rename local_ocr to ocr
This commit is contained in:
parent
eaed474ccf
commit
8baad566aa
|
@ -14,7 +14,7 @@ use crate::{
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capture,
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config::Config,
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image_processing::{self, extract_and_filter, hash_image, Region, to_png_bytes},
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ocr,
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remote_ocr,
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state::{AppState, DebugOcrFrame, LapState, RaceState, SharedAppState}, learned_tracks::get_track_hash,
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};
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@ -159,7 +159,7 @@ fn run_loop_once(capturer: &mut Capturer, state: &SharedAppState) -> Result<()>
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locked.should_sample_ocr_data
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)
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};
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let ocr_results = ocr::ocr_all_regions(&frame, config.clone(), ocr_cache, should_sample);
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let ocr_results = remote_ocr::ocr_all_regions(&frame, config.clone(), ocr_cache, should_sample);
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if state.lock().unwrap().debug_frames {
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let debug_frames = save_frames_from(&frame, config.as_ref(), &ocr_results);
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135
src/local_ocr.rs
135
src/local_ocr.rs
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@ -1,135 +0,0 @@
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use image::{Rgb, RgbImage};
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use img_hash::{image::GenericImageView};
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use crate::image_processing;
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#[derive(Debug)]
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struct BoundingBox {
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x: u32,
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y: u32,
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width: u32,
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height: u32,
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}
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fn column_has_any_dark(image: &RgbImage, x: u32) -> bool {
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for y in 0..image.height() {
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let [r, g, b] = image.get_pixel(x, y).0;
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if r < 100 && g < 100 && b < 100 {
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return true;
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}
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}
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false
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}
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fn row_has_any_dark(image: &RgbImage, y: u32, start_x: u32, width: u32) -> bool {
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for x in start_x..(start_x + width) {
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let [r, g, b] = image.get_pixel(x, y).0;
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if r < 100 && g < 100 && b < 100 {
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return true;
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}
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}
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false
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}
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fn take_while<F: Fn(u32) -> bool>(x: &mut u32, max: u32, f: F) {
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while *x < max && f(*x) {
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*x += 1;
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}
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}
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fn get_character_bounding_boxes(image: &RgbImage) -> Vec<BoundingBox> {
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let mut x = 0;
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let mut boxes = Vec::new();
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while x < image.width() {
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take_while(&mut x, image.width(), |x| !column_has_any_dark(image, x));
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let start_x = x;
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take_while(&mut x, image.width(), |x| column_has_any_dark(image, x));
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let width = x - start_x;
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if width >= 1 {
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let mut y = 0;
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take_while(&mut y, image.height(), |y| {
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!row_has_any_dark(image, y, start_x, width)
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});
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let start_y = y;
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let mut inverse_y = 0;
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take_while(&mut inverse_y, image.height(), |y| {
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!row_has_any_dark(image, image.height() - 1 - y, start_x, width)
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});
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let end_y = image.height() - inverse_y;
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let height = end_y - start_y;
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if height >= 1 {
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boxes.push(BoundingBox {
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x: start_x,
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y: start_y,
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width,
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height,
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});
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}
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}
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}
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boxes
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}
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fn trim_to_bounding_box(image: &RgbImage, bounding_box: &BoundingBox) -> RgbImage {
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const PADDING: u32 = 2;
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let mut buffer = RgbImage::from_pixel(
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bounding_box.width + 2 * PADDING,
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bounding_box.height + 2 * PADDING,
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Rgb([0xFF, 0xFF, 0xFF]),
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);
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for y in 0..bounding_box.height {
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for x in 0..bounding_box.width {
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buffer.put_pixel(
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x + PADDING,
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y + PADDING,
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*image.get_pixel(bounding_box.x + x, bounding_box.y + y),
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);
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}
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}
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buffer
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}
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pub fn bounding_box_images(image: &RgbImage) -> Vec<RgbImage> {
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let mut trimmed = Vec::new();
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let boxes = get_character_bounding_boxes(image);
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for bounding_box in boxes {
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trimmed.push(trim_to_bounding_box(image, &bounding_box));
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}
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trimmed
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}
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pub fn compute_box_hashes(image: &RgbImage) -> Vec<String> {
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let mut hashes = Vec::new();
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let boxes = get_character_bounding_boxes(image);
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for bounding_box in boxes {
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let trimmed = trim_to_bounding_box(image, &bounding_box);
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hashes.push(image_processing::hash_image(&trimmed))
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}
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hashes
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}
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#[test]
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fn test_bounding_boxes() {
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let image_bytes = include_bytes!("test_data/test-image-2.png");
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let image = image::load_from_memory(image_bytes).unwrap().to_rgb8();
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let boxes = get_character_bounding_boxes(&image);
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assert_eq!(boxes.len(), 10);
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assert_ne!(boxes[0].x, 0);
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assert_ne!(boxes[0].y, 0);
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assert_ne!(boxes[0].height, 0);
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assert_ne!(boxes[0].width, 0);
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}
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#[test]
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fn test_box_hashes() {
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let image_bytes = include_bytes!("test_data/test-image-2.png");
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let image = image::load_from_memory(image_bytes).unwrap().to_rgb8();
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let hashes = compute_box_hashes(&image);
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assert_eq!(hashes.len(), 10);
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}
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10
src/main.rs
10
src/main.rs
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@ -4,8 +4,8 @@ mod analysis;
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mod capture;
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mod config;
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mod image_processing;
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mod local_ocr;
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mod ocr;
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mod remote_ocr;
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mod state;
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mod stats_writer;
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mod training_ui;
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@ -125,9 +125,6 @@ struct DebugLap {
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struct UiState {
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config_load_err: Option<String>,
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hash_to_learn: String,
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value_to_learn: String,
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debug_lap: Option<DebugLap>,
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}
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@ -289,7 +286,7 @@ fn open_debug_lap(
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) {
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if let Some(screenshot_bytes) = &lap.screenshot {
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let screenshot = from_png_bytes(screenshot_bytes);
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let ocr_results = ocr::ocr_all_regions(&screenshot, config.clone(), ocr_cache, false);
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let ocr_results = remote_ocr::ocr_all_regions(&screenshot, config.clone(), ocr_cache, false);
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let debug_lap = DebugLap {
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screenshot: RetainedImage::from_image_bytes("debug-lap", &to_png_bytes(&screenshot))
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.unwrap(),
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@ -308,9 +305,6 @@ fn show_combo_box(ui: &mut Ui, name: &str, label: &str, options: &[String], valu
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*value = options[index].clone();
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}
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fn save_learned_track(_learned_tracks: &mut Arc<LearnedTracks>, _track: &str, _hash: &str) {
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}
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impl eframe::App for AppUi {
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fn update(&mut self, ctx: &egui::Context, _frame: &mut eframe::Frame) {
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let mut state = self.state.lock().unwrap();
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229
src/ocr.rs
229
src/ocr.rs
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@ -1,121 +1,134 @@
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use std::{
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collections::HashMap,
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sync::{Arc, Mutex, RwLock},
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};
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use image::{Rgb, RgbImage};
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use anyhow::Result;
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use image::RgbImage;
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use serde::{Deserialize, Serialize};
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use crate::image_processing;
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use crate::{
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config::Config,
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image_processing::{extract_and_filter, hash_image},
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state::OcrCache,
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};
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#[derive(Serialize, Deserialize, Debug)]
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pub struct OcrRegion {
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pub confidence: f64,
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pub value: String,
