lama remove
This commit is contained in:
Julian Freeman
3
.gitignore
vendored
3
.gitignore
vendored
@@ -22,3 +22,6 @@ dist-ssr
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368
src-tauri/Cargo.lock
generated
368
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||||
version = "2.11.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "897b2245f0b511c87893af39b033e5ca9cce68824c4d7e7630b5a1d339658d02"
|
||||
dependencies = [
|
||||
"bitflags 2.10.0",
|
||||
"core-foundation 0.9.4",
|
||||
"core-foundation-sys",
|
||||
"libc",
|
||||
"security-framework-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "security-framework-sys"
|
||||
version = "2.15.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "cc1f0cbffaac4852523ce30d8bd3c5cdc873501d96ff467ca09b6767bb8cd5c0"
|
||||
dependencies = [
|
||||
"core-foundation-sys",
|
||||
"libc",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "selectors"
|
||||
version = "0.24.0"
|
||||
@@ -3699,6 +3978,17 @@ dependencies = [
|
||||
"windows-sys 0.60.2",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "socks"
|
||||
version = "0.3.4"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "f0c3dbbd9ae980613c6dd8e28a9407b50509d3803b57624d5dfe8315218cd58b"
|
||||
dependencies = [
|
||||
"byteorder",
|
||||
"libc",
|
||||
"winapi",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "softbuffer"
|
||||
version = "0.4.8"
|
||||
@@ -3858,7 +4148,7 @@ checksum = "f3a753bdc39c07b192151523a3f77cd0394aa75413802c883a0f6f6a0e5ee2e7"
|
||||
dependencies = [
|
||||
"bitflags 2.10.0",
|
||||
"block2",
|
||||
"core-foundation",
|
||||
"core-foundation 0.10.1",
|
||||
"core-graphics",
|
||||
"crossbeam-channel",
|
||||
"dispatch",
|
||||
@@ -4180,6 +4470,19 @@ dependencies = [
|
||||
"toml 0.9.11+spec-1.1.0",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tempfile"
|
||||
version = "3.24.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "655da9c7eb6305c55742045d5a8d2037996d61d8de95806335c7c86ce0f82e9c"
|
||||
dependencies = [
|
||||
"fastrand",
|
||||
"getrandom 0.3.4",
|
||||
"once_cell",
|
||||
"rustix",
|
||||
"windows-sys 0.61.2",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tendril"
|
||||
version = "0.4.3"
|
||||
@@ -4572,6 +4875,36 @@ version = "1.12.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "f6ccf251212114b54433ec949fd6a7841275f9ada20dddd2f29e9ceea4501493"
|
||||
|
||||
[[package]]
|
||||
name = "ureq"
|
||||
version = "3.1.4"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "d39cb1dbab692d82a977c0392ffac19e188bd9186a9f32806f0aaa859d75585a"
|
||||
dependencies = [
|
||||
"base64 0.22.1",
|
||||
"der",
|
||||
"log",
|
||||
"native-tls",
|
||||
"percent-encoding",
|
||||
"rustls-pki-types",
|
||||
"socks",
|
||||
"ureq-proto",
|
||||
"utf-8",
|
||||
"webpki-root-certs",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "ureq-proto"
|
||||
version = "0.5.3"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "d81f9efa9df032be5934a46a068815a10a042b494b6a58cb0a1a97bb5467ed6f"
|
||||
dependencies = [
|
||||
"base64 0.22.1",
|
||||
"http",
|
||||
"httparse",
|
||||
"log",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "url"
