feat: Added stuff

Cargo.toml

@@ -22,6 +22,7 @@ mnn-bridge = { git = "https://github.com/uttarayan21/mnn-rs", version = "0.1.0",
 mnn-sync = { git = "https://github.com/uttarayan21/mnn-rs", version = "0.1.0", features = [
     "tracing",
 ], branch = "restructure-tensor-type" }
+nalgebra = { version = "0.34.0", default-features = false, features = ["std"] }
 
 [package]
 name = "detector"
@@ -35,7 +36,7 @@ clap_complete = "4.5"
 error-stack = "0.5"
 fast_image_resize = "5.2.0"
 image = "0.25.6"
-nalgebra = "0.33.2"
+nalgebra = { workspace = true }
 ndarray = "0.16.1"
 ndarray-image = { workspace = true }
 ndarray-resize = { workspace = true }
@@ -52,6 +53,7 @@ bounding-box = { version = "0.1.0", path = "bounding-box" }
 color = "0.3.1"
 itertools = "0.14.0"
 ordered-float = "5.0.0"
+ort = "2.0.0-rc.10"
 
 [profile.release]
 debug = true

Makefile.toml

@@ -0,0 +1,27 @@
+[tasks.convert_facenet]
+command = "MNNConvert"
+args = [
+    "-f",
+    "ONNX",
+    "--modelFile",
+    "models/facenet.onnx",
+    "--MNNModel",
+    "models/facenet.mnn",
+    "--fp16",
+    "--bizCode",
+    "MNN",
+]
+
+[tasks.convert_retinaface]
+command = "MNNConvert"
+args = [
+    "-f",
+    "ONNX",
+    "--modelFile",
+    "models/retinaface.onnx",
+    "--MNNModel",
+    "models/retinaface.mnn",
+    "--fp16",
+    "--bizCode",
+    "MNN",
+]

bounding-box/Cargo.toml

@@ -6,7 +6,7 @@ edition = "2024"
 [dependencies]
 color = "0.3.1"
 itertools = "0.14.0"
-nalgebra = "0.33.2"
+nalgebra = { workspace = true }
 ndarray = { version = "0.16.1", optional = true }
 num = "0.4.3"
 ordered-float = "5.0.0"

flake.nix

@@ -27,7 +27,8 @@
     };
   };
 
-  outputs = {
+  outputs =
+    {
       self,
       crane,
       flake-utils,
@@ -40,7 +41,8 @@
       ...
     }:
     flake-utils.lib.eachDefaultSystem (
-      system: let
+      system:
+      let
         pkgs = import nixpkgs {
           inherit system;
           overlays = [
@@ -61,24 +63,39 @@
 
         stableToolchain = pkgs.rust-bin.stable.latest.default;
         stableToolchainWithLLvmTools = stableToolchain.override {
-          extensions = ["rust-src" "llvm-tools"];
+          extensions = [
+            "rust-src"
+            "llvm-tools"
+          ];
         };
         stableToolchainWithRustAnalyzer = stableToolchain.override {
-          extensions = ["rust-src" "rust-analyzer"];
+          extensions = [
+            "rust-src"
+            "rust-analyzer"
+          ];
         };
         craneLib = (crane.mkLib pkgs).overrideToolchain stableToolchain;
         craneLibLLvmTools = (crane.mkLib pkgs).overrideToolchain stableToolchainWithLLvmTools;
 
