mirror of
https://github.com/starovoid/rxing.git
synced 2026-07-26 04:12:34 +00:00
does not build, mostly ported concentric_finder
This commit is contained in:
Henry Schimke
@@ -78,6 +78,7 @@ pub trait BitMatrixCursor {
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// }
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fn movedBy<T: BitMatrixCursor>(self, d: Point) -> Self;
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fn turnedBack(&self) -> Self;// { return {*img, p, back()}; }
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// {
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// auto res = *this;
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// res.p += d;
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@@ -160,6 +161,8 @@ pub trait BitMatrixCursor {
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res
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}
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fn p(&self) -> Point;
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// template<typename ARRAY>
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// ARRAY readPattern(int range = 0)
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// {
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@@ -1 +1,532 @@
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use crate::{
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common::{
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cpp_essentials::{
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Direction, FixedPattern, IsPattern, PatternRow, PatternType, PatternView,
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},
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BitMatrix, Quadrilateral,
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},
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point, Point,
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};
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use super::{
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BitMatrixCursor, DMRegressionLine, EdgeTracer, FastEdgeToEdgeCounter, Pattern, RegressionLine,
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};
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pub fn CenterFromEnd<const N: usize, T: Into<f32> + std::iter::Sum<T> + Copy>(
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pattern: &[T; N],
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end: f32,
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) -> f32 {
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if (N == 5) {
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let a: f32 = pattern[4].into() + pattern[3].into() + pattern[2].into() / 2.0;
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let b: f32 =
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pattern[4].into() + (pattern[3].into() + pattern[2].into() + pattern[1].into()) / 2.0;
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let c: f32 = (pattern[4].into()
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+ pattern[3].into()
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+ pattern[2].into()
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+ pattern[1].into()
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+ pattern[0].into())
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/ 2.0;
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end - (2.0 * a + b + c) / 4.0
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} else if (N == 3) {
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let a: f32 = pattern[2].into() + pattern[1].into() / 2.0;
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let b: f32 = (pattern[2].into() + pattern[1].into() + pattern[0].into()) / 2.0;
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end - (2.0 * a + b) / 3.0
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} else {
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// aztec
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let a: f32 =
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pattern.iter().skip(N / 2 + 1).copied().sum::<T>().into() + pattern[N / 2].into() / 2.0;
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// let a = std::accumulate(pattern.begin() + (N/2 + 1), pattern.end(), pattern[N/2] / 2.0);
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end - a
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}
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}
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pub fn ReadSymmetricPattern<const N: usize, Cursor: BitMatrixCursor>(
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cur: &mut Cursor,
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range: i32,
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) -> Option<Pattern<N>> {
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assert!(N % 2 == 1);
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assert!(range > 0);
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let mut range = range;
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let mut res: Pattern<N> = [0; N];
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let s_2 = res.len() as isize / 2;
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let mut cuo = cur.turnedBack();
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let mut next = |cur: &mut Cursor, i: isize| {
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let v = cur.stepToEdge(Some(1), Some(range), None);
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res[(s_2 + i) as usize] = (res[(s_2 + i) as usize] as i32 + v) as u16;
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// res[(s_2 + i) as usize] += v;
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if (range != 0) {
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range -= v;
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}
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v
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};
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for i in 0..=s_2 {
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// for (int i = 0; i <= s_2; ++i) {
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if (!next(cur, i) != 0 || !next(&mut cuo, -i) != 0) {
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return None;
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}
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}
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res[s_2 as usize] -= 1; // the starting pixel has been counted twice, fix this
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Some(res)
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}
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// default for RELAXED_THRESHOLD should be false
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pub fn CheckSymmetricPattern<
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const RELAXED_THRESHOLD: bool,
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const LEN: usize,
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const SUM: usize,
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T: BitMatrixCursor,
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>(
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cur: &mut T,
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pattern: &Pattern<LEN>,
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range: i32,
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updatePosition: bool,
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) -> i32 {
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let mut range = range;
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let curFwd: FastEdgeToEdgeCounter = FastEdgeToEdgeCounter::new(cur);
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let curBwd: FastEdgeToEdgeCounter = FastEdgeToEdgeCounter::new(&cur.turnedBack());
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let centerFwd = curFwd.stepToNextEdge(range);
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if (!(centerFwd != 0)) {
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return 0;
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}
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let centerBwd = curBwd.stepToNextEdge(range);
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if (!(centerBwd != 0)) {
