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.

## ๐Ÿš€ 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`.

## ๐Ÿ“Š 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.

## ๐Ÿ“ฆ 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.

## ๐Ÿ›  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