|
||||
version = "2.5.8"
|
||||
@@ -4632,6 +4965,12 @@ dependencies = [
|
||||
"wasm-bindgen",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "vcpkg"
|
||||
version = "0.2.15"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "accd4ea62f7bb7a82fe23066fb0957d48ef677f6eeb8215f372f52e48bb32426"
|
||||
|
||||
[[package]]
|
||||
name = "version-compare"
|
||||
version = "0.2.1"
|
||||
@@ -4783,6 +5122,8 @@ dependencies = [
|
||||
"ab_glyph",
|
||||
"image",
|
||||
"imageproc",
|
||||
"ndarray 0.16.1",
|
||||
"ort",
|
||||
"rayon",
|
||||
"serde",
|
||||
"serde_json",
|
||||
@@ -4845,6 +5186,15 @@ dependencies = [
|
||||
"system-deps",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "webpki-root-certs"
|
||||
version = "1.0.5"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "36a29fc0408b113f68cf32637857ab740edfafdf460c326cd2afaa2d84cc05dc"
|
||||
dependencies = [
|
||||
"rustls-pki-types",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "webview2-com"
|
||||
version = "0.38.2"
|
||||
@@ -5498,6 +5848,12 @@ dependencies = [
|
||||
"synstructure",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zeroize"
|
||||
version = "1.8.2"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "b97154e67e32c85465826e8bcc1c59429aaaf107c1e4a9e53c8d8ccd5eff88d0"
|
||||
|
||||
[[package]]
|
||||
name = "zerotrie"
|
||||
version = "0.2.3"
|
||||
|
||||
@@ -26,4 +26,6 @@ rayon = "1.10"
|
||||
tauri-plugin-dialog = "2"
|
||||
imageproc = "0.25"
|
||||
ab_glyph = "0.2.23"
|
||||
ort = { version = "=2.0.0-rc.11", features = ["load-dynamic"] }
|
||||
ndarray = "0.16"
|
||||
|
||||
|
||||
139
src-tauri/src/lama.rs
Normal file
139
src-tauri/src/lama.rs
Normal file
@@ -0,0 +1,139 @@
|
||||
use image::{Rgba, RgbaImage};
|
||||
use ort::session::{Session, builder::GraphOptimizationLevel};
|
||||
use ort::value::Value;
|
||||
|
||||
pub fn run_lama_inpainting(
|
||||
model_path: &std::path::Path,
|
||||
input_image: &RgbaImage,
|
||||
mask_image: &image::GrayImage,
|
||||
) -> Result<RgbaImage, String> {
|
||||
// 1. Initialize Session
|
||||
let mut session = Session::builder()
|
||||
.map_err(|e| format!("Failed to create session builder: {}", e))?
|
||||
.with_optimization_level(GraphOptimizationLevel::Level3)
|
||||
.map_err(|e| format!("Failed to set opt level: {}", e))?
|
||||
.with_intra_threads(4)
|
||||
.map_err(|e| format!("Failed to set threads: {}", e))?
|
||||
.commit_from_file(model_path)
|
||||
.map_err(|e| format!("Failed to load model from {:?}: {}", model_path, e))?;
|
||||
|
||||
// 2. Preprocess
|
||||
let target_size = (512, 512);
|
||||
|
||||
let resized_img = image::imageops::resize(input_image, target_size.0, target_size.1, image::imageops::FilterType::Triangle);
|
||||
let resized_mask = image::imageops::resize(mask_image, target_size.0, target_size.1, image::imageops::FilterType::Triangle);
|
||||
|
||||
// Flatten Image to Vec<f32> (NCHW: 1, 3, 512, 512)
|
||||
let channel_stride = (target_size.0 * target_size.1) as usize;
|
||||
let mut input_data: Vec<f32> = Vec::with_capacity(1 * 3 * channel_stride);
|
||||
|
||||
// We need to fill R plane, then G plane, then B plane
|
||||