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return 0;
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}
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assert!(range > 0);
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let mut res: PatternRow = PatternRow::new(vec![0; LEN]);
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let s_2 = (res.len()) / 2;
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res[s_2] = (centerFwd + centerBwd - 1) as u16; // -1 because the starting pixel is counted twice
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range -= res[s_2] as i32;
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let mut next = |cur: &FastEdgeToEdgeCounter, i: isize| {
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let v = cur.stepToNextEdge(range);
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res[(s_2 as isize + i) as usize] = v as u16;
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range -= v;
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v
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};
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for i in 1..=s_2 {
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// for (int i = 1; i <= s_2; ++i) {
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if (!(next(&curFwd, i as isize) != 0) || !(next(&curBwd, -(i as isize)) != 0)) {
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return 0;
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}
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}
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if (!(IsPattern(
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&PatternView::new(&res),
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&FixedPattern::<LEN, SUM, false>::with_reference(pattern),
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None,
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0.0,
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0.0,
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Some(RELAXED_THRESHOLD),
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) != 0.0))
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{
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return 0;
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}
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if (updatePosition) {
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cur.step(Some((res[s_2] as i32 / 2 - (centerBwd as i32 - 1)) as f32));
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}
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res.into_iter().sum::<PatternType>() as i32
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}
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pub fn AverageEdgePixels<T: BitMatrixCursor>(
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cur: &mut T,
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range: i32,
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numOfEdges: u32,
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) -> Option<Point> {
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let mut sum = Point::default();
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for i in 0..numOfEdges {
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// for (int i = 0; i < numOfEdges; ++i) {
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if (!cur.isInSelf()) {
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return None;
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}
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cur.stepToEdge(Some(1), Some(range), None);
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sum += cur.p().centered() + (cur.p() + cur.back()).centered()
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// sum += centered(cur.p) + centered(cur.p + cur.back());
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// log(cur.p + cur.back(), 2);
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}
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Some(sum / (2 * numOfEdges) as f32)
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}
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pub fn CenterOfDoubleCross(
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image: &BitMatrix,
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center: Point,
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range: i32,
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numOfEdges: u32,
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) -> Option<Point> {
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let mut sum = Point::default();
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for d in [
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point(0.0, 1.0),
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point(1.0, 0.0),
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point(1.0, 1.0),
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point(1.0, -1.0),
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] {
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// for (auto d : {PointI{0, 1}, {1, 0}, {1, 1}, {1, -1}}) {
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let avr1 = AverageEdgePixels(&mut EdgeTracer::new(image, center, d), range, numOfEdges)?;
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let avr2 = AverageEdgePixels(&mut EdgeTracer::new(image, center, -d), range, numOfEdges)?;
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sum += avr1 + avr2;
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}
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Some(sum / 8.0)
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}
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pub fn CenterOfRing(
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image: &BitMatrix,
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center: Point,
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range: i32,
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nth: i32,
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requireCircle: bool,
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) -> Option<Point> {
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// range is the approximate width/height of the nth ring, if nth>1 then it would be plausible to limit the search radius
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// to approximately range / 2 * sqrt(2) == range * 0.75 but it turned out to be too limiting with realworld/noisy data.
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let radius = range;
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let inner = nth < 0;
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let nth = nth.abs();
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// log(center, 3);
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let mut cur = EdgeTracer::new(image, center, point(0.0, 1.0));
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if (!(cur.stepToEdge(Some(nth), Some(radius), Some(inner)) != 0)) {
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return None;
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}
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cur.turnRight(); // move clock wise and keep edge on the right/left depending on backup
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let edgeDir = if inner {
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Direction::Left
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} else {
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Direction::Right
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};
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let mut neighbourMask = 0;
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let start = cur.p();
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let mut sum = Point::default();
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let mut n = 0;
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loop {
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// log(cur.p, 4);
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sum += cur.p().centered();
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n += 1;
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// find out if we come full circle around the center. 8 bits have to be set in the end.
