Update README.md

README.md

@@ -10,4 +10,33 @@ short_description: Real-Time Monocular Depth Estimation for AR
 sdk_version: 5.7.1
 ---
 
+# Real-time Depth Estimation using Knowledge Distillation
+
+This project demonstrates real-time depth estimation using a compressed student model trained through knowledge distillation. Here's how it works:
+
+## Knowledge Distillation
+The CompressedStudentModel was trained using knowledge distillation from a larger, more complex teacher model (DPT). This technique allows the smaller student model to learn from the teacher's predictions, effectively transferring knowledge and achieving comparable performance with reduced computational requirements.
+
+## Model Architecture
+The student model uses an encoder-decoder architecture optimized for efficient depth estimation:
+- Encoder: Extracts hierarchical features through convolutional layers and max pooling.
+- Decoder: Upsamples features to produce a high-resolution depth map.
+
+## Real-time Processing
+The model is designed for real-time inference on webcam input:
+1. Each frame is preprocessed and resized to 200x200 pixels.
+2. The frame is passed through the model to generate a depth map.
+3. The depth map is visualized as a 3D surface plot using matplotlib.
+
+## 3D Visualization
+The depth map is rendered as an interactive 3D surface, providing an intuitive representation of the scene's depth structure. The plot uses a viridis colormap to represent depth values, with warmer colors indicating closer objects and cooler colors for more distant ones.
+
+## Usage
+To use this depth estimation tool:
+1. Ensure your webcam is connected and functioning.
+2. The interface will display your webcam feed and the corresponding 3D depth visualization in real-time.
+3. Move objects or your camera to see how the depth map changes dynamically.
+
+This project showcases the potential of compressed models and knowledge distillation in creating efficient, real-time computer vision applications.
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference