burn_depth 0.2.0

burn depth pro model inference
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# burn_depth 🔥📐😎

[![test](https://github.com/mosure/burn_depth/workflows/test/badge.svg)](https://github.com/Mosure/burn_depth/actions?query=workflow%3Atest)
[![crates.io](https://img.shields.io/crates/v/burn_depth.svg)](https://crates.io/crates/burn_depth)


burn [depth pro](https://github.com/apple/ml-depth-pro) model inference


| input               | metric depth               |
|-----------------------|-----------------------|
| ![Alt text](./assets/image/test.jpg)    | ![Alt text](./docs/test_depth.png)    |


## usage

```rust
use burn::prelude::*;
use burn_depth::{InferenceBackend, model::depth_pro::DepthPro};

// NdArray backend (alternatively: burn::backend::Cuda, burn::backend::Cpu)
let device = <InferenceBackend as Backend>::Device::default();

let model = DepthPro::<InferenceBackend>::load(&device, "assets/model/depth_pro.mpk")?;

// Image tensor with shape [1, 3, H, W] (batch, channels, height, width)
let input: Tensor<InferenceBackend, 4> = Tensor::zeros([1, 3, 512, 512], &device);

let result = model.infer(input, None);
// result.depth: Tensor<InferenceBackend, 3> with shape [1, H, W]
// result.focallength_px: Tensor<InferenceBackend, 1> with shape [1]
```


## setup

- download [`depth_pro.pt`](https://github.com/apple/ml-depth-pro/blob/main/get_pretrained_models.sh) to `assets/model/`
- `cargo run --bin import --features import`
- `cargo run --example inference`