let mut r_plane: Vec<f32> = Vec::with_capacity(channel_stride);
|
||||
let mut g_plane: Vec<f32> = Vec::with_capacity(channel_stride);
|
||||
let mut b_plane: Vec<f32> = Vec::with_capacity(channel_stride);
|
||||
|
||||
for (_x, _y, pixel) in resized_img.enumerate_pixels() {
|
||||
r_plane.push(pixel[0] as f32 / 255.0f32);
|
||||
g_plane.push(pixel[1] as f32 / 255.0f32);
|
||||
b_plane.push(pixel[2] as f32 / 255.0f32);
|
||||
}
|
||||
|
||||
input_data.extend(r_plane);
|
||||
input_data.extend(g_plane);
|
||||
input_data.extend(b_plane);
|
||||
|
||||
// Flatten Mask to Vec<f32> (NCHW: 1, 1, 512, 512)
|
||||
let mut mask_data: Vec<f32> = Vec::with_capacity(channel_stride);
|
||||
for (_x, _y, pixel) in resized_mask.enumerate_pixels() {
|
||||
let val = if pixel[0] > 127 { 1.0f32 } else { 0.0f32 };
|
||||
mask_data.push(val);
|
||||
}
|
||||
|
||||
// 3. Inference
|
||||
// Use (Shape, Data) tuple which implements OwnedTensorArrayData
|
||||
// Explicitly casting shape to i64 is correct for ORT
|
||||
let input_shape = vec![1, 3, target_size.1 as i64, target_size.0 as i64];
|
||||
let input_value = Value::from_array((input_shape, input_data))
|
||||
.map_err(|e| format!("Failed to create input tensor: {}", e))?;
|
||||
|
||||
let mask_shape = vec![1, 1, target_size.1 as i64, target_size.0 as i64];
|
||||
let mask_value = Value::from_array((mask_shape, mask_data))
|
||||
.map_err(|e| format!("Failed to create mask tensor: {}", e))?;
|
||||
|
||||
let inputs = ort::inputs![
|
||||
"image" => input_value,
|
||||
"mask" => mask_value
|
||||
];
|
||||
|
||||
let outputs = session.run(inputs).map_err(|e| format!("Inference failed: {}", e))?;
|
||||
|
||||
// Get output tensor
|
||||
// Just take the first output.
|
||||
let output_tensor_ref = outputs.values().next()
|
||||
.ok_or("No output tensor produced by model")?;
|
||||
|
||||
let (shape, data) = output_tensor_ref.try_extract_tensor::<f32>()
|
||||
.map_err(|e| format!("Failed to extract tensor: {}", e))?;
|
||||
|
||||
// 4. Post-process
|
||||
let mut output_img_512 = RgbaImage::new(target_size.0, target_size.1);
|
||||
|
||||
if shape.len() < 4 {
|
||||
return Err(format!("Unexpected output shape: {:?}", shape));
|
||||
}
|
||||
|
||||
let h = 512;
|
||||
let w = 512;
|
||||
let channel_stride = (h * w) as usize;
|
||||
|
||||
// Safety check on data length
|
||||
if data.len() < (3 * h * w) as usize {
|
||||
return Err(format!("Output data size mismatch. Expected {}, got {}", 3*h*w, data.len()));
|
||||
}
|
||||
|
||||
// Auto-detect output range
|
||||
// If values are already in 0-255 range, multiplying by 255 results in all white image.
|
||||
let mut max_val = 0.0f32;
|
||||
// Check a subset of pixels to avoid iterating everything if speed is key, but full scan is safer and fast enough.
|
||||
for v in data.iter().take(1000) {
|
||||
if *v > max_val { max_val = *v; }
|
||||
}
|
||||
|
||||
// Heuristic: if max > 2.0, it's likely 0-255. If it's <= 1.0 (or slightly above due to overshoot), it's 0-1.
|
||||
// LaMa usually outputs -1..1 or 0..1. But some exports differ.
|
||||
// Let's assume if any value is > 5.0, it is definitely not 0-1 normalized.
