Add DINOv2Reg4 + PlantCLEF2024 (#2293)

* Add: DINOv2Reg4 with PlantCLEF2024 weights and example ( See https://arxiv.org/abs/2309.16588 and https://zenodo.org/records/10848263 )

* Remove extra files + update README to download them + remove extra lines

* minor fix (README remove extra spaces)

* minor fix (README: Fix image url)

* Modif: Add back interpolate_pos_encoding() + fix when no interpolation + remove extra comments + Update README ( source image changed and so the predictions )

* Fix: Improve code lisibility with '$ cargo clippy' and '$ cargo fmt'

* Another clippy fix.

---------

Co-authored-by: x-VEspit <vincent.espitalier@cirad.fr>
Co-authored-by: laurent <laurent.mazare@gmail.com>

candle-examples/examples/dinov2reg4/README.md

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+# candle-dinov2-reg4
+
+[DINOv2-reg4](https://arxiv.org/abs/2309.16588) is the lastest version of DINOv2 with registers.
+In this example, it is used as an plant species classifier: the model returns the
+probability for the image to belong to each of the 7806 PlantCLEF2024 categories.
+
+## Running some example
+
+```bash
+# Download classes names and a plant picture to identify
+curl https://huggingface.co/vincent-espitalier/dino-v2-reg4-with-plantclef2024-weights/raw/main/species_id_mapping.txt --output candle-examples/examples/dinov2reg4/species_id_mapping.txt
+curl https://bs.plantnet.org/image/o/bd2d3830ac3270218ba82fd24e2290becd01317c --output candle-examples/examples/dinov2reg4/bd2d3830ac3270218ba82fd24e2290becd01317c.jpg
+
+# Perform inference
+cargo run --example dinov2reg4 --release -- --image candle-examples/examples/dinov2reg4/bd2d3830ac3270218ba82fd24e2290becd01317c.jpg
+
+> Orchis simia Lam.       : 45.55%
+> Orchis × bergonii Nanteuil: 9.80%
+> Orchis italica Poir.    : 9.66%
+> Orchis × angusticruris Franch.: 2.76%
+> Orchis × bivonae Tod.   : 2.54%
+
+```
+
+![Orchis Simia](https://bs.plantnet.org/image/o/bd2d3830ac3270218ba82fd24e2290becd01317c)

candle-examples/examples/dinov2reg4/main.rs

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+//! DINOv2 reg4 finetuned on PlantCLEF 2024
+//! https://arxiv.org/abs/2309.16588
+//! https://huggingface.co/spaces/BVRA/PlantCLEF2024
+//! https://zenodo.org/records/10848263
+
+#[cfg(feature = "mkl")]
+extern crate intel_mkl_src;
+
+#[cfg(feature = "accelerate")]
+extern crate accelerate_src;
+
+use clap::Parser;
+
+use candle::{DType, IndexOp, D};
+use candle_nn::{Module, VarBuilder};
+use candle_transformers::models::dinov2reg4;
+
+#[derive(Parser)]
+struct Args {
+    #[arg(long)]
+    model: Option<String>,
+
+    #[arg(long)]
+    image: String,
+
+    /// Run on CPU rather than on GPU.
+    #[arg(long)]
+    cpu: bool,
+}
+
+pub fn main() -> anyhow::Result<()> {
+    let args = Args::parse();
+
+    let device = candle_examples::device(args.cpu)?;
+
+    let image = candle_examples::imagenet::load_image518(args.image)?.to_device(&device)?;
+    println!("loaded image {image:?}");
+
+    let f_species_id_mapping = "candle-examples/examples/dinov2reg4/species_id_mapping.txt";
+    let classes: Vec<String> = std::fs::read_to_string(f_species_id_mapping)
+        .expect("missing classes file")
+        .split('\n')
+        .map(|s| s.to_string())
+        .collect();
+
+    let model_file = match args.model {
+        None => {
+            let api = hf_hub::api::sync::Api::new()?;
+            let api =
+                api.model("vincent-espitalier/dino-v2-reg4-with-plantclef2024-weights".into());
+            api.get(
+                "vit_base_patch14_reg4_dinov2_lvd142m_pc24_onlyclassifier_then_all.safetensors",
+            )?
+        }
+        Some(model) => model.into(),
+    };
+    let vb = unsafe { VarBuilder::from_mmaped_safetensors(&[model_file], DType::F32, &device)? };
+    let model = dinov2reg4::vit_base(vb)?;
+    println!("model built");
+    let logits = model.forward(&image.unsqueeze(0)?)?;
+    let prs = candle_nn::ops::softmax(&logits, D::Minus1)?
+        .i(0)?
+        .to_vec1::<f32>()?;
+    let mut prs = prs.iter().enumerate().collect::<Vec<_>>();
+    prs.sort_by(|(_, p1), (_, p2)| p2.total_cmp(p1));
+    for &(category_idx, pr) in prs.iter().take(5) {
+        println!("{:24}: {:.2}%", classes[category_idx], 100. * pr);
+    }
+    Ok(())
+}