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#[derive(Debug)]
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struct BoundingBox {
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x: u32,
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y: u32,
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width: u32,
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height: u32,
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}
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#[derive(Serialize, Deserialize, Debug)]
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struct OcrResult {
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regions: Vec<OcrRegion>,
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error: Option<String>,
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}
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async fn run_ocr(image: &RgbImage, url: &str) -> Result<Option<String>> {
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let client = reqwest::Client::new();
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let response = client
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.post(url)
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.body(crate::image_processing::to_png_bytes(image))
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.send()
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.await?;
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if !response.status().is_success() {
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eprintln!("failed to run OCR query");
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anyhow::bail!("failed to run OCR query")
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}
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let result: OcrResult = response.json().await?;
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let result = if result.regions.is_empty() {
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None
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} else {
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let mut buffer = String::new();
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for r in &result.regions {
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buffer += &r.value;
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}
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Some(buffer)
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};
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Ok(result)
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}
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async fn run_ocr_cached(
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ocr_cache: Arc<RwLock<HashMap<String, Option<String>>>>,
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hash: String,
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region: &crate::image_processing::Region,
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config: Arc<Config>,
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filtered_image: &image::ImageBuffer<image::Rgb<u8>, Vec<u8>>,
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) -> Option<String> {
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let cached = {
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let locked = ocr_cache.read().unwrap();
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locked.get(&hash).cloned()
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};
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let use_cache = region.use_ocr_cache.unwrap_or(true) && config.use_ocr_cache.unwrap_or(true);
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if let Some(cached) = cached {
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if use_cache {
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return cached;
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fn column_has_any_dark(image: &RgbImage, x: u32) -> bool {
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for y in 0..image.height() {
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let [r, g, b] = image.get_pixel(x, y).0;
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if r < 100 && g < 100 && b < 100 {
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return true;
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}
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}
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match run_ocr(filtered_image, &config.ocr_server_endpoint).await {
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Ok(v) => {
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if use_cache {
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ocr_cache.write().unwrap().insert(hash.clone(), v.clone());
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false
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}
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fn row_has_any_dark(image: &RgbImage, y: u32, start_x: u32, width: u32) -> bool {
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for x in start_x..(start_x + width) {
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let [r, g, b] = image.get_pixel(x, y).0;
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if r < 100 && g < 100 && b < 100 {
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return true;
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}
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}
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false
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}
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fn take_while<F: Fn(u32) -> bool>(x: &mut u32, max: u32, f: F) {
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while *x < max && f(*x) {
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*x += 1;
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}
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}
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fn get_character_bounding_boxes(image: &RgbImage) -> Vec<BoundingBox> {
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let mut x = 0;
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let mut boxes = Vec::new();
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while x < image.width() {
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take_while(&mut x, image.width(), |x| !column_has_any_dark(image, x));
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let start_x = x;
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take_while(&mut x, image.width(), |x| column_has_any_dark(image, x));
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let width = x - start_x;
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if width >= 1 {
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let mut y = 0;
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take_while(&mut y, image.height(), |y| {
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!row_has_any_dark(image, y, start_x, width)
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});
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let start_y = y;
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let mut inverse_y = 0;
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take_while(&mut inverse_y, image.height(), |y| {
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!row_has_any_dark(image, image.height() - 1 - y, start_x, width)
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});
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let end_y = image.height() - inverse_y;
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let height = end_y - start_y;
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if height >= 1 {