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neighbourMask |= (1
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<< (4.0 + Point::dot(Point::bresenhamDirection(cur.p() - center), point(1.0, 3.0)))
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as u32);
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if (!cur.stepAlongEdge(edgeDir, None)) {
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return None;
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}
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// use L-inf norm, simply because it is a lot faster than L2-norm and sufficiently accurate
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if (Point::maxAbsComponent(cur.p - center) > radius as f32
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|| center == cur.p
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|| n > 4 * 2 * range)
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{
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return None;
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}
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if !(cur.p != start) {
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break;
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}
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} //while (cur.p != start);
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if (requireCircle && neighbourMask != 0b111101111) {
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return None;
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}
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Some(sum / n as f32)
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}
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pub fn CenterOfRings(
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image: &BitMatrix,
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center: Point,
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range: i32,
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numOfRings: u32,
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) -> Option<Point> {
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let mut n = numOfRings;
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let mut sum = numOfRings * center;
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for i in 1..numOfRings {
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// for (int i = 1; i < numOfRings; ++i) {
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let c = CenterOfRing(image, center, range, i as i32 + 1, false)?;
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// TODO: decide whether this wheighting depending on distance to the center is worth it
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let weight = numOfRings - i;
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sum += weight * c;
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n += weight;
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}
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Some(sum / n as f32)
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}
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pub fn FinetuneConcentricPatternCenter(
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image: &BitMatrix,
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center: Point,
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range: i32,
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finderPatternSize: u32,
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) -> Option<Point> {
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// make sure we have at least one path of white around the center
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let res = CenterOfRing(image, center, range, 1, false)?;
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let center = res;
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let mut res = CenterOfRings(image, center, range, finderPatternSize / 2);
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if (res.is_none() || !image.get_point(res?)) {
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res = CenterOfDoubleCross(image, (center), range, finderPatternSize / 2 + 1);
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}
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if (res.is_none() || !image.get_point(res?)) {
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res = Some(center);
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}
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if (res.is_none() || !image.get_point(res?)) {
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return None;
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}
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res
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}
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pub fn CollectRingPoints(
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image: &BitMatrix,
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center: Point,
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range: i32,
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edgeIndex: i32,
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backup: bool,
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) -> Vec<Point> {
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let centerI = center.round();
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let radius = range;
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let mut cur = EdgeTracer::new(image, centerI, point(0.0, 1.0));
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if (!(cur.stepToEdge(Some(edgeIndex), Some(radius), Some(backup)) != 0)) {
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return Vec::default();
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}
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cur.turnRight(); // move clock wise and keep edge on the right/left depending on backup
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let edgeDir = if backup {
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Direction::Left
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} else {
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Direction::Right
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};
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let mut neighbourMask = 0;
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let start = cur.p();
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let mut points = Vec::<Point>::with_capacity(4 * range as usize);
