotion analysis.
  • Emotion Classification: Trains and applies machine learning models (Scikit Learn) to classify emotions.
  • Data Preprocessing: Includes scripts for cleaning and organizing the dataset.
  • Model Training/Evaluation: Supports model training, evaluation, and testing on new data.

Tech Stack

  • pyhton
  • numpy
  • pandas
  • matplotlib
  • cv2
  • mediapipe

Explore the notebook

GitHub : https://github.com/samithcsachi/Image_Classification_CNN_Fruits

Kaggle : https://www.kaggle.com/datasets/saharnazyaghoobpoor/happy-and-sad-image

Contribution

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change or contribute.

License

MIT License

Copyright (c) 2025 Samith Chimminiyan

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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If you have any questions, suggestions, or collaborations in data science, feel free to reach out:

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The project focuses on building a system to classify human emotions by analyzing facial expressions captured through images or video.

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