flystem-usls/examples/clip/README.md

This demo showcases how to use CLIP to compute similarity between texts and images, which can be employed for image-to-text or text-to-image retrieval tasks.

Quick Start

cargo run -r --example clip

Or you can manully

1.Donwload CLIP ONNX Model

clip-b32-visual
clip-b32-textual

2. Specify the ONNX model path in main.rs

    // visual
    let options_visual = Options::default()
        .with_model("VISUAL_MODEL")  // <= modify this
        .with_i00((1, 1, 4).into())
        .with_profile(false);

    // textual
    let options_textual = Options::default()
        .with_model("TEXTUAL_MODEL")  // <= modify this
        .with_i00((1, 1, 4).into())
        .with_profile(false);

3. Then, run

cargo run -r --example clip

Results

(90.11472%) ./examples/clip/images/carrot.jpg => 几个胡萝卜 
[0.04573484, 0.0048218793, 0.0011618224, 0.90114725, 0.0036694852, 0.031348046, 0.0121166315]

(94.07785%) ./examples/clip/images/peoples.jpg => Some people holding wine glasses in a restaurant 
[0.050406333, 0.0011632168, 0.0019338318, 0.0013227565, 0.003916758, 0.00047858112, 0.9407785]

(86.59852%) ./examples/clip/images/doll.jpg => There is a doll with red hair and a clock on a table 
[0.07032883, 0.00053773675, 0.0006372929, 0.06066096, 0.0007378078, 0.8659852, 0.0011121632]

TODO

• TensorRT support for textual model