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loop {
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// log(cur.p, 4);
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points.push((cur.p().centered()));
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// find out if we come full circle around the center. 8 bits have to be set in the end.
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neighbourMask |= (1
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<< (4.0 + Point::dot(Point::bresenhamDirection(cur.p - centerI), point(1.0, 3.0)))
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as u32);
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if (!cur.stepAlongEdge(edgeDir, None)) {
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return Vec::default();
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}
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// use L-inf norm, simply because it is a lot faster than L2-norm and sufficiently accurate
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if (Point::maxAbsComponent(cur.p - centerI) > radius as f32
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|| centerI == cur.p
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|| (points).len() > 4 * 2 * range as usize)
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{
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return Vec::default();
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}
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if !(cur.p != start) {
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break;
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}
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} //while (cur.p != start);
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if (neighbourMask != 0b111101111) {
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return Vec::default();
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}
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points
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}
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pub fn FitQadrilateralToPoints(center: Point, points: &mut [Point]) -> Option<Quadrilateral> {
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let dist2Center = |a, b| Point::distance(a, center) < Point::distance(b, center);
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// rotate points such that the first one is the furthest away from the center (hence, a corner)
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let max_by_pred = |a: &Point, b: &Point| {
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if dist2Center(*a, *b) {
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std::cmp::Ordering::Greater
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} else {
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std::cmp::Ordering::Less
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}
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};
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let max = points.iter().copied().max_by(max_by_pred)?;
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let pos = points.iter().position(|e| *e == max)?;
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points.rotate_left(pos);
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// std::rotate(points.begin(), std::max_element(points.begin(), points.end(), dist2Center), points.end());
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let mut corners = [Point::default(); 4];
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corners[0] = points[0];
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// find the oposite corner by looking for the farthest point near the oposite point
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points[(points.len() * 3 / 8)..=(points.len() * 5 / 8)]
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.iter()
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.copied()
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.max_by(max_by_pred)?;
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// corners[2] = std::max_element(&points[Size(points) * 3 / 8], &points[Size(points) * 5 / 8], dist2Center);
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// find the two in between corners by looking for the points farthest from the long diagonal
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let l = DMRegressionLine::with_two_points(corners[0], corners[2]);
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let dist2Diagonal = /*[l = RegressionLine(*corners[0], *corners[2])]*/| a, b| { l.distance_single(a) < l.distance_single(b) };
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let diagonal_max_by_pred = |p1: &Point, p2: &Point| {
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if dist2Diagonal(*p1, *p2) {
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std::cmp::Ordering::Greater
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} else {
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std::cmp::Ordering::Less
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}
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};
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corners[1] = points[(points.len() * 1 / 8)..=(points.len() * 3 / 8)]
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.iter()
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.copied()
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.max_by(diagonal_max_by_pred)?;
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// corners[1] = std::max_element(&points[Size(points) * 1 / 8], &points[Size(points) * 3 / 8], dist2Diagonal);
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corners[3] = points[(points.len() * 5 / 8)..=(points.len() * 7 / 8)]
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.iter()
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.copied()
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.max_by(diagonal_max_by_pred)?;
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// corners[3] = std::max_element(&points[Size(points) * 5 / 8], &points[Size(points) * 7 / 8], dist2Diagonal);
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let lines = [
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DMRegressionLine::with_two_points((corners[0] + 1.0), corners[1]),
|
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DMRegressionLine::with_two_points((corners[1] + 1.0), corners[2]),
