chore: update README.md

README.md

@@ -2,34 +2,51 @@
 license: apple-ascl
 library_name: coreml
 tags:
-- apple
-- amlr
-- computer-vision
 - depth-estimation
 - visionos
-- macos
+- apple-silicon
+- amlr
+- computer-vision
+- depth-pro
+- 512x512
+- ane-optimized
+extra_gated_heading: DepthPro CoreML (Fast 512px - ANE Optimized)
+extra_gated_button_content: Access Model
 ---
 
-# DepthPro: High-Resolution Monocular Depth (CoreML)
-
-This repository provides CoreML-optimized weights for **DepthPro**, adapted for on-device inference on visionOS and macOS.
-
-## Configuration
-- **Resolution**: 512x512 (Optimized for <1s inference)
-- **Precision**: Float16
-- **Architecture**: Multi-scale ViT-Large with Sharp Boundary Refinement
-
-## Performance (M2 Apple Vision Pro)
-- **Transform + Encoder**: ~700ms (GPU Fallback)
-- **Decoder + Depth Head**: ~150ms
-- **Total Pipeline**: < 1.0s per frame
-
-## Citation
-If you use this model in your research or applications, please cite the original work:
-```bibtex
-@article{Bochkovskii2024:DepthPro,
-  title={DepthPro: Sharp Monocular Depth Estimation with Full-Resolution Refinement},
-  author={Bochkovskii, Alexey and Fogosar, Ambron and Koltun, Vladlen},
-  journal={arXiv preprint arXiv:2410.02073},
-  year={2024}
-}
+# DepthPro CoreML (512x512 Real-Time)
+
+This repository contains the **Fast (512x512)** version of the DepthPro model, specifically optimized for the **Apple Neural Engine (ANE)**.
+
+DepthPro is a state-of-the-art monocular depth estimation model. This 512px version is designed for **Real-Time Previews** and high-speed video conversion on Apple Vision Pro and Apple Silicon Macs.
+
+## 🚀 Key Features
+- **ANE Accelerated**: Leveraging the Apple Neural Engine for ultra-low power and high-speed inference.
+- **Real-Time Performance**: Ideal for interactive parameter tuning (Max Disparity, Convergence Plane).
+- **VisionOS Ready**: Fully compatible with Apple Vision Pro via the `DepthProPipeline`.
+
+## 📊 Performance & Requirements
+| Metric | Specification |
+| :--- | :--- |
+| **Input Resolution** | 512 x 512 pixels |
+| **Compute Units** | All (Optimized for ANE) |
+| **Average Latency** | < 1.0s per frame (on M2/M3 chips) |
+| **Target Use Case** | Real-time 3D Preview / Quick Video Conversion |
+
+> [!TIP]
+> This model is the best choice for the initial phase of your 3D conversion workflow, allowing for near-instant feedback while adjusting 3D rendering parameters.
+
+## 📦 Repository Contents
+The repository contains the following core components:
+1. `DepthPro_transform.mlpackage`: Image preprocessing.
+2. `DepthPro_encoder.mlpackage`: Feature extraction (ANE Optimized).
+3. `DepthPro_decoder.mlpackage`: Multiresolution fusion.
+4. `DepthPro_depth.mlpackage`: Final depth output.
+
+## 🛠 Usage with Swift Transformers
+You can download and cache this model dynamically using `swift-transformers`:
+
+```swift
+let hub = Hub()
+let modelDir = try await hub.snapshot(repoId: "aarondevstack/DepthPro-512x512-coreml")
+// Load models from the downloaded directory