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boxes.push(BoundingBox {
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x: start_x,
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y: start_y,
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width,
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height,
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});
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}
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v
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}
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Err(_) => None,
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}
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boxes
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}
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#[tokio::main(flavor = "current_thread")]
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pub async fn ocr_all_regions(
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image: &RgbImage,
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config: Arc<Config>,
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ocr_cache: Arc<OcrCache>,
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should_sample: bool,
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) -> HashMap<String, Option<String>> {
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let results = Arc::new(Mutex::new(HashMap::new()));
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let mut handles = Vec::new();
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for region in &config.ocr_regions {
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let filtered_image = extract_and_filter(image, region);
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let region = region.clone();
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let results = results.clone();
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let config = config.clone();
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let ocr_cache = ocr_cache.clone();
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handles.push(tokio::spawn(async move {
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let filtered_image = filtered_image;
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let hash = hash_image(&filtered_image);
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let value =
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run_ocr_cached(ocr_cache, hash, ®ion, config.clone(), &filtered_image).await;
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if let Some(sample_fraction) = &config.dump_frame_fraction {
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if rand::random::<f64>() < *sample_fraction && should_sample {
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let file_id = rand::random::<usize>();
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let img_filename = format!("ocr_data/{}.png", file_id);
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filtered_image.save(img_filename).unwrap();
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let value_filename = format!("ocr_data/{}.txt", file_id);
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std::fs::write(value_filename, value.clone().unwrap_or_default()).unwrap();
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}
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}
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results.lock().unwrap().insert(region.name, value);
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}));
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fn trim_to_bounding_box(image: &RgbImage, bounding_box: &BoundingBox) -> RgbImage {
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const PADDING: u32 = 2;
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let mut buffer = RgbImage::from_pixel(
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bounding_box.width + 2 * PADDING,
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bounding_box.height + 2 * PADDING,
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Rgb([0xFF, 0xFF, 0xFF]),
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);
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for y in 0..bounding_box.height {
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for x in 0..bounding_box.width {
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buffer.put_pixel(
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x + PADDING,
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y + PADDING,
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*image.get_pixel(bounding_box.x + x, bounding_box.y + y),
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);
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}
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}
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for handle in handles {
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handle.await.expect("failed to join task in OCR");
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}
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let results = results.lock().unwrap().clone();
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results
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buffer
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}
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pub fn bounding_box_images(image: &RgbImage) -> Vec<RgbImage> {
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let mut trimmed = Vec::new();
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let boxes = get_character_bounding_boxes(image);
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for bounding_box in boxes {
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trimmed.push(trim_to_bounding_box(image, &bounding_box));
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}
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trimmed
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}
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pub fn compute_box_hashes(image: &RgbImage) -> Vec<String> {
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let mut hashes = Vec::new();
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|
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let boxes = get_character_bounding_boxes(image);
|
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for bounding_box in boxes {
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let trimmed = trim_to_bounding_box(image, &bounding_box);
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hashes.push(image_processing::hash_image(&trimmed))
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}
|
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hashes
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}
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|
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#[test]
|
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fn test_bounding_boxes() {
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let image_bytes = include_bytes!("test_data/test-image-2.png");
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let image = image::load_from_memory(image_bytes).unwrap().to_rgb8();
|
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let boxes = get_character_bounding_boxes(&image);
|
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assert_eq!(boxes.len(), 10);
|
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assert_ne!(boxes[0].x, 0);
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assert_ne!(boxes[0].y, 0);
|
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assert_ne!(boxes[0].height, 0);
