Update README.md

README.md

@@ -1,35 +1,47 @@
-# Engagement Detection API
-
-A Flask-based API for detecting engagement levels from facial expressions using TensorFlow Lite.
-
-## API Endpoints
-
-- `GET /`: Returns API information
-- `POST /predict`: Accepts an image file and returns engagement predictions
-
-## Deployment
-
-1. Clone this repository
-2. Build Docker image: `docker build -t engagement-api .`
-3. Run container: `docker run -p 7860:7860 engagement-api`
-
-## Example Usage
-
-```python
-import requests
-
-url = "https://your-huggingface-space-url.hf.space/predict"
-files = {'image': open('test.jpg', 'rb')}
-response = requests.post(url, files=files)
-print(response.json())
-```
-
-## Model Details
-
-- Model: Custom TensorFlow Lite model (`engagement_model_89.tflite`)
-- Input: 224x224 RGB face image
-- Output: Probabilities for 4 engagement states:
-  - Engaged
-  - Frustrated
-  - Bored
-  - Confused
+---
+title: "Detect4Enhance Backend"
+emoji: "🤖"
+colorFrom: blue
+colorTo: green
+sdk: docker
+sdk_version: "latest"
+app_file: app.py
+pinned: false
+---
+
+
+# Engagement Detection API
+
+A Flask-based API for detecting engagement levels from facial expressions using TensorFlow Lite.
+
+## API Endpoints
+
+- `GET /`: Returns API information
+- `POST /predict`: Accepts an image file and returns engagement predictions
+
+## Deployment
+
+1. Clone this repository
+2. Build Docker image: `docker build -t engagement-api .`
+3. Run container: `docker run -p 7860:7860 engagement-api`
+
+## Example Usage
+
+```python
+import requests
+
+url = "https://your-huggingface-space-url.hf.space/predict"
+files = {'image': open('test.jpg', 'rb')}
+response = requests.post(url, files=files)
+print(response.json())
+```
+
+## Model Details
+
+- Model: Custom TensorFlow Lite model (`engagement_model_89.tflite`)
+- Input: 224x224 RGB face image
+- Output: Probabilities for 4 engagement states:
+  - Engaged
+  - Frustrated
+  - Bored
+  - Confused