DepthAnything-ROS is ROS2 wrapper for Depth-Anything.
nuscenes_demo.mp4
- Environment
- Ubuntu 22.04.01, ROS2 Humble
- CUDA 12.3, cuDNN 8.9.5.29-1+cuda12.2, TensorRT 8.6.1.6-1+cuda12.0
- Install ROS2
See ROS2 document.
To install ROS2 easily, I recommend to use ansible script of Autoware. In detail, please see the installation page.
- Install dependency
sudo apt install libgflags-dev libboost-all-dev
- Prepare your rosbag
If you don't have any rosbag, I recommend rosbag for Nuscenes dataset.
Set onnx files for DepthAnything-ROS/data or set onnx_path parameter.
<arg name="onnx_path" default="$(find-pkg-share depth_anything)/data/depth_anything_vitb14.onnx" />
Run below command to get the onnx files of pre-train model.
# Install gdown
pip install gdown
# Download onnx file
mkdir data && cd data
gdown 1jFTCJv0uJovPAww9PHCYAoek-KfeajK_If you want to make onnx files at yourself, please use depth-anything-tensorrt.
ros2 launch depth_anything depth_anything.launch.xml
input/image(sensor_msgs::msg::Image)
The input image.
~/output/depth_image(sensor_msgs::msg::Image)
The depth image made by DepthAnything.
onnx_path(string)- Default parameter: "$(find-pkg-share depth_anything)/data/depth_anything_vitb14.onnx"
The path to onnx file.
precision(string)- Default parameter: "fp32"
The precision mode to use quantization. DepthAnything-ROS supports in "fp32" or "fp16" (#2) for now.
When you run on the first start up, you need to wait about 5 minutes for build step.
- Performance
- RTX4090 results is written in official code
| Model | Params | RTX4090 TensorRT | RTX2070 TensorRT |
|---|---|---|---|
| Depth-Anything-Small | 24.8M | 3 ms | 27 ms, VRAM 300MB |
| Depth-Anything-Base | 97.5M | 6 ms | 65 ms, VRAM 700MB |
| Depth-Anything-Large | 335.3M | 12 ms | 200 ms, VRAM 1750MB |
- Depth-Anything
- trt-depth-anything Use for TensorRT inference
- depth-anything-tensorrt Use for making from pth files to onnx files
- tensorrt_common Use library
- cuda_utils Use library
- gdown