File size: 2,090 Bytes
305b807 14ff16b d8d87bc 305b807 14ff16b d8d87bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | ---
license: apple-ascl
library_name: coreml
tags:
- depth-estimation
- visionos
- 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 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.
## ๐ 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`.
## ๐ 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.
## ๐ฆ 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.
## ๐ 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
|