Create README.md

README.md

@@ -0,0 +1,72 @@
+---
+language: en
+tags:
+- facial-emotion-recognition
+- computer-vision
+- tensorflow
+- keras
+license: apache-2.0
+---
+
+# Facial Emotion Detection Model
+
+A lightweight deep learning model that classifies facial expressions into 7 emotion categories.
+
+## Model Details
+
+- **Model type:** Image Classification
+- **Architecture:** ResNet50-based
+- **Input:** 224x224 RGB images
+- **Output:** 7 emotion classes
+- **Accuracy:** 85.60%
+
+## Emotion Classes
+
+- 😠 Angry
+- 🤢 Disgust  
+- 😨 Fear
+- 😊 Happy
+- 😐 Neutral
+- 😢 Sad
+- 😲 Surprise
+
+## Quick Start
+
+```python
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+
+# Load model
+model = load_model('Facial_Emotion_Detection_Model.h5')
+
+# Preprocess image
+img = Image.open('face.jpg').convert('RGB').resize((224, 224))
+x = np.array(img) / 255.0
+x = np.expand_dims(x, axis=0)
+
+# Predict
+predictions = model.predict(x)
+emotion = ['angry', 'disgust', 'fear', 'happy', 'neutral', 'sad', 'surprise'][np.argmax(predictions)]
+confidence = np.max(predictions)
+
+print(f"Emotion: {emotion} ({confidence:.2%})")
+Usage
+Ideal for:
+
+Emotion analysis applications
+
+Human-computer interaction
+
+Customer sentiment analysis
+
+Research projects
+
+Limitations
+Best with frontal face images
+
+Performance varies with image quality
+
+Cultural differences may affect accuracy
+
+License: Apache 2.0