-        src = let
+        src =
+          let
             filterBySuffix = path: exts: lib.any (ext: lib.hasSuffix ext path) exts;
-          sourceFilters = path: type: (craneLib.filterCargoSources path type) || filterBySuffix path [".c" ".h" ".hpp" ".cpp" ".cc"];
+            sourceFilters =
+              path: type:
+              (craneLib.filterCargoSources path type)
+              || filterBySuffix path [
+                ".c"
+                ".h"
+                ".hpp"
+                ".cpp"
+                ".cc"
+              ];
           in
           lib.cleanSourceWith {
             filter = sourceFilters;
             src = ./.;
           };
-        commonArgs =
-          {
+        commonArgs = {
           inherit src;
           pname = name;
           stdenv = pkgs.clangStdenv;
@@ -88,7 +105,8 @@
           #   cmake
           #   llvmPackages.libclang.lib
           # ];
-            buildInputs = with pkgs;
+          buildInputs =
+            with pkgs;
             [ ]
             ++ (lib.optionals pkgs.stdenv.isDarwin [
               libiconv
@@ -99,14 +117,16 @@
           # BINDGEN_EXTRA_CLANG_ARGS = "-I${pkgs.llvmPackages.libclang.lib}/lib/clang/18/include";
         });
         cargoArtifacts = craneLib.buildPackage commonArgs;
-      in {
-        checks =
+      in
       {
-            "${name}-clippy" = craneLib.cargoClippy (commonArgs
+        checks = {
+          "${name}-clippy" = craneLib.cargoClippy (
+            commonArgs
             // {
               inherit cargoArtifacts;
               cargoClippyExtraArgs = "--all-targets -- --deny warnings";
-              });
+            }
+          );
           "${name}-docs" = craneLib.cargoDoc (commonArgs // { inherit cargoArtifacts; });
           "${name}-fmt" = craneLib.cargoFmt { inherit src; };
           "${name}-toml-fmt" = craneLib.taploFmt {
@@ -121,20 +141,26 @@
           "${name}-deny" = craneLib.cargoDeny {
             inherit src;
           };
-            "${name}-nextest" = craneLib.cargoNextest (commonArgs
+          "${name}-nextest" = craneLib.cargoNextest (
+            commonArgs
             // {
               inherit cargoArtifacts;
               partitions = 1;
               partitionType = "count";
-              });
+            }
+          );
         }
         // lib.optionalAttrs (!pkgs.stdenv.isDarwin) {
           "${name}-llvm-cov" = craneLibLLvmTools.cargoLlvmCov (commonArgs // { inherit cargoArtifacts; });
         };
 
-        packages = let
-          pkg = craneLib.buildPackage (commonArgs
-            // {inherit cargoArtifacts;}
+        packages =
+          let
+            pkg = craneLib.buildPackage (
+              commonArgs
+              // {
+                inherit cargoArtifacts;
+              }
               // {
                 nativeBuildInputs = with pkgs; [
                   installShellFiles
@@ -145,28 +171,34 @@
                     --fish <($out/bin/${name} completions fish) \
                     --zsh <($out/bin/${name} completions zsh)
                 '';
-            });
-        in {
+              }
+            );
+          in
+          {
             "${name}" = pkg;
             default = pkg;
           };
 
         devShells = {
-          default = pkgs.mkShell.override {stdenv = pkgs.clangStdenv;} (commonArgs
+          default = pkgs.mkShell.override { stdenv = pkgs.clangStdenv; } (
+            commonArgs
             // {
               LLDB_DEBUGSERVER_PATH = "/Applications/Xcode.app/Contents/SharedFrameworks/LLDB.framework/Versions/A/Resources/debugserver";
-              packages = with pkgs;
+              packages =
+                with pkgs;
                 [
                   stableToolchainWithRustAnalyzer
                   cargo-nextest
                   cargo-deny
                   cmake
                   mnn
+                  cargo-make
                 ]
                 ++ (lib.optionals pkgs.stdenv.isDarwin [
                   apple-sdk_13
                 ]);
-            });
+            }
+          );
         };
       }
     )

src/cli.rs

@@ -48,6 +48,8 @@ pub struct Detect {
     pub model_type: Models,
     #[clap(short, long)]
     pub output: Option<PathBuf>,
+    #[clap(short, long, default_value = "cpu")]
+    pub forward_type: mnn::ForwardType,
     #[clap(short, long, default_value_t = 0.8)]
     pub threshold: f32,
     #[clap(short, long, default_value_t = 0.3)]