|
||||
let scale_factor = if max_val > 2.0 { 1.0 } else { 255.0 };
|
||||
|
||||
for y in 0..h {
|
||||
for x in 0..w {
|
||||
let offset = (y * w + x) as usize;
|
||||
|
||||
let r_idx = offset;
|
||||
let g_idx = offset + channel_stride;
|
||||
let b_idx = offset + 2 * channel_stride;
|
||||
|
||||
let r = (data[r_idx] * scale_factor).clamp(0.0, 255.0) as u8;
|
||||
let g = (data[g_idx] * scale_factor).clamp(0.0, 255.0) as u8;
|
||||
let b = (data[b_idx] * scale_factor).clamp(0.0, 255.0) as u8;
|
||||
|
||||
output_img_512.put_pixel(x, y, Rgba([r, g, b, 255]));
|
||||
}
|
||||
}
|
||||
|
||||
// Resize back to original
|
||||
let (orig_w, orig_h) = input_image.dimensions();
|
||||
let final_inpainted = image::imageops::resize(&output_img_512, orig_w, orig_h, image::imageops::FilterType::Lanczos3);
|
||||
|
||||
// 5. Blending
|
||||
let mut result_image = input_image.clone();
|
||||
|
||||
for y in 0..orig_h {
|
||||
for x in 0..orig_w {
|
||||
if mask_image.get_pixel(x, y)[0] > 127 {
|
||||
result_image.put_pixel(x, y, *final_inpainted.get_pixel(x, y));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Ok(result_image)
|
||||
}
|
||||
@@ -92,6 +92,9 @@ use rayon::prelude::*;
|
||||
use std::path::Path;
|
||||
use imageproc::drawing::draw_text_mut;
|
||||
use ab_glyph::{FontRef, PxScale};
|
||||
use tauri::{AppHandle, Manager};
|
||||
|
||||
mod lama;
|
||||
|
||||
// Embed the font to ensure it's always available without path issues
|
||||
const FONT_DATA: &[u8] = include_bytes!("../assets/fonts/Roboto-Regular.ttf");
|
||||
@@ -646,12 +649,12 @@ enum MaskStroke {
|
||||
}
|
||||
|
||||
#[tauri::command]
|
||||
async fn run_inpainting(path: String, strokes: Vec<MaskStroke>) -> Result<String, String> {
|
||||
async fn run_inpainting(app: AppHandle, path: String, strokes: Vec<MaskStroke>) -> Result<String, String> {
|
||||
let img = image::open(&path).map_err(|e| e.to_string())?.to_rgba8();
|
||||
let (width, height) = img.dimensions();
|
||||
|
||||
// 1. Create Mask
|
||||
let mut mask = vec![false; (width * height) as usize];
|
||||
// 1. Create Gray Mask (0 = keep, 255 = remove)
|
||||
let mut mask = image::GrayImage::new(width, height);
|
||||
|
||||
for stroke in strokes {
|
||||
match stroke {
|
||||
@@ -661,10 +664,11 @@ async fn run_inpainting(path: String, strokes: Vec<MaskStroke>) -> Result<String
|
||||
let w = (rect.w * width as f64) as i32;
|
||||
let h = (rect.h * height as f64) as i32;
|
||||
|
||||
// Draw 255 on mask
|
||||
for y in y1..(y1 + h) {
|
||||
for x in x1..(x1 + w) {
|
||||
if x >= 0 && x < width as i32 && y >= 0 && y < height as i32 {
|
||||
mask[(y as u32 * width + x as u32) as usize] = true;
|
||||
mask.put_pixel(x as u32, y as u32, image::Luma([255]));
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -699,7 +703,7 @@ async fn run_inpainting(path: String, strokes: Vec<MaskStroke>) -> Result<String
|
||||
let nx = cx + dx;
|
||||
let ny = cy + dy;
|
||||
if nx >= 0 && nx < width as i32 && ny >= 0 && ny < height as i32 {
|
||||
mask[(ny as u32 * width + nx as u32) as usize] = true;
|
||||
mask.put_pixel(nx as u32, ny as u32, image::Luma([255]));
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -710,76 +714,26 @@ async fn run_inpainting(path: String, strokes: Vec<MaskStroke>) -> Result<String
|
||||
}
|
||||
}
|
||||
|
||||
// 2. Diffusion Inpainting (Simple)
|
||||
// Iteratively replace masked pixels with average of non-masked neighbors
|
||||
// To make it converge, we update 'mask' as we go (treating filled pixels as valid source)
|
||||
// But standard diffusion uses double buffering.
