Build Advanced Robotics with Embedded Stereo Vision
Stereovis offers a fully integrated development experience, from edge devices with NVIDIA Jetson to SDKs, APIs, and ready-to-run examples in Python, C++, and ROS. Everything you need is right here.
⚙️ Quick Start
✅ Supported Languages
- Python 3.7+
- C++
- C#
- ROS (Noetic / Humble)
✅ Supported OS
- Ubuntu 20.04 / 22.04
- Windows 10/11 (x64)
🔌 Device Setup
- Connect the camera via Gigabit Ethernet
-
Set your PC’s IP address to match the subnet
e.g.: Camera 192.168.1.251, PC 192.168.1.254 - Enable jumbo frames + full duplex (recommended)
🔧 SDK Installation
Python:
pip install stereovis_sdk
C++: Link the included .lib or .so from the /lib folder
Include headers from /include
C#: Add reference to StereovisAPI.dll in your project
📚 SDK Structure
/lib → Precompiled libraries (Windows/Linux)
/include → C++ and C# headers
/demo → Sample applications
/tools → Image viewer + config tool
/docs → Full documentation PDFs
🐍 Python Sample
from stereovis_sdk import Camera
cam = Camera(ip='192.168.1.251')
cam.initialize()
cam.trigger()
pointcloud = cam.get_point_cloud('6D')
print("Points captured:", len(pointcloud))
💻 C++ Sample
init3DCam(0, "192.168.1.251", imgW, imgH);
softTrigCam(true);
getXYZInt(150, 120, outXYZ);
🤖 Robot Communication
Send Pose via TCP (Python):
cam.send_robot_pose(x=300, y=0, z=200, roll=0, pitch=0, yaw=90)
Works with:
Universal Robots, ABB, KUKA, Doosan, Kinova, and many more mainstream 6-axis robots
🔬 3D Output Options
- getPtCloud4D() → XYZ + Intensity
- getPtCloud6N() → XYZ + Normals
- getPtCloud6C() → XYZ + RGB
- getXYZInt(x, y) → 3D from pixel
- getRect3DCloud() → ROI point cloud
📦 ROS Integration
Install via package manager:
sudo apt install ros-noetic-stereovis
Launch:
roslaunch stereovis camera.launch
🧠 AI & Inference (Jetson Devices)
Use torch, onnxruntime, or TensorRT for inference:
from my_model import Net
model = Net()
output = model(cam.get_point_cloud())