bevy-sensor

A Rust library and CLI for capturing multi-view images (RGBA + Depth) of 3D objects, specifically designed for the Thousand Brains Project sensor simulation.

This crate serves as the visual sensor module for the neocortx project, providing TBP-compatible sensor data (64x64 resolution, specific camera intrinsics) from YCB dataset models.

Features

TBP-Compatible: Matches Habitat sensor specifications (resolution, coordinate systems).
Multi-View: Captures objects from spherical viewpoints (yaw/pitch).
YCB Integration: Auto-downloads and caches YCB Benchmark models.
Headless: Optimized for headless rendering on Linux and WSL2 (via WebGPU).

Requirements

Rust: 1.70+
Bevy: 0.15+
System: Linux with Vulkan drivers (or WSL2).
Tools: just (recommended command runner).

Quick Start

Install Just (Optional but recommended):
```
cargo install just
```

Run a Test Render:

just render-single 003_cracker_box
# Models will be automatically downloaded to /tmp/ycb if missing.
# To use a custom location: cargo run --bin prerender -- --data-dir ./my_models ...
# Output saved to test_fixtures/renders/

Usage

CLI (Batch Rendering)

Render the standard TBP benchmark set (10 objects):

just render-tbp-benchmark

Render specific objects:

just render-batch "003_cracker_box,005_tomato_soup_can"

Library (Rust)

Add to your Cargo.toml:

[dependencies]
bevy-sensor = "0.4"

Use in your code:

use bevy_sensor::{render_to_buffer, RenderConfig, ViewpointConfig, ObjectRotation};
use std::path::Path;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // 1. Configure
    let config = RenderConfig::tbp_default(); // 64x64, TBP intrinsics
    let viewpoint = bevy_sensor::generate_viewpoints(&ViewpointConfig::default())[0];
    let rotation = ObjectRotation::identity();
    let object_path = Path::new("/tmp/ycb/003_cracker_box");

    // 2. Render to memory (RGBA + Depth)
    let output = render_to_buffer(object_path, &viewpoint, &rotation, &config)?;
    
    println!("Captured {}x{} image", output.width, output.height);
    Ok(())
}

Troubleshooting

WSL2 Support

WSL2 does not support native Vulkan window surfaces well. This project defaults to the WebGPU backend on WSL2, which works reliably for headless rendering.

Fix: Ensure you have up-to-date GPU drivers on Windows.

Software Rendering (No GPU)

If you absolutely have no GPU, you can try software rendering (slow, potential artifacts):

LIBGL_ALWAYS_SOFTWARE=1 GALLIUM_DRIVER=llvmpipe cargo run --release

License

MIT

bevy-sensor 0.4.6