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DMRegressionLine::with_two_points((corners[2] + 1.0), corners[3]),
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DMRegressionLine::with_two_points((corners[3] + 1.0), (*points.last()? + 1.0)),
|
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];
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// std::array lines{RegressionLine{corners[0] + 1, corners[1]}, RegressionLine{corners[1] + 1, corners[2]},
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// RegressionLine{corners[2] + 1, corners[3]}, RegressionLine{corners[3] + 1, &points.back() + 1}};
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if lines.iter().any(|line| !line.isValid()) {
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return None;
|
||||
}
|
||||
|
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let mut res = Quadrilateral::default();
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||||
for i in 0..4 {
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// for (int i = 0; i < 4; ++i) {
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||||
res[i] = DMRegressionLine::intersect(&lines[i], &lines[(i + 1) % 4])?;
|
||||
}
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||||
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||||
Some(res)
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||||
}
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||||
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||||
pub fn QuadrilateralIsPlausibleSquare(q: &Quadrilateral, lineIndex: usize) -> bool {
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||||
let mut m = f64::default();
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||||
// let mut M = f64::default();
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||||
|
||||
m = Point::distance(q[0], q[3]) as f64; //M = distance(q[0], q[3]);
|
||||
let mut M = m;
|
||||
|
||||
for i in 1..4 {
|
||||
// for (int i = 1; i < 4; ++i)
|
||||
|
||||
UpdateMinMaxFloat(&mut m, &mut M, Point::distance(q[i - 1], q[i]) as f64);
|
||||
}
|
||||
|
||||
m >= (lineIndex * 2) as f64 && m > M / 3.0
|
||||
}
|
||||
|
||||
pub fn FitSquareToPoints(
|
||||
image: &BitMatrix,
|
||||
center: Point,
|
||||
range: i32,
|
||||
lineIndex: i32,
|
||||
backup: bool,
|
||||
) -> Option<Quadrilateral> {
|
||||
let mut points = CollectRingPoints(image, center, range, lineIndex, backup);
|
||||
if (points.is_empty()) {
|
||||
return None;
|
||||
}
|
||||
|
||||
let res = FitQadrilateralToPoints(center, &mut points)?;
|
||||
if (!QuadrilateralIsPlausibleSquare(&res, (lineIndex - i32::from(backup)) as usize)) {
|
||||
return None;
|
||||
}
|
||||
|
||||
Some(res)
|
||||
}
|
||||
|
||||
pub fn FindConcentricPatternCorners(
|
||||
image: &BitMatrix,
|
||||
center: Point,
|
||||
range: i32,
|
||||
lineIndex: i32,
|
||||
) -> Option<Quadrilateral> {
|
||||
let innerCorners = FitSquareToPoints(image, center, range, lineIndex, false)?;
|
||||
|
||||
let outerCorners = FitSquareToPoints(image, center, range, lineIndex + 1, true)?;
|
||||
|
||||
let res = Quadrilateral::blend(&innerCorners, &outerCorners);
|
||||
|
||||
// for p in innerCorners{
|
||||
// log(p, 3);}
|
||||
|
||||
// for p in outerCorners{
|
||||
// log(p, 3);}
|
||||
|
||||
// for p in res{
|
||||
// log(p, 3);}
|
||||
|
||||
Some(res)
|
||||
}
|
||||
|
||||
#[derive(Default)]
|
||||
pub struct ConcentricPattern {
|
||||
p: Point,
|
||||
size: usize,
|
||||
}
|
||||
|
||||
pub fn LocateConcentricPattern<const RELAXED_THRESHOLD:bool, const LEN: usize,
|
||||
const SUM: usize,
|
||||
T: BitMatrixCursor>( image:&BitMatrix, pattern:&Pattern<LEN>, center:Point, range:i32) -> Option<ConcentricPattern>
|
||||
{
|
||||
let mut cur = EdgeTracer::new(image, center, Point::default());
|
||||
let mut minSpread = image.getWidth() as i32;
|
||||
let mut maxSpread = 0_i32;
|
||||
for d in [point(0.0,1.0), point(1.0,0.0)] {
|
||||
// for (auto d : {PointI{0, 1}, {1, 0}}) {
|
||||
cur.setDirection(d); // THIS COULD POSSIBLY BE WRONG, WE MIGHT MEAN TO CLONE cur EACH RUN?
|
||||
let spread = CheckSymmetricPattern(&mut cur, pattern, range, true);
|
||||
if (!(spread != 0))
|
||||
{return None}
|
||||
UpdateMinMax(&mut minSpread, &mut maxSpread, spread);
|
||||
}
|
||||
|
||||
//#if 1
|
||||
for d in [point(1.0,1.0), point(1.0,-1.0)] {
|
||||
// for (auto d : {PointI{1, 1}, {1, -1}}) {
|
||||
cur.setDirection(d);// THIS COULD POSSIBLY BE WRONG, WE MIGHT MEAN TO CLONE cur EACH RUN?
|
||||
let spread = CheckSymmetricPattern(&mut cur, pattern, range * 2, false);
|
||||
if (!(spread != 0))
|
||||
{return None}
|
||||
UpdateMinMax(&mut minSpread, &mut maxSpread, spread);
|
||||
}
|
||||
//#endif
|
||||
|
||||
if (maxSpread > 5 * minSpread)
|
||||
{return None}
|
||||
|
||||
let newCenter = FinetuneConcentricPatternCenter(image, cur.p(), range, pattern.len() as u32)?;
|
||||
|
||||
Some(ConcentricPattern{*newCenter, (maxSpread + minSpread) / 2})
|
||||
}
|
||||
|
||||
fn UpdateMinMax<T: Ord + Copy>(min: &mut T, max: &mut T, val: T) {
|
||||
*min = std::cmp::min(*min, val);
|
||||
*max = std::cmp::max(*max, val);
|
||||
}
|
||||
|
||||
fn UpdateMinMaxFloat(min: &mut f64, max: &mut f64, val: f64) {
|
||||
*min = f64::min(*min, val);
|
||||
*max = f64::max(*max, val);
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
use crate::common::Result;
|
||||
use crate::{Exceptions, Point};
|
||||
use crate::{Exceptions, Point, point};
|
||||
|
||||
use super::{
|
||||
util::{float_max, float_min},
|
||||
@@ -211,9 +211,27 @@ impl RegressionLine for DMRegressionLine {
|
||||
Point::dot(self.direction_inward, self.normal()) > 0.5
|
||||
// angle between original and new direction is at most 60 degree
|
||||
}
|
||||
|
||||
fn a(&self) -> f32 {
|
||||
self.a
|
||||
}
|
||||
|
||||
fn b(&self) -> f32 {
|
||||
self.b
|
||||
}
|
||||
|
||||
fn c(&self) -> f32 {
|
||||
self.c
|
||||
}
|
||||
}
|
||||
|
||||
impl DMRegressionLine {
|
||||
pub fn with_two_points(point1: Point, point2: Point) -> Self {
|
||||
let mut new_rl = DMRegressionLine::default();
|
||||
new_rl.evaluate(&[point1, point2]);
|
||||
new_rl
|
||||
}
|
||||
|
||||
// template <typename Container, typename Filter>
|
||||
fn average<T>(c: &[f64], f: T) -> f64
|
||||
where
|
||||
|
||||
@@ -126,6 +126,13 @@ impl BitMatrixCursor for EdgeTracer<'_> {
|
||||
res
|
||||
}
|
||||
|
||||
fn turnedBack(&self) -> Self {
|
||||
let mut res = self.clone();
|
||||
res.d = res.back();
|
||||
|
||||
res
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief stepToEdge advances cursor to one step behind the next (or n-th) edge.
