Upload folder using huggingface_hub

README.md

@@ -1,3 +1,21 @@
+---
+language: en
+license: mit
+library_name: tensorflow
+tags:
+- computer-vision
+- drowsiness-detection
+- driver-safety
+- cnn
+- tensorflow
+datasets:
+- custom
+metrics:
+- accuracy
+- binary-crossentropy
+pipeline_tag: image-classification
+---
+
 # Driver Drowsiness Detection Model
 
 This model is designed to detect driver drowsiness from facial images using a CNN architecture.
@@ -32,3 +50,25 @@ is_drowsy = prediction[0][0] > 0.5
 - Training method: Binary cross-entropy loss with Adam optimizer
 - Validation split: 20%
 - Early stopping with patience=3
+
+## Model Architecture
+- Input Layer: 64x64x3 images
+- Convolutional Layers:
+  - Conv2D(32, 3x3) + BatchNorm + ReLU
+  - MaxPooling2D(2x2)
+  - Conv2D(64, 3x3) + BatchNorm + ReLU
+  - MaxPooling2D(2x2)
+  - Conv2D(128, 3x3) + BatchNorm + ReLU
+  - MaxPooling2D(2x2)
+- Dense Layers:
+  - Dense(128) + BatchNorm + ReLU
+  - Dropout(0.5)
+  - Dense(1) + Sigmoid
+
+## Performance
+- Binary classification for drowsiness detection
+- Optimized for real-time inference
+- Suitable for embedded systems and edge devices
+
+## License
+This model is released under the MIT License.