liboxen 0.53.0

Oxen is a fast data version control system, built with machine learning training data in mind. Designed to handle terabytes of data with ease, using a workflow similar to git. Version both structured and unstructured data of any modality: text, images, video, audio, CSV, Parquet, JSONL, model checkpoints, and more. liboxen is the embeddable core library behind the oxen CLI and server, which power fine tuning and inference pipelines for multimodal LLMs, image models, and video models on Oxen.ai.
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use crate::error::OxenError;
use image::imageops;
use std::path::Path;

pub fn resize_and_save(
    src: impl AsRef<Path>,
    dst: impl AsRef<Path>,
    dims: u32,
) -> Result<(), OxenError> {
    let src_path = src.as_ref();
    let img = match image::open(src_path) {
        Ok(img) => img,
        Err(e) => return Err(OxenError::basic_str(e.to_string())),
    };

    // If the path ends in .jpg or .jpeg, convert to RGB
    let ext = src_path
        .extension()
        .unwrap_or_default()
        .to_ascii_lowercase();
    if ext == "jpg" || ext == "jpeg" {
        let img = img.to_rgb8();
        let resized = imageops::resize(&img, dims, dims, imageops::Nearest);
        resized.save(dst)?;
    } else {
        let resized = imageops::resize(&img, dims, dims, imageops::Nearest);
        resized.save(dst)?;
    }

    Ok(())
}