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assert_ne!(boxes[0].width, 0);
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}
|
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|
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#[test]
|
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fn test_box_hashes() {
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let image_bytes = include_bytes!("test_data/test-image-2.png");
|
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let image = image::load_from_memory(image_bytes).unwrap().to_rgb8();
|
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let hashes = compute_box_hashes(&image);
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assert_eq!(hashes.len(), 10);
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}
|
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|
|
|
@ -0,0 +1,121 @@
|
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use std::{
|
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collections::HashMap,
|
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sync::{Arc, Mutex, RwLock},
|
||||
};
|
||||
|
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use anyhow::Result;
|
||||
use image::RgbImage;
|
||||
use serde::{Deserialize, Serialize};
|
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|
||||
use crate::{
|
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config::Config,
|
||||
image_processing::{extract_and_filter, hash_image},
|
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state::OcrCache,
|
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};
|
||||
|
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#[derive(Serialize, Deserialize, Debug)]
|
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pub struct OcrRegion {
|
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pub confidence: f64,
|
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pub value: String,
|
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}
|
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|
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#[derive(Serialize, Deserialize, Debug)]
|
||||
struct OcrResult {
|
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regions: Vec<OcrRegion>,
|
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error: Option<String>,
|
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}
|
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|
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async fn run_ocr(image: &RgbImage, url: &str) -> Result<Option<String>> {
|
||||
let client = reqwest::Client::new();
|
||||
let response = client
|
||||
.post(url)
|
||||
.body(crate::image_processing::to_png_bytes(image))
|
||||
.send()
|
||||
.await?;
|
||||
|
||||
if !response.status().is_success() {
|
||||
eprintln!("failed to run OCR query");
|
||||
anyhow::bail!("failed to run OCR query")
|
||||
}
|
||||
let result: OcrResult = response.json().await?;
|
||||
let result = if result.regions.is_empty() {
|
||||
None
|
||||
} else {
|
||||
let mut buffer = String::new();
|
||||
for r in &result.regions {
|
||||
buffer += &r.value;
|
||||
}
|
||||
Some(buffer)
|
||||
};
|
||||
Ok(result)
|
||||
}
|
||||
|
||||
async fn run_ocr_cached(
|
||||
ocr_cache: Arc<RwLock<HashMap<String, Option<String>>>>,
|
||||
hash: String,
|
||||
region: &crate::image_processing::Region,
|
||||
config: Arc<Config>,
|
||||
filtered_image: &image::ImageBuffer<image::Rgb<u8>, Vec<u8>>,
|
||||
) -> Option<String> {
|
||||
let cached = {
|
||||
let locked = ocr_cache.read().unwrap();
|
||||
locked.get(&hash).cloned()
|
||||
};
|
||||
let use_cache = region.use_ocr_cache.unwrap_or(true) && config.use_ocr_cache.unwrap_or(true);
|
||||
if let Some(cached) = cached {
|
||||
if use_cache {
|
||||
return cached;
|
||||
}
|
||||
}
|
||||
match run_ocr(filtered_image, &config.ocr_server_endpoint).await {
|
||||
Ok(v) => {
|
||||
if use_cache {
|
||||
ocr_cache.write().unwrap().insert(hash.clone(), v.clone());
|
||||
}
|
||||
v
|
||||
}
|
||||
Err(_) => None,
|
||||
}
|
||||
}
|
||||
|
||||
#[tokio::main(flavor = "current_thread")]
|
||||
pub async fn ocr_all_regions(
|
||||
image: &RgbImage,
|
||||
config: Arc<Config>,
|
||||
ocr_cache: Arc<OcrCache>,
|
||||
should_sample: bool,
|
||||
) -> HashMap<String, Option<String>> {
|
||||
let results = Arc::new(Mutex::new(HashMap::new()));
|
||||
|
||||
let mut handles = Vec::new();
|
||||
for region in &config.ocr_regions {
|
||||
let filtered_image = extract_and_filter(image, region);
|
||||
let region = region.clone();
|
||||
let results = results.clone();
|
||||
let config = config.clone();
|
||||
let ocr_cache = ocr_cache.clone();
|
||||
handles.push(tokio::spawn(async move {
|
||||
let filtered_image = filtered_image;
|
||||
let hash = hash_image(&filtered_image);
|
||||
let value =
|
||||
run_ocr_cached(ocr_cache, hash, ®ion, config.clone(), &filtered_image).await;
|
||||
|
||||
if let Some(sample_fraction) = &config.dump_frame_fraction {
|
||||
if rand::random::<f64>() < *sample_fraction && should_sample {
|
||||
let file_id = rand::random::<usize>();
|
||||
let img_filename = format!("ocr_data/{}.png", file_id);
|
||||
filtered_image.save(img_filename).unwrap();
|
||||
let value_filename = format!("ocr_data/{}.txt", file_id);
|
||||
std::fs::write(value_filename, value.clone().unwrap_or_default()).unwrap();
|
||||
}
|
||||
}
|
||||
results.lock().unwrap().insert(region.name, value);
|
||||
}));
|
||||
}
|
||||
for handle in handles {
|
||||
handle.await.expect("failed to join task in OCR");
|
||||
}
|
||||
|
||||
let results = results.lock().unwrap().clone();
|
||||
results
|
||||
}
|
10
src/state.rs
10
src/state.rs
|
@ -66,13 +66,11 @@ impl LapState {
|
|||
fn median_wear(values: Vec<Option<usize>>) -> Option<usize> {
|
||||
let mut wear_values = Vec::new();
|
||||
let mut last_value = 100;
|
||||
for val in values {
|
||||
if let Some(val) = val {
|
||||
if val < last_value {
|
||||
wear_values.push(last_value - val);
|
||||
}
|
||||
last_value = val;
|
||||
for val in values.into_iter().flatten() {
|
||||
if val < last_value {
|
||||
wear_values.push(last_value - val);
|
||||
}
|
||||
last_value = val;
|
||||
}
|
||||
wear_values.sort_unstable();
|
||||
wear_values.get(wear_values.len() / 2).cloned()
|
||||
|
|
|
@ -10,7 +10,7 @@ use eframe::{
|
|||
use egui_extras::RetainedImage;
|
||||
use image::RgbImage;
|
||||
|
||||
use crate::{image_processing::to_png_bytes, local_ocr};
|
||||
use crate::{image_processing::to_png_bytes, ocr};
|
||||
|
||||
#[derive(Default)]
|
||||
struct TrainingUi {
|
||||
|
@ -24,7 +24,6 @@ struct TrainingUi {
|
|||
struct TrainingImage {
|
||||
img_file: PathBuf,
|
||||
data_file: PathBuf,
|
||||
image: RgbImage,
|
||||
text: String,
|
||||
|
||||
ui_image: RetainedImage,
|
||||
|
@ -74,15 +73,14 @@ fn get_training_data() -> Vec<TrainingImage> {
|
|||
let ocr_value = String::from_utf8(std::fs::read(&ocr_file).unwrap()).unwrap();
|
||||
let ui_image = load_retained_image(&image);
|
||||
|
||||
let char_images = local_ocr::bounding_box_images(&image)
|
||||
let char_images = ocr::bounding_box_images(&image)
|
||||
.iter()
|
||||
.map(load_retained_image)
|
||||
.collect();
|
||||
let char_hashes = local_ocr::compute_box_hashes(&image);
|
||||
let char_hashes = ocr::compute_box_hashes(&image);
|
||||
data.push(TrainingImage {
|
||||
img_file,
|
||||
data_file: ocr_file,
|
||||
image,
|
||||
text: ocr_value,
|
||||
ui_image,
|
||||
char_images,
|
||||
|
@ -170,7 +168,7 @@ impl eframe::App for TrainingUi {
|
|||
.write(true)
|
||||
.open("learned_chars.txt")
|
||||
.unwrap();
|
||||
file.write(buffer.as_bytes()).unwrap();
|
||||
file.write_all(buffer.as_bytes()).unwrap();
|
||||
}
|
||||
|
||||
current_image.ui_image.show(ui);
|
||||
|
|
Loading…
Reference in New Issue