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dinov2 - read images from disk and compute the class probabilities (#503)
* Load the image from disk and convert it to a tensor. * Tweak the function name.
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@ -1,4 +1,4 @@
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use candle::{Device, Result};
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use candle::{Device, Result, Tensor};
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pub fn device(cpu: bool) -> Result<Device> {
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if cpu {
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@ -12,6 +12,42 @@ pub fn device(cpu: bool) -> Result<Device> {
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}
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}
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/// Loads an image from disk using the image crate, this returns a tensor with shape
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/// (3, 224, 224). imagenet normaliation is applied.
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pub fn load_image<P: AsRef<std::path::Path>>(p: P) -> Result<Tensor> {
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let img = image::io::Reader::open(p)?
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.decode()
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.map_err(candle::Error::wrap)?
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.resize_to_fill(224, 224, image::imageops::FilterType::Triangle);
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let img = img.to_rgb8();
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let data = img.into_raw();
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let data = Tensor::from_vec(data, (3, 224, 224), &Device::Cpu)?;
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let mean = Tensor::new(&[0.485f32, 0.456, 0.406], &Device::Cpu)?.reshape((3, 1, 1))?;
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let std = Tensor::new(&[0.229f32, 0.224, 0.225], &Device::Cpu)?.reshape((3, 1, 1))?;
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(data.to_dtype(candle::DType::F32)? / 255.)?
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.broadcast_sub(&mean)?
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.broadcast_div(&std)
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}
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/// Saves an image to disk using the image crate, this expects an input with shape
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/// (c, width, height).
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pub fn save_image<P: AsRef<std::path::Path>>(img: &Tensor, p: P) -> Result<()> {
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let p = p.as_ref();
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let (channel, width, height) = img.dims3()?;
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if channel != 3 {
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candle::bail!("save_image expects an input of shape (3, width, height)")
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}
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let img = img.transpose(0, 1)?.t()?.flatten_all()?;
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let pixels = img.to_vec1::<u8>()?;
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let image: image::ImageBuffer<image::Rgb<u8>, Vec<u8>> =
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match image::ImageBuffer::from_raw(width as u32, height as u32, pixels) {
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Some(image) => image,
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None => candle::bail!("error saving image {p:?}"),
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};
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image.save(p).map_err(candle::Error::wrap)?;
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Ok(())
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}
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#[cfg(test)]
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mod tests {
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// NOTE: Waiting on https://github.com/rust-lang/mdBook/pull/1856
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