A Rust client library for async interfacing with Limelight smart cameras.
Add this to your Cargo.toml:
[dependencies]
limelightlib-rust = "0.1.0"
tokio = { version = "1.0", features = ["full"] }use limelightlib_rust::{LimelightClient, LimelightConfig};
use tokio;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
// Create client with custom configuration
let config = LimelightConfig {
host: "10.0.0.2".to_string(),
port: 5807,
poll_interval_ms: 20,
};
let client = LimelightClient::new(config);
client.start().await?;
// Subscribe to vision processing results
let mut results = client.subscribe();
while let Ok(result) = results.recv().await {
// Process standard targeting results
if let Some(tx) = result.tx {
println!("Target X offset: {:.2}°", tx);
}
// Process AprilTag results
for tag in result.fiducial {
if let Some(id) = tag.f_id {
println!("Detected AprilTag ID: {}", id);
}
}
// Process MegaTag2 results
if let Some(botpose) = &result.botposeMT2 {
println!("MegaTag2 Robot Pose: {:?}", botpose);
}
}
Ok(())
}Access comprehensive vision processing results:
if let Some(result) = client.get_latest_result().await {
// Basic target information
if result.v.unwrap_or(0.0) > 0.0 {
println!("Valid target found!");
println!("X Offset: {:?}°", result.tx);
println!("Y Offset: {:?}°", result.ty);
println!("Target Area: {:?}%", result.ta);
// Non-cross-filtered results
println!("X Offset (No Cross): {:?}°", result.txnc);
println!("Y Offset (No Cross): {:?}°", result.tync);
}
// Process barcode results
for barcode in &result.barcode {
println!("Barcode: {:?} (Family: {:?})", barcode.data, barcode.fam);
}
// Process classifier results
for class in &result.classifier {
println!("Class: {:?} (ID: {:?})", class.class, class.class_id);
}
// Process detector results
for detection in &result.detector {
println!("Detection: {:?} (Conf: {:?})", detection.class, detection.conf);
}
}Complete pipeline control and configuration:
// Basic pipeline operations
client.switch_pipeline(1).await?;
client.reload_pipeline().await?;
// Get pipeline configurations
let default_pipeline = client.get_default_pipeline().await?;
let specific_pipeline = client.get_pipeline_at_index(0).await?;
// Update pipeline settings
let settings = serde_json::json!({
"type": "apriltag",
"parameters": { /* ... */ }
});
client.update_pipeline(settings, true).await?; // true to flush changes
// Upload complete pipeline
let pipeline = serde_json::json!({ /* pipeline config */ });
client.upload_pipeline(pipeline, Some(0)).await?;Upload and configure custom neural networks:
// Upload detector network
let detector_data = std::fs::read("detector.tflite")?;
client.upload_neural_network("detector", &detector_data, Some(0)).await?;
// Upload classifier network
let classifier_data = std::fs::read("classifier.tflite")?;
client.upload_neural_network("classifier", &classifier_data, Some(0)).await?;
// Upload network labels
let labels = "class1\nclass2\nclass3";
client.upload_neural_network_labels("detector", labels, Some(0)).await?;Comprehensive calibration management:
// Get calibration data
let default_cal = client.get_calibration_default().await?;
let file_cal = client.get_calibration_file().await?;
let eeprom_cal = client.get_calibration_eeprom().await?;
let latest_cal = client.get_calibration_latest().await?;
// Update calibration
let calibration = serde_json::json!({ /* calibration data */ });
client.update_calibration_file(calibration).await?;
client.update_calibration_eeprom(calibration).await?;
// Delete calibration data
client.delete_calibration_latest().await?;
client.delete_calibration_file().await?;
client.delete_calibration_eeprom().await?;Access device information and status:
// Get device status and reports
let status = client.get_status().await?;
let hardware_report = client.get_hardware_report().await?;Comprehensive pose estimation support:
if let Some(result) = client.get_latest_result().await {
// Standard pose estimation
if let Some(pose) = &result.botpose {
println!("Robot Pose: {:?}", pose);
}
// IMU-Fused MegaTag2 pose estimation (requires robot orientation updates)
if let Some(pose_mt2) = &result.botposeMT2 {
println!("MegaTag2 Pose: {:?}", pose_mt2);
}
// WPI field space poses (blue/red alliance)
if let Some(pose_blue) = &result.botpose_wpiblue {
println!("WPI Blue Alliance Pose: {:?}", pose_blue);
}
// Pose quality metrics
println!("Tag Count: {:?}", result.botpose_tagcount);
println!("Pose Span: {:?}", result.botpose_span);
println!("Average Distance: {:?}", result.botpose_avgdist);
println!("Average Area: {:?}", result.botpose_avgarea);
}
// Update robot orientation
client.update_robot_orientation(45.0).await?;Manage Python processing pipelines:
// Get available SnapScript names
let scripts = client.get_snapscript_names().await?;
// Update Python inputs
let inputs = vec![1.0, 2.0, 3.0];
client.update_python_inputs(&inputs).await?;
// Get Python outputs from results
if let Some(result) = client.get_latest_result().await {
if let Some(outputs) = &result.python_out {
println!("Python outputs: {:?}", outputs);
}
}Comprehensive snapshot control:
// Capture and manage snapshots
client.capture_snapshot("calibration").await?;
client.upload_snapshot("custom_image", &image_data).await?;
let snapshot_list = client.get_snapshot_manifest().await?;
client.delete_snapshot("old_image").await?;
client.delete_snapshots().await?; // Delete all// Change polling rate to 50ms
client.set_poll_rate(50).await?;
// Get current poll rate
let current_rate = client.get_poll_rate().await;pub enum LimelightError {
HttpError(reqwest::Error),
WebSocketError(tokio_tungstenite::tungstenite::Error),
JsonError(serde_json::Error),
UrlError(url::ParseError),
ConfigError(String),
TimeoutError,
NotRunning,
}Enable debug logging:
use tracing_subscriber;
tracing_subscriber::fmt()
.with_env_filter("limelightlib_rust=debug")
.init();Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License.