wip

.envrc

@@ -0,0 +1 @@
+use flake

.gitignore

@@ -1 +1,2 @@
 /target
+.direnv

.vscode/extensions.json

@@ -0,0 +1,9 @@
+{
+    "recommendations": [
+        "fill-labs.dependi",
+        "jnoortheen.nix-ide",
+        "mkhl.direnv",
+        "rust-lang.rust-analyzer",
+        "tamasfe.even-better-toml",
+    ]
+}

flake.lock

@@ -20,11 +20,11 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1768886240,
+        "lastModified": 1769789167,
-        "narHash": "sha256-C2TjvwYZ2VDxYWeqvvJ5XPPp6U7H66zeJlRaErJKoEM=",
+        "narHash": "sha256-kKB3bqYJU5nzYeIROI82Ef9VtTbu4uA3YydSk/Bioa8=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "80e4adbcf8992d3fd27ad4964fbb84907f9478b0",
+        "rev": "62c8382960464ceb98ea593cb8321a2cf8f9e3e5",
         "type": "github"
       },
       "original": {
@@ -62,11 +62,11 @@
         "nixpkgs": "nixpkgs_2"
       },
       "locked": {
-        "lastModified": 1768963622,
+        "lastModified": 1769915446,
-        "narHash": "sha256-n6VHiUgrYD9yjagzG6ncVVqFbVTsKCI54tR9PNAFCo0=",
+        "narHash": "sha256-f1F/umtX3ZD7fF9DHSloVHc0mnAT0ry0YK2jI/6E0aI=",
         "owner": "oxalica",
         "repo": "rust-overlay",
-        "rev": "2ef5b3362af585a83bafd34e7fc9b1f388c2e5e2",
+        "rev": "bc00300f010275e46feb3c3974df6587ff7b7808",
         "type": "github"
       },
       "original": {

flake.nix

@@ -20,7 +20,9 @@
         overlays = [ (import rust-overlay) ];
         pkgs = import nixpkgs { inherit system overlays; };
         stdenv = pkgs.stdenvAdapters.useMoldLinker pkgs.clangStdenv;
-        rustToolchain = pkgs.rust-bin.stable.latest.default;
+        rustToolchain = pkgs.rust-bin.stable.latest.default.override {
+          extensions = [ "rust-src" ];
+        };
 
         nativeBuildInputs = with pkgs; [
           rustToolchain

rust-toolchain.toml

@@ -1,2 +0,0 @@
-[toolchain]
-channel = "stable"

src/main.rs

@@ -9,7 +9,7 @@ mod model;
 mod postprocessing;
 mod preprocessing;
 
-use model::{ModelInfo, create_session, get_model_path};
+use model::{Model, create_session, get_model_path};
 use postprocessing::{apply_mask, create_side_by_side};
 use preprocessing::preprocess_image;
 
@@ -20,7 +20,17 @@ struct Args {
     #[arg(help = "URL of the image to download and process")]
     url: String,
 
-    #[arg(long, help = "Path to custom ONNX model")]
+    #[arg(
+        short,
+        long,
+        group = "model_selection",
+        value_enum,
+        default_value_t = Model::Bria,
+        help = "Model to use: 'bria' or 'birefnet-lite' (mutually exclusive with --model-path)"
+    )]
+    model: Model,
+
+    #[arg(long, group = "model_selection", help = "Path to custom ONNX model")]
     model_path: Option<String>,
 
     #[arg(long, help = "Skip model download, fail if not cached")]
@@ -50,25 +60,35 @@ fn main() -> Result<(), Box<dyn Error>> {
 
     // Load the image
     let img = image::load_from_memory(&bytes)?;
-    let (width, height) = img.dimensions();
+    let (img_width, img_height) = img.dimensions();
-    println!("Loaded image: {}x{}\n", width, height);
+    println!("Loaded image: {}x{}\n", img_width, img_height);
 
