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71 lines
2.0 KiB
Rust
71 lines
2.0 KiB
Rust
use anyhow::Result;
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use usls::{models::Clip, DataLoader, Ops, Options};
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#[derive(argh::FromArgs)]
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/// CLIP Example
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struct Args {
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/// device
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#[argh(option, default = "String::from(\"cpu:0\")")]
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device: String,
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}
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fn main() -> Result<()> {
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tracing_subscriber::fmt()
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.with_env_filter(tracing_subscriber::EnvFilter::from_default_env())
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.with_timer(tracing_subscriber::fmt::time::ChronoLocal::rfc_3339())
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.init();
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let args: Args = argh::from_env();
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// build model
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let options_visual = Options::jina_clip_v1_visual()
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// clip_vit_b32_visual()
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.with_model_device(args.device.as_str().try_into()?)
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.commit()?;
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let options_textual = Options::jina_clip_v1_textual()
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// clip_vit_b32_textual()
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.with_model_device(args.device.as_str().try_into()?)
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.commit()?;
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let mut model = Clip::new(options_visual, options_textual)?;
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// texts
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let texts = vec![
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"A photo of a dinosaur",
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"A photo of a cat",
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"A photo of a dog",
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"Some carrots",
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"There are some playing cards on a striped table cloth",
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"There is a doll with red hair and a clock on a table",
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"Some people holding wine glasses in a restaurant",
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];
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let feats_text = model.encode_texts(&texts)?; // [n, ndim]
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// load images
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let dl = DataLoader::new("./examples/clip/images")?.build()?;
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// run
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for images in dl {
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let feats_image = model.encode_images(&images)?;
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// use image to query texts
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let matrix = Ops::dot2(&feats_image, &feats_text)?;
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for i in 0..images.len() {
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let probs = &matrix[i];
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let (id, &score) = probs
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.iter()
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.enumerate()
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.reduce(|max, x| if x.1 > max.1 { x } else { max })
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.unwrap();
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println!(
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"({:?}%) {:?} => {} ",
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score * 100.0,
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images[i].source(),
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&texts[id]
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);
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}
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}
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Ok(())
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}
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