src/facedet/retinaface.rs

@@ -246,7 +246,56 @@ impl FaceDetectionModelOutput {
     }
 }
 
+pub struct FaceDetectionBuilder {
+    schedule_config: Option<mnn::ScheduleConfig>,
+    backend_config: Option<mnn::BackendConfig>,
+    model: mnn::Interpreter,
+}
+
+impl FaceDetectionBuilder {
+    pub fn new(model: impl AsRef<[u8]>) -> Result<Self> {
+        Ok(Self {
+            schedule_config: None,
+            backend_config: None,
+            model: mnn::Interpreter::from_bytes(model.as_ref())
+                .map_err(|e| e.into_inner())
+                .change_context(Error)
+                .attach_printable("Failed to load model from bytes")?,
+        })
+    }
+
+    pub fn with_forward_type(mut self, forward_type: mnn::ForwardType) -> Self {
+        self.schedule_config
+            .get_or_insert_default()
+            .set_type(forward_type);
+        self
+    }
+
+    pub fn with_schedule_config(mut self, config: mnn::ScheduleConfig) -> Self {
+        self.schedule_config = Some(config);
+        self
+    }
+
+    pub fn with_backend_config(mut self, config: mnn::BackendConfig) -> Self {
+        self.backend_config = Some(config);
+        self
+    }
+
+    pub fn build(self) -> Result<FaceDetection> {
+        let model = self.model;
+        let sc = self.schedule_config.unwrap_or_default();
+        let handle = mnn_sync::SessionHandle::new(model, sc)
+            .change_context(Error)
+            .attach_printable("Failed to create session handle")?;
+        Ok(FaceDetection { handle })
+    }
+}
+
 impl FaceDetection {
+    pub fn builder<T: AsRef<[u8]>>()
+    -> fn(T) -> std::result::Result<FaceDetectionBuilder, Report<Error>> {
+        FaceDetectionBuilder::new
+    }
     pub fn new(path: impl AsRef<Path>) -> Result<Self> {
         let model = std::fs::read(path)
             .change_context(Error)
@@ -267,7 +316,7 @@ impl FaceDetection {
             .attach_printable("Failed to set cache file")?;
         let bc = mnn::BackendConfig::default().with_memory_mode(mnn::MemoryMode::High);
         let sc = mnn::ScheduleConfig::new()
-            .with_type(mnn::ForwardType::CPU)
+            .with_type(mnn::ForwardType::Metal)
             .with_backend_config(bc);
         tracing::info!("Creating session handle for face detection model");
         let handle = mnn_sync::SessionHandle::new(model, sc)

src/faceembed/facenet.rs

@@ -2,11 +2,57 @@ use crate::errors::*;
 use mnn_bridge::ndarray::*;
 use ndarray::{Array1, Array2, ArrayView3, ArrayView4};
 use std::path::Path;
+mod mnn_impl;
+mod ort_impl;
 
 #[derive(Debug)]
 pub struct EmbeddingGenerator {
     handle: mnn_sync::SessionHandle,
 }
+pub struct EmbeddingGeneratorBuilder {
+    schedule_config: Option<mnn::ScheduleConfig>,
+    backend_config: Option<mnn::BackendConfig>,
+    model: mnn::Interpreter,
+}
+
+impl EmbeddingGeneratorBuilder {
+    pub fn new(model: impl AsRef<[u8]>) -> Result<Self> {
+        Ok(Self {
+            schedule_config: None,
+            backend_config: None,
+            model: mnn::Interpreter::from_bytes(model.as_ref())
+                .map_err(|e| e.into_inner())
+                .change_context(Error)
+                .attach_printable("Failed to load model from bytes")?,
+        })
+    }
+
+    pub fn with_forward_type(mut self, forward_type: mnn::ForwardType) -> Self {
+        self.schedule_config
+            .get_or_insert_default()
+            .set_type(forward_type);
+        self
+    }
+
+    pub fn with_schedule_config(mut self, config: mnn::ScheduleConfig) -> Self {
+        self.schedule_config = Some(config);
+        self
+    }
+
+    pub fn with_backend_config(mut self, config: mnn::BackendConfig) -> Self {
+        self.backend_config = Some(config);
+        self
+    }
+
+    pub fn build(self) -> Result<EmbeddingGenerator> {
+        let model = self.model;
+        let sc = self.schedule_config.unwrap_or_default();
+        let handle = mnn_sync::SessionHandle::new(model, sc)
+            .change_context(Error)
+            .attach_printable("Failed to create session handle")?;
+        Ok(EmbeddingGenerator { handle })
+    }
+}
 
 impl EmbeddingGenerator {
     const INPUT_NAME: &'static str = "serving_default_input_6:0";
@@ -18,6 +64,11 @@ impl EmbeddingGenerator {
         Self::new_from_bytes(&model)
     }
 