-    // Get model info
+    // Get model path - either from custom path or by selecting built-in model
-    let model_info = ModelInfo::BIREFNET_LITE;
+    let model_path = if let Some(custom_path) = args.model_path {
+        // Custom model path provided, use it directly
+        let model_path = std::path::PathBuf::from(&custom_path);
+        if !model_path.exists() {
+            return Err(format!("Custom model path does not exist: {}", custom_path).into());
+        }
+        println!("Using custom model: {}", custom_path);
+        model_path
+    } else {
+        // Use built-in model
+        let model_info = args.model.info();
         println!("Using model: {}", model_info.name);
-
+        get_model_path(&model_info, None, args.offline)?
-    // Get or download model
+    };
-    let model_path = get_model_path(&model_info, args.model_path.as_deref(), args.offline)?;
 
     // Create ONNX Runtime session
     let mut session = create_session(&model_path)?;
+    let input_name = session.inputs()[0].name().to_string();
 
-    // Preprocess image
+    // Preprocess
-    let input_tensor = preprocess_image(&img, model_info.input_size.0, model_info.input_size.1)?;
+    let input_tensor = preprocess_image(&img, 1024, 1024)?;
 
     // Run inference
     println!("Running inference...");
-    let outputs = session.run(ort::inputs!["input" => Tensor::from_array(input_tensor)?])?;
+    let outputs = session.run(ort::inputs![input_name => Tensor::from_array(input_tensor)?])?;
 
     // Extract mask output
     let mask_output = &outputs[0];

src/model.rs

@@ -1,3 +1,5 @@
+use clap::ValueEnum;
+use ort::execution_providers::CUDAExecutionProvider;
 use ort::session::{Session, builder::GraphOptimizationLevel};
 use sha2::{Digest, Sha256};
 use std::error::Error;
@@ -5,21 +7,41 @@ use std::fs;
 use std::io::Write;
 use std::path::{Path, PathBuf};
 
+#[derive(Debug, Clone, Copy, PartialEq, Eq, ValueEnum)]
+#[clap(rename_all = "kebab-case")]
+pub enum Model {
+    BiRefNetLite,
+    Bria,
+}
+
+impl Model {
+    pub fn info(&self) -> &ModelInfo {
+        match self {
+            Model::BiRefNetLite => &ModelInfo::BIREFNET_LITE,
+            Model::Bria => &ModelInfo::BRIA,
+        }
+    }
+}
+
 /// Model metadata
 pub struct ModelInfo {
     pub name: &'static str,
     pub url: &'static str,
     pub sha256: Option<&'static str>,
-    pub input_size: (u32, u32),
 }
 
 impl ModelInfo {
     /// BiRefNet General Lite model
     pub const BIREFNET_LITE: ModelInfo = ModelInfo {
         name: "birefnet-general-lite",
-        url: "https://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png",
+        url: "https://github.com/danielgatis/rembg/releases/download/v0.0.0/BiRefNet-general-bb_swin_v1_tiny-epoch_232.onnx",
-        sha256: None, // We'll skip verification for now
+        sha256: Some("5600024376f572a557870a5eb0afb1e5961636bef4e1e22132025467d0f03333"),
-        input_size: (1024, 1024),
+    };
+
+    pub const BRIA: ModelInfo = ModelInfo {
+        name: "bria",
+        url: "https://github.com/danielgatis/rembg/releases/download/v0.0.0/bria-rmbg-2.0.onnx",
+        sha256: Some("5b486f08200f513f460da46dd701db5fbb47d79b4be4b708a19444bcd4e79958"),
     };
 }
 
@@ -156,16 +178,17 @@ pub fn get_model_path(
     Ok(model_path)
 }
 
-/// Create an ONNX Runtime session from model path
+/// Create an ONNX Runtime session from model path with CUDA backend
 pub fn create_session(model_path: &Path) -> Result<Session, Box<dyn Error>> {
-    println!("Loading model into ONNX Runtime...");
+    println!("Loading model into ONNX Runtime with CUDA backend...");
 
     let session = Session::builder()?
+        .with_execution_providers([CUDAExecutionProvider::default().build()])?
         .with_optimization_level(GraphOptimizationLevel::Level3)?
         .with_intra_threads(4)?
         .commit_from_file(model_path)?;
 
-    println!("Model loaded successfully!");
+    println!("Model loaded successfully with CUDA!");
 
     Ok(session)
 }