|
||||
// For "Removing Text", simple inward filling works well.
|
||||
// 2. Resolve Model Path
|
||||
let model_path = app.path().resource_dir()
|
||||
.map_err(|e| e.to_string())?
|
||||
.join("resources")
|
||||
.join("lama_fp32.onnx");
|
||||
|
||||
let iterations = 30;
|
||||
let mut current_img = img.clone();
|
||||
let mut next_img = img.clone();
|
||||
|
||||
// Convert mask to a distance map-like state?
|
||||
// Or just simple neighbor average.
|
||||
|
||||
for _ in 0..iterations {
|
||||
let mut changed = false;
|
||||
for y in 0..height {
|
||||
for x in 0..width {
|
||||
let idx = (y * width + x) as usize;
|
||||
if mask[idx] {
|
||||
// It's a hole. Find valid neighbors.
|
||||
// Valid = Not in ORIGINAL mask (so we pull from original image)
|
||||
// OR processed in previous iteration?
|
||||
// Simple logic: Pull from 'current_img'.
|
||||
|
||||
let mut sum_r = 0u32;
|
||||
let mut sum_g = 0u32;
|
||||
let mut sum_b = 0u32;
|
||||
let mut count = 0;
|
||||
|
||||
// Check 4 neighbors
|
||||
let neighbors = [
|
||||
(x.wrapping_sub(1), y), (x + 1, y),
|
||||
(x, y.wrapping_sub(1)), (x, y + 1)
|
||||
];
|
||||
|
||||
for (nx, ny) in neighbors {
|
||||
if nx < width && ny < height {
|
||||
// Weighted check: If neighbor is ALSO masked, it contributes less?
|
||||
// Or just take everything.
|
||||
let pixel = current_img.get_pixel(nx, ny);
|
||||
sum_r += pixel[0] as u32;
|
||||
sum_g += pixel[1] as u32;
|
||||
sum_b += pixel[2] as u32;
|
||||
count += 1;
|
||||
}
|
||||
if !model_path.exists() {
|
||||
return Err("Model file 'lama_fp32.onnx' not found in resources.".to_string());
|
||||
}
|
||||
|
||||
if count > 0 {
|
||||
let avg = image::Rgba([
|
||||
(sum_r / count) as u8,
|
||||
(sum_g / count) as u8,
|
||||
(sum_b / count) as u8,
|
||||
255
|
||||
]);
|
||||
next_img.put_pixel(x, y, avg);
|
||||
changed = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
current_img = next_img.clone();
|
||||
if !changed { break; }
|
||||
}
|
||||
// 3. Run Inference
|
||||
// This is computationally heavy, maybe run in thread? Tauri async commands are already threaded.
|
||||
let result_img = lama::run_lama_inpainting(&model_path, &img, &mask)?;
|
||||
|
||||
// Save to temp
|
||||
let cache_dir = get_cache_dir();
|
||||
let file_name = format!("inpainted_{}.png", std::time::SystemTime::now().duration_since(std::time::UNIX_EPOCH).unwrap().as_millis());
|
||||
let out_path = cache_dir.join(file_name);
|
||||
|
||||
current_img.save(&out_path).map_err(|e| e.to_string())?;
|
||||
result_img.save(&out_path).map_err(|e| e.to_string())?;
|
||||
|
||||
Ok(out_path.to_string_lossy().to_string())
|
||||
}
|
||||
|
||||
@@ -28,6 +28,7 @@
|
||||
"bundle": {
|
||||
"active": true,
|
||||
"targets": "all",
|
||||
"resources": ["resources/lama_fp32.onnx"],
|
||||
"icon": [
|
||||
"icons/32x32.png",
|
||||
"icons/128x128.png",
|
||||
|
||||
Reference in New Issue
Block a user