+    pub fn builder<T: AsRef<[u8]>>()
+    -> fn(T) -> std::result::Result<EmbeddingGeneratorBuilder, Report<Error>> {
+        EmbeddingGeneratorBuilder::new
+    }
+
     pub fn new_from_bytes(model: &[u8]) -> Result<Self> {
         tracing::info!("Loading face embedding model from bytes");
         let mut model = mnn::Interpreter::from_bytes(model)
@@ -57,16 +108,24 @@ impl EmbeddingGenerator {
                 tracing::trace!("Image Tensor shape: {:?}", tensor.shape());
                 let (intptr, session) = sr.both_mut();
                 tracing::trace!("Copying input tensor to host");
-                unsafe {
+                let needs_resize = unsafe {
                     let mut input = intptr.input_unresized::<f32>(session, Self::INPUT_NAME)?;
                     tracing::trace!("Input shape: {:?}", input.shape());
                     if *input.shape() != shape {
                         tracing::trace!("Resizing input tensor to shape: {:?}", shape);
                         // input.resize(shape);
                         intptr.resize_tensor(input.view_mut(), shape);
+                        true
+                    } else {
+                        false
                     }
-                }
+                };
+                if needs_resize {
+                    tracing::trace!("Resized input tensor to shape: {:?}", shape);
+                    let now = std::time::Instant::now();
                     intptr.resize_session(session);
+                    tracing::trace!("Session resized in {:?}", now.elapsed());
+                }
                 let mut input = intptr.input::<f32>(session, Self::INPUT_NAME)?;
                 tracing::trace!("Input shape: {:?}", input.shape());
                 input.copy_from_host_tensor(tensor.view())?;

src/faceembed/facenet/mnn_impl.rs

@@ -0,0 +1 @@
+

src/faceembed/facenet/ort_impl.rs

@@ -0,0 +1,65 @@
+use crate::errors::{Result, *};
+use ndarray::*;
+use ort::*;
+use std::path::Path;
+
+#[derive(Debug)]
+pub struct EmbeddingGenerator {
+    handle: ort::session::Session,
+}
+
+// impl EmbeddingGeneratorBuilder {
+//     pub fn new(model: impl AsRef<[u8]>) -> Result<Self> {
+//         Ok(Self {
+//             schedule_config: None,
+//             backend_config: None,
+//             model: mnn::Interpreter::from_bytes(model.as_ref())
+//                 .map_err(|e| e.into_inner())
+//                 .change_context(Error)
+//                 .attach_printable("Failed to load model from bytes")?,
+//         })
+//     }
+//
+//     pub fn with_forward_type(mut self, forward_type: mnn::ForwardType) -> Self {
+//         self.schedule_config
+//             .get_or_insert_default()
+//             .set_type(forward_type);
+//         self
+//     }
+//
+//     pub fn with_schedule_config(mut self, config: mnn::ScheduleConfig) -> Self {
+//         self.schedule_config = Some(config);
+//         self
+//     }
+//
+//     pub fn with_backend_config(mut self, config: mnn::BackendConfig) -> Self {
+//         self.backend_config = Some(config);
+//         self
+//     }
+//
+//     pub fn build(self) -> Result<EmbeddingGenerator> {
+//         let model = self.model;
+//         let sc = self.schedule_config.unwrap_or_default();
+//         let handle = mnn_sync::SessionHandle::new(model, sc)
+//             .change_context(Error)
+//             .attach_printable("Failed to create session handle")?;
+//         Ok(EmbeddingGenerator { handle })
+//     }
+// }
+
+impl EmbeddingGenerator {
+    const INPUT_NAME: &'static str = "serving_default_input_6:0";
+    const OUTPUT_NAME: &'static str = "StatefulPartitionedCall:0";
+    pub fn new(path: impl AsRef<Path>) -> Result<Self> {
+        let model = std::fs::read(path)
+            .change_context(Error)
+            .attach_printable("Failed to read model file")?;
+        Self::new_from_bytes(&model)
+    }
+
+    pub fn new_from_bytes(model: impl AsRef<[u8]>) -> Result<Self> {
+        todo!()
+    }
+
+    // pub fn run_models(&self, face: ArrayView4<u8>) -> Result<Array2<f32>> {}
+}

