Crate speciesnet

SpeciesNet Rust

The home of the ensemble for running SpeciesNet models in Rust.

Setup

Run

cargo add --git https://github.com/zubalis/speciesnet-rust.git --path speciesnet
cargo add --git https://github.com/zubalis/speciesnet-rust.git --path core
cargo add ort@=2.0.0-rc.9 -F download-binaries

to your program to get the lastest version of speciesnet.

Cargo features

• download-model, enabled by default, this allows you to run SpeciesNet::new to initialize the ensemble, which will download the default model from the internet.

Model setup

SpeciesNet Rust ensemble is using ort to run the model, which means the detector model and the classifier model needs to be converted to ONNX before this program can be run. We have a separate repository for generating SpeciesNet Rust compatible models in zubalis/speciesnet-onnx. You can grab the model files from there, extract it to a directory and use SpeciesNet::from_model_folder to initialize the model from that folder.

Examples

Initializing speciesnet with a custom extracted model folder.

use speciesnet::SpeciesNet;

let speciesnet = SpeciesNet::from_model_folder("./speciesnet-v4a/")?;

Running the entire pipeline (detector + classifier + ensemble).

use std::path::PathBuf;

use speciesnet_core::io::Instance;
use speciesnet::SpeciesNet;

let instances = vec![
    Instance::from_path_buf(PathBuf::from("./img1.jpeg")),
    Instance::from_path_buf(PathBuf::from("./img2.jpeg"))
];

let speciesnet = SpeciesNet::new()?;
let detections = speciesnet.predict(&instances)?;

Running the detector pipeline.

use std::path::PathBuf;

use speciesnet_core::io::Instance;
use speciesnet::SpeciesNet;

let instances = vec![
    Instance::from_path_buf(PathBuf::from("./img1.jpeg")),
    Instance::from_path_buf(PathBuf::from("./img2.jpeg"))
];

let speciesnet = SpeciesNet::new()?;
let detections = speciesnet.detect(&instances)?;

The returned detections is in the format of Prediction vector, which is the same for all apis.

Running the classifier pipeline.

use std::path::PathBuf;

use speciesnet_core::io::Instance;
use speciesnet::SpeciesNet;

let instances = vec![
    Instance::from_path_buf(PathBuf::from("./img1.jpeg")),
    Instance::from_path_buf(PathBuf::from("./img2.jpeg"))
];

let speciesnet = SpeciesNet::new()?;
let classifications = speciesnet.classify(&instances)?;

Running the ensemble and geofence of the pipeline.

NOTE: This function differs from other functions where it operates on each instance of prediction, instead of taking the vector of predictions or instance like other API.

use std::path::PathBuf;

use speciesnet_core::{
    classifier::ClassificationBundle,
    detector::{BoundingBox, Category, Detection},
};
use speciesnet::SpeciesNet;

let instances_json_path = "./instances.json";
let detector_file_path = "./output_detector.json";
let classifier_file_path = "./output_classifier.json";

let speciesnet = SpeciesNet::new()?;
let ensembles = speciesnet.ensemble(
    instances_json_path,
    detector_file_path,
    classifier_file_path,
)?;

Re-exports

pub use speciesnet::SpeciesNet;

Modules

error

model_info

speciesnet