|
||||
* @param nth number of edges to pass
|
||||
@@ -134,9 +141,9 @@ impl BitMatrixCursor for EdgeTracer<'_> {
|
||||
* @return number of steps taken or 0 if moved outside of range/image
|
||||
*/
|
||||
fn stepToEdge(&mut self, nth: Option<i32>, range: Option<i32>, backup: Option<bool>) -> i32 {
|
||||
let mut nth = if let Some(nth) = nth { nth } else { 1 };
|
||||
let range = if let Some(r) = range { r } else { 0 };
|
||||
let backup = if let Some(b) = backup { b } else { false };
|
||||
let mut nth = nth.unwrap_or(1); //if let Some(nth) = nth { nth } else { 1 };
|
||||
let range = range.unwrap_or(0);//if let Some(r) = range { r } else { 0 };
|
||||
let backup = backup.unwrap_or(false);//if let Some(b) = backup { b } else { false };
|
||||
// TODO: provide an alternative and faster out-of-bounds check than isIn() inside testAt()
|
||||
let mut steps = 0;
|
||||
let mut lv = self.testAt(self.p);
|
||||
@@ -155,6 +162,11 @@ impl BitMatrixCursor for EdgeTracer<'_> {
|
||||
self.p += self.d * steps;
|
||||
steps * i32::from(nth == 0)
|
||||
}
|
||||
|
||||
fn p(&self) -> Point {
|
||||
self.p
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
impl<'a> EdgeTracer<'_> {
|
||||
|
||||
40
src/common/cpp_essentials/fast_edge_to_edge_counter.rs
Normal file
40
src/common/cpp_essentials/fast_edge_to_edge_counter.rs
Normal file
@@ -0,0 +1,40 @@
|
||||
use super::BitMatrixCursor;
|
||||
|
||||
pub struct FastEdgeToEdgeCounter {
|
||||
// const uint8_t* p = nullptr;
|
||||
// int stride = 0;
|
||||
// int stepsToBorder = 0;
|
||||
}
|
||||
|
||||
impl FastEdgeToEdgeCounter
|
||||
{
|
||||
pub fn new<T: BitMatrixCursor>(cur: &T) -> Self {
|
||||
todo!()
|
||||
// stride = cur.d.y * cur.img->width() + cur.d.x;
|
||||
// p = cur.img->row(cur.p.y).begin() + cur.p.x;
|
||||
|
||||
// int maxStepsX = cur.d.x ? (cur.d.x > 0 ? cur.img->width() - 1 - cur.p.x : cur.p.x) : INT_MAX;
|
||||
// int maxStepsY = cur.d.y ? (cur.d.y > 0 ? cur.img->height() - 1 - cur.p.y : cur.p.y) : INT_MAX;
|
||||
// stepsToBorder = std::min(maxStepsX, maxStepsY);
|
||||
}
|
||||
|
||||
pub fn stepToNextEdge(&self, range: i32) -> i32
|
||||
{
|
||||
todo!()
|
||||
// int maxSteps = std::min(stepsToBorder, range);
|
||||
// int steps = 0;
|
||||
// do {
|
||||
// if (++steps > maxSteps) {
|
||||
// if (maxSteps == stepsToBorder)
|
||||
// break;
|
||||
// else
|
||||
// return 0;
|
||||
// }
|
||||
// } while (p[steps * stride] == p[0]);
|
||||
|
||||
// p += steps * stride;
|
||||
// stepsToBorder -= steps;
|
||||
|
||||
// return steps;
|
||||
}
|
||||
}
|
||||
@@ -8,6 +8,7 @@ pub mod regression_line;
|
||||
pub mod step_result;
|
||||
pub mod util;
|
||||
pub mod value;
|
||||
pub mod fast_edge_to_edge_counter;
|
||||
|
||||
pub use bitmatrix_cursor::*;
|
||||
pub use concentric_finder::*;
|
||||
@@ -19,3 +20,4 @@ pub use regression_line::*;
|
||||
pub use step_result::*;
|
||||
pub use util::*;
|
||||
pub use value::*;
|
||||
pub use fast_edge_to_edge_counter::*;
|
||||
|
||||
@@ -8,17 +8,49 @@ use crate::{common::Result, Exceptions};
|
||||
pub type PatternType = u16;
|
||||
pub type Pattern<const N: usize> = [PatternType; N];