src/main.rs

@@ -4,10 +4,12 @@ use bounding_box::roi::MultiRoi;
 use detector::{facedet::retinaface::FaceDetectionConfig, faceembed};
 use errors::*;
 use fast_image_resize::ResizeOptions;
-use nalgebra::zero;
+use ndarray::*;
 use ndarray_image::*;
+use ndarray_resize::NdFir;
 const RETINAFACE_MODEL: &[u8] = include_bytes!("../models/retinaface.mnn");
 const FACENET_MODEL: &[u8] = include_bytes!("../models/facenet.mnn");
+const CHUNK_SIZE: usize = 8;
 pub fn main() -> Result<()> {
     tracing_subscriber::fmt()
         .with_env_filter("trace")
@@ -19,10 +21,16 @@ pub fn main() -> Result<()> {
     match args.cmd {
         cli::SubCommand::Detect(detect) => {
             use detector::facedet;
-            let retinaface = facedet::retinaface::FaceDetection::new_from_bytes(RETINAFACE_MODEL)
+            let retinaface = facedet::retinaface::FaceDetection::builder()(RETINAFACE_MODEL)
+                .change_context(Error)?
+                .with_forward_type(detect.forward_type)
+                .build()
                 .change_context(errors::Error)
                 .attach_printable("Failed to create face detection model")?;
-            let facenet = faceembed::facenet::EmbeddingGenerator::new_from_bytes(FACENET_MODEL)
+            let facenet = faceembed::facenet::EmbeddingGenerator::builder()(FACENET_MODEL)
+                .change_context(Error)?
+                .with_forward_type(detect.forward_type)
+                .build()
                 .change_context(errors::Error)
                 .attach_printable("Failed to create face embedding model")?;
             let image = image::open(detect.image).change_context(Error)?;
@@ -45,8 +53,6 @@ pub fn main() -> Result<()> {
                 use bounding_box::draw::*;
                 array.draw(bbox, color::palette::css::GREEN_YELLOW.to_rgba8(), 1);
             }
-            use ndarray::{Array2, Array3, Array4, Axis};
-            use ndarray_resize::NdFir;
             let face_rois = array
                 .view()
                 .multi_roi(&output.bbox)
@@ -68,21 +74,19 @@ pub fn main() -> Result<()> {
                 .collect::<Result<Vec<_>>>()?;
             let face_roi_views = face_rois.iter().map(|roi| roi.view()).collect::<Vec<_>>();
 
+            let chunk_size = CHUNK_SIZE;
             let embeddings = face_roi_views
-                .chunks(8)
+                .chunks(chunk_size)
                 .map(|chunk| {
                     tracing::info!("Processing chunk of size: {}", chunk.len());
 
                     if chunk.len() < 8 {
                         tracing::warn!("Chunk size is less than 8, padding with zeros");
                         let zeros = Array3::zeros((512, 512, 3));
-                        let padded: Vec<ndarray::ArrayView3<'_, u8>> = chunk
-                            .iter()
-                            .cloned()
-                            .chain(core::iter::repeat(zeros.view()))
-                            .take(8)
-                            .collect();
-                        let face_rois: Array4<u8> = ndarray::stack(Axis(0), padded.as_slice())
+                        let zero_array = core::iter::repeat(zeros.view())
+                            .take(chunk_size)
+                            .collect::<Vec<_>>();
+                        let face_rois: Array4<u8> = ndarray::stack(Axis(0), zero_array.as_slice())
                             .change_context(errors::Error)
                             .attach_printable("Failed to stack rois together")?;
                         let output = facenet.run_models(face_rois.view()).change_context(Error)?;