{"id":27260283,"url":"https://github.com/akshaypatra/expression_detector","last_synced_at":"2026-04-30T13:34:30.016Z","repository":{"id":287022041,"uuid":"963329955","full_name":"akshaypatra/Expression_detector","owner":"akshaypatra","description":"The Expression Detector is an AI-based system that identifies and classifies human facial expressions in real-time . 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Its goal is to classify human emotions such as happy, sad, angry, surprised, neutral, etc., based on facial features.\n\n### 🔑 Key Points of Expression Detector\n\n#### 1. Face Detection\n\n-- First, the system detects the face region in the image or video frame.\n-- OpenCV is used .\n\n#### 2. Feature Extraction\n\n-- Facial landmarks (eyes, eyebrows, mouth, nose, etc.) are extracted.\n--  MediaPipe and deep learning models (like CNNs) is used.\n\n#### 3. Emotion Classification\n\n-- Once features are extracted, the model classifies the expression.\n-- Deep learning models (e.g. custom CNNs) is used.\n-- Typical emotions: Happy, Sad, Angry, Fear, Disgust, Surprise, Neutral.\n\n#### 4. Real-time Analysis \n\n-- Webcam or camera feed is used to analyze and predict expressions in real-time.\n-- Useful for interactive systems or monitoring applications.\n\n#### 5. Output\n\n-- Displays the detected emotion label predicted by the Model .\n\n\n### Sample Output :\n\n\n\u003cimg width=\"1027\" alt=\"Screenshot 2025-04-10 at 21 57 57\" src=\"https://github.com/user-attachments/assets/e10d9bb2-c3d5-4230-a8f5-4cfba620a0fd\" /\u003e\n\n\u003cimg width=\"1059\" alt=\"Screenshot 2025-04-10 at 21 58 17\" src=\"https://github.com/user-attachments/assets/d2bc4b9b-e2ab-4112-a65e-9e0453415825\" /\u003e\n\n\n\n\n\n## Before you run \n\n### Step 1: install python@3.10 or 3.11\n\n### Step 2:  create a virtual environment \n\n1. for mac :\n\n        python3.10 -m venv myenv\n\n        source myenv/bin/activate\n\n\n2. for windows : \n\n        python -m venv myenv\n\n        myenv\\Scripts\\activate\n\n\n### Step 3: Configure VS Code to Use Python 3.10\n\nIf you're using VS Code, follow these steps:\n\n1. Press Ctrl+Shift+P → Type \"Python: Select Interpreter\".\n   \n2. Select Python 3.10 or the virtual environment myenv/bin/python.\n   \n3. Restart VS Code to apply changes.\n\n\n\n### Step 4 : install dependencies \n\n        pip install mediapipe numpy tensorflow keras opencv-python\n\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakshaypatra%2Fexpression_detector","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fakshaypatra%2Fexpression_detector","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakshaypatra%2Fexpression_detector/lists"}