This repository contains a Jupyter Notebook for building an emotion detection model, so the README should explain the idea, data, model, and how to run the notebook.[1][2]
You can create a README.md in your repo with content like this (edit details to match your exact notebook steps):
# Emotion Detection 🎭
This project implements an emotion detection model using deep learning to classify human emotions from images (or video frames) of faces. It is built in Python using a Jupyter Notebook (`Emotion_Detection.ipynb`) and common ML libraries like TensorFlow/Keras, OpenCV, and NumPy.
## 🚀 Project Overview
- Detects facial emotions such as happy, sad, angry, surprised, neutral, etc.
- Uses a convolutional neural network (CNN) trained on a labeled emotion dataset (e.g., FER-2013 or similar).
- Can be extended to work on images, video files, or webcam streams.
## 🧠 Features
- Data loading and preprocessing (grayscale/resize/normalization).
- CNN model definition, compilation, and training.
- Evaluation using accuracy/loss and confusion matrix.
- Option to test on custom images or webcam (if implemented in the notebook).
## 📂 Repository Contents
- `Emotion_Detection.ipynb` – main notebook with data preprocessing, model building, training, and evaluation.
- `requirements.txt` (recommended) – list of Python dependencies (TensorFlow/Keras, OpenCV, NumPy, Matplotlib, etc.).
- `models/` (optional) – saved trained model weights (`.h5` or `.keras`) if you export them.
- `samples/` (optional) – example input images and prediction outputs.
## 🛠️ Tech Stack
- Python
- Jupyter Notebook
- TensorFlow / Keras
- NumPy, Pandas
- Matplotlib / Seaborn
- OpenCV (if you use webcam/image detection)
## 📦 Installation
git clone https://github.com/Dnrahul/emotion-.git cd emotion-
pip install -r requirements.txt
If you do not have a `requirements.txt` yet, you can manually install:
pip install tensorflow keras opencv-python numpy pandas matplotlib seaborn
## ▶️ How to Run
1. Open the notebook:
jupyter notebook Emotion_Detection.ipynb
or upload it to Google Colab.
2. Run the cells in order to:
- Load and preprocess the dataset.
- Define and compile the CNN model.
- Train the model on the emotion dataset.
- Evaluate performance on validation/test data.
- (Optional) Run prediction on sample images or webcam frames.
3. If the notebook saves a trained model, find it as something like `emotion_model.h5` in the project directory.
## 📊 Results
Describe your best result here, for example:
- Training accuracy and validation accuracy after N epochs.
- Test accuracy.
- Observations about which emotions are predicted well and which are harder.
You can also add one or two sample plots (loss vs. epochs, accuracy vs. epochs) generated in the notebook.
## 🔮 Future Work
- Improve model architecture (deeper CNN, regularization, data augmentation).
- Add real-time webcam emotion detection using OpenCV.
- Deploy as a simple web app (Flask/FastAPI + frontend).
- Experiment with different datasets and class mappings.
## 📚 Inspiration / References
- Emotion detection projects and notebooks on GitHub and tutorials for FER-2013–based CNNs. [web:49][web:57]
[1](https://github.com/Faiz99khan/Emotion-Detection/blob/master/Emotion%20Detection.ipynb)
[2](https://github.com/topics/emotion-detection)
[3](https://github.com/RAHUL-KAD/Be-emotional)
[4](https://huggingface.co/RahulShewale/EmotionClassification/blame/main/Emotion_Classification.ipynb)
[5](https://github.com/Rahul5430/Speech-Emotion-Recognition-System)
[6](https://www.scribd.com/document/701894797/Music-Recommendation-System-by-Facial-Emotion-by-Rahul)
[7](https://github.com/sayakpaul/Emotion-Detection-using-Deep-Learning/blob/master/Emotion_Detection_Using_Deep_Learning.ipynb)
[8](https://github.com/apoorvaKR12695/Face-Emotion-Detection-)
[9](https://github.com/atulapra/Emotion-detection)
[10](https://github.com/AryaKoureshi/Emotion-Detection)
[11](https://github.com/rahulprasad2000/Real-Time-Emotion-Detection)
[12](https://github.com/i-benjelloun/text_emotions_detection)
[13](https://colab.research.google.com/github/rushikeshmagar31/emotions-detection/blob/main/Emotions_Detection.ipynb)
[14](https://github.com/priya-dwivedi/face_and_emotion_detection)
[15](https://www.youtube.com/watch?v=Vq_01gFG2vk)
[16](https://github.com/SanjayMarreddi/Emotion-Investigator)
[17](https://github.com/priya-dwivedi/face_and_emotion_detection/blob/master/src/EmotionDetector_v2.ipynb)
[18](https://github.com/gdscnitp/emotion-detection)
[19](https://github.com/topics/emotion-recognition)
[20](https://github.com/SannketNikam/Emotion-Detection-in-Text)