|
||||
|
||||
#[derive(Default)]
|
||||
#[derive(Default,Debug)]
|
||||
pub struct PatternRow(Vec<PatternType>);
|
||||
|
||||
// pub struct PatternRow<T: std::iter::Sum + Into<f32> + Into<usize> + Copy>(Vec<T>);
|
||||
|
||||
impl PatternRow {
|
||||
pub fn new( v: Vec<PatternType>) -> Self {
|
||||
Self(v)
|
||||
}
|
||||
|
||||
pub fn len(&self) -> usize {
|
||||
self.0.len()
|
||||
}
|
||||
|
||||
pub fn into_pattern_view(&self) -> PatternView {
|
||||
PatternView::new(self)
|
||||
}
|
||||
}
|
||||
|
||||
impl IntoIterator for PatternRow {
|
||||
type Item = PatternType;
|
||||
|
||||
type IntoIter = std::vec::IntoIter<PatternType>;
|
||||
|
||||
fn into_iter(self) -> Self::IntoIter {
|
||||
self.0.into_iter()
|
||||
}
|
||||
}
|
||||
|
||||
impl std::ops::Index<usize> for PatternRow {
|
||||
type Output = PatternType;
|
||||
|
||||
fn index(&self, index: usize) -> &Self::Output {
|
||||
&self.0[index]
|
||||
}
|
||||
}
|
||||
|
||||
impl std::ops::IndexMut<usize> for PatternRow {
|
||||
fn index_mut(&mut self, index: usize) -> &mut Self::Output {
|
||||
&mut self.0[index]
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> Iterator for PatternView<'_> {
|
||||
type Item = PatternType;
|
||||
|
||||
@@ -33,6 +65,7 @@ impl<'a> Iterator for PatternView<'_> {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct PatternView<'a> {
|
||||
data: &'a PatternRow,
|
||||
start: usize,
|
||||
@@ -96,7 +129,7 @@ impl<'a> PatternView<'_> {
|
||||
|
||||
// index is the number of bars and spaces from the first bar to the current position
|
||||
pub fn index(&self) -> usize {
|
||||
self.current - self.start - 1 /*return narrow_cast<int>(_data - _base) - 1;*/
|
||||
self.current - self.start /*return narrow_cast<int>(_data - _base) - 1;*/
|
||||
}
|
||||
pub fn pixelsInFront(&self) -> PatternType {
|
||||
self.data
|
||||
@@ -183,7 +216,7 @@ impl<'a> PatternView<'_> {
|
||||
// }
|
||||
|
||||
pub fn shift(&mut self, n: usize) -> bool {
|
||||
self.start += n;
|
||||
self.current += n;
|
||||
!self.data.0.is_empty() && self.start + self.count <= (self.start + self.count)
|
||||
}
|
||||
|
||||
@@ -234,7 +267,15 @@ impl<'a> std::ops::Index<usize> for PatternView<'_> {
|
||||
if index > self.data.0.len() {
|
||||
panic!("array index out of bounds")
|
||||
}
|
||||
self.data.0.get(self.start + self.current).unwrap()
|
||||
self.data.0.get(self.start + self.current + index).unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> std::ops::Index<i32> for PatternView<'_> {
|
||||
type Output = PatternType;
|
||||
|
||||
fn index(&self, index: i32) -> &Self::Output {
|
||||
std::ops::Index::<isize>::index(self, index as isize)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -283,7 +324,7 @@ impl<T: Default + std::cmp::PartialEq> std::ops::IndexMut<usize> for BarAndSpace
|
||||
// bool isValid() const { return bar != T{} && space != T{}; }
|
||||
// };
|
||||
|
||||
type BarAndSpaceI = BarAndSpace<u16>;
|
||||
type BarAndSpaceI = BarAndSpace<PatternType>;
|
||||
|
||||
/**
|
||||
* @brief FixedPattern describes a compile-time constant (start/stop) pattern.
