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Get EagleEye running on your robot

FRC vision that gets your robot pose on NetworkTables. Install it, point a camera at an AprilTag, and go.

Start setup
1. Install
One command on supported Debian 12 ARM64 hardware
2. Build a pipeline
Discover and check cameras, then wire up detection in the web UI
3. Publish pose
Publish robot pose to NetworkTables with a configured output node

Install on your hardware

Flash or SSH into supported Debian 12 ARM64 hardware, run the install command, and reach the web UI on port 5001.

Install →

Set up cameras

Discover cameras, check their views, calibrate intrinsics, and place them on the robot for a usable field pose.

Cameras →

Publish AprilTag pose

Send robot pose to NetworkTables so your drive code can consume it, then keep it healthy on match day.

NetworkTables →

Extending EagleEye or adding an operation? Developer Docs

See what the system is doing

Open http://<device-ip>:5001 from a laptop on the robot network. The UI covers camera setup, pipeline editing, live status, and device controls.

Live camera frame with detected AprilTags marked

See live detections

Open an operation to inspect its output while the pipeline runs.

AprilTag operations connected in the Pipeline tab

Build the graph

Wire camera input, AprilTag detection, pose, and NetworkTables output.

Robot pose shown on the field in the 3D View tab

Check pose on the field

The 3D view makes bad camera placement and pose jumps obvious.

ChArUco detections and captured corner coverage in the calibration tool

Calibrate in the browser

See detected ChArUco corners and coverage while collecting calibration frames.

Wi-Fi Network Manager opened from the Settings tab

Run the device

Connect Wi-Fi, read logs, restart the backend, or use the built-in terminal.

Temporal Acceleration settings beside its live processed frame

See what each operation sees

Tune preprocessing beside its live output, then keep the graph running.