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MobileCLIP models S1 and S2 (#2454)

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* Allow loading images with given std and mean

* OpenCLIP text encoder component

* Two MobileCLIP models

* Clippy fixes.

---------

Co-authored-by: Laurent <laurent.mazare@gmail.com>
This commit is contained in:
Jani Monoses
2024-08-29 16:38:58 +03:00
committed by GitHub
parent 29e25c458d
commit 86613c00e2
8 changed files with 608 additions and 10 deletions
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35
candle-examples/src/imagenet.rs
View File

@ -1,23 +1,42 @@
use candle::{Device, Result, Tensor};
/// Loads an image from disk using the image crate at the requested resolution.
// This returns a tensor with shape (3, res, res). imagenet normalization is applied.
pub fn load_image<P: AsRef<std::path::Path>>(p: P, res: u32) -> Result<Tensor> {
pub const IMAGENET_MEAN: [f32; 3] = [0.485f32, 0.456, 0.406];
pub const IMAGENET_STD: [f32; 3] = [0.229f32, 0.224, 0.225];
/// Loads an image from disk using the image crate at the requested resolution,
/// using the given std and mean parameters.
/// This returns a tensor with shape (3, res, res). imagenet normalization is applied.
pub fn load_image_with_std_mean<P: AsRef<std::path::Path>>(
p: P,
res: usize,
mean: &[f32; 3],
std: &[f32; 3],
) -> Result<Tensor> {
let img = image::ImageReader::open(p)?
.decode()
.map_err(candle::Error::wrap)?
.resize_to_fill(res, res, image::imageops::FilterType::Triangle);
.resize_to_fill(
res as u32,
res as u32,
image::imageops::FilterType::Triangle,
);
let img = img.to_rgb8();
let data = img.into_raw();
let data = Tensor::from_vec(data, (res as usize, res as usize, 3), &Device::Cpu)?
.permute((2, 0, 1))?;
let mean = Tensor::new(&[0.485f32, 0.456, 0.406], &Device::Cpu)?.reshape((3, 1, 1))?;
let std = Tensor::new(&[0.229f32, 0.224, 0.225], &Device::Cpu)?.reshape((3, 1, 1))?;
let data = Tensor::from_vec(data, (res, res, 3), &Device::Cpu)?.permute((2, 0, 1))?;
let mean = Tensor::new(mean, &Device::Cpu)?.reshape((3, 1, 1))?;
let std = Tensor::new(std, &Device::Cpu)?.reshape((3, 1, 1))?;
(data.to_dtype(candle::DType::F32)? / 255.)?
.broadcast_sub(&mean)?
.broadcast_div(&std)
}
/// Loads an image from disk using the image crate at the requested resolution.
/// This returns a tensor with shape (3, res, res). imagenet normalization is applied.
pub fn load_image<P: AsRef<std::path::Path>>(p: P, res: usize) -> Result<Tensor> {
load_image_with_std_mean(p, res, &IMAGENET_MEAN, &IMAGENET_STD)
}
/// Loads an image from disk using the image crate, this returns a tensor with shape
/// (3, 224, 224). imagenet normalization is applied.
pub fn load_image224<P: AsRef<std::path::Path>>(p: P) -> Result<Tensor> {