1use candle_core::{Device, Result, Tensor};
24use image::DynamicImage;
25mod ops;
26mod pad;
27mod transforms;
28pub(crate) mod utils;
29
30pub use ops::{get_resize_image_size, make_pixel_mask, pad};
31pub use pad::{pad_to_max_edge, pad_to_max_image_size};
32pub use transforms::{InterpolateResize, Normalize, Rescale, ToTensor, ToTensorNoNorm};
33
34pub trait ImageTransform {
36 type Input;
37 type Output;
38
39 fn map(&self, x: &Self::Input, device: &Device) -> Result<Self::Output>;
40}
41
42#[derive(Clone, Copy)]
45pub struct Transforms<'a> {
46 pub input: &'a dyn ImageTransform<Input = DynamicImage, Output = Tensor>,
47 pub inner_transforms: &'a [&'a dyn ImageTransform<Input = Tensor, Output = Tensor>],
48}
49
50#[derive(Clone, Copy)]
52pub struct TensorTransforms<'a> {
53 pub inner_transforms: &'a [&'a dyn ImageTransform<Input = Tensor, Output = Tensor>],
54}
55
56pub trait ApplyTransforms<'a> {
58 fn apply(&self, transforms: Transforms<'a>, device: &Device) -> Result<Tensor>;
59}
60
61impl<'a> ApplyTransforms<'a> for DynamicImage {
62 fn apply(&self, transforms: Transforms<'a>, device: &Device) -> Result<Tensor> {
63 let mut res = transforms.input.map(self, device)?;
64 for transform in transforms.inner_transforms {
65 res = transform.map(&res, device)?;
66 }
67 Ok(res)
68 }
69}
70
71pub trait ApplyTensorTransforms<'a> {
73 fn apply(&self, transforms: TensorTransforms<'a>, device: &Device) -> Result<Tensor>;
74}
75
76impl<'a> ApplyTensorTransforms<'a> for Tensor {
77 fn apply(&self, transforms: TensorTransforms<'a>, device: &Device) -> Result<Tensor> {
78 let mut res = self.clone();
79 for transform in transforms.inner_transforms {
80 res = transform.map(&res, device)?;
81 }
82 Ok(res)
83 }
84}