fix: use ort rc

Cargo.toml

@@ -60,7 +60,6 @@ features = [
 
 [dependencies.ort]
 version = "2.0.0-rc.0"
-git = "https://github.com/pykeio/ort.git"
 default-features = false
 features = [
   "cuda",

benches/modnet.rs

@@ -75,7 +75,7 @@ fn modnet_output_to_luma_images_benchmark(c: &mut Criterion) {
 
     let session = Session::builder().unwrap()
         .with_optimization_level(GraphOptimizationLevel::Level3).unwrap()
-        .commit_from_file("assets/modnet_photographic_portrait_matting.onnx").unwrap();
+        .with_model_from_file("assets/modnet_photographic_portrait_matting.onnx").unwrap();
 
     let data = vec![0u8; (1920 * 1080 * 4) as usize];
     let image: Image = Image::new(

src/lib.rs

@@ -88,7 +88,7 @@ impl AssetLoader for OnnxLoader {
                     // TODO: add session configuration
                     let session = Session::builder()?
                         .with_optimization_level(GraphOptimizationLevel::Level3)?
-                        .commit_from_memory(&bytes)?;
+                        .with_model_from_memory(&bytes)?;
 
                     Ok(Onnx {
                         session: Arc::new(Mutex::new(Some(session))),

src/models/modnet.rs

@@ -7,7 +7,8 @@ use rayon::prelude::*;
 pub fn modnet_output_to_luma_images(
     output_value: &ort::Value,
 ) -> Vec<Image> {
-    let data = output_value.extract_tensor::<f32>().unwrap();
+    let tensor = output_value.extract_tensor::<f32>().unwrap();
+    let data = tensor.view();
 
     let shape = data.shape();
     let batch_size = shape[0];