|
||||
@@ -293,15 +334,19 @@ type BarAndSpaceI = BarAndSpace<u16>;
|
||||
* @param IS_SPARCE whether or not the pattern contains '0's denoting 'wide' bars/spaces
|
||||
*/
|
||||
pub struct FixedPattern<const N: usize, const SUM: usize, const IS_SPARCE: bool = false> {
|
||||
data: [u16; N],
|
||||
data: [PatternType; N],
|
||||
}
|
||||
|
||||
impl<const N: usize, const SUM: usize, const IS_SPARCE: bool> FixedPattern<N, SUM, IS_SPARCE> {
|
||||
fn new(data: [u16; N]) -> Self {
|
||||
pub fn new(data: [PatternType; N]) -> Self {
|
||||
FixedPattern { data }
|
||||
}
|
||||
|
||||
fn as_slice(&self) -> &[u16] {
|
||||
pub fn with_reference(data: &[PatternType; N]) -> Self {
|
||||
FixedPattern { data: data.clone() }
|
||||
}
|
||||
|
||||
fn as_slice(&self) -> &[PatternType] {
|
||||
&self.data
|
||||
}
|
||||
|
||||
@@ -313,7 +358,7 @@ impl<const N: usize, const SUM: usize, const IS_SPARCE: bool> FixedPattern<N, SU
|
||||
impl<const N: usize, const SUM: usize, const IS_SPARCE: bool> std::ops::Index<usize>
|
||||
for FixedPattern<N, SUM, IS_SPARCE>
|
||||
{
|
||||
type Output = u16;
|
||||
type Output = PatternType;
|
||||
|
||||
fn index(&self, index: usize) -> &Self::Output {
|
||||
&self.data[index]
|
||||
@@ -419,10 +464,6 @@ pub fn FindLeftGuardBy<'a, const LEN: usize, Pred: Fn(&PatternView, Option<f32>)
|
||||
|
||||
window.skipPair();
|
||||
}
|
||||
// for (auto end = view.end() - minSize; window.data() < end; window.skipPair())
|
||||
// {
|
||||
|
||||
// }
|
||||
|
||||
Err(Exceptions::ILLEGAL_STATE)
|
||||
}
|
||||
@@ -483,7 +524,7 @@ pub fn NormalizedPattern<'a, const LEN: usize, const SUM: usize>(
|
||||
.min_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
|
||||
};
|
||||
let mi = mi.ok_or(Exceptions::ILLEGAL_STATE)?;
|
||||
is[*mi as usize] += err as u16;
|
||||
is[*mi as usize] += err as PatternType;
|
||||
rs[*mi as usize] -= err as f32;
|
||||
}
|
||||
|
||||
@@ -496,17 +537,16 @@ enum Color {
|
||||
Black = 1
|
||||
}
|
||||
|
||||
impl<T: Into<u16>> From<T> for Color {
|
||||
impl<T: Into<PatternType>> From<T> for Color {
|
||||
fn from(value: T) -> Self {
|
||||
match value.into() {
|
||||
0 => Color::White,
|
||||
_ => Color::Black,
|
||||
_=>Color::Black
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn GetPatternRow<T: Into<u16> + Copy + Default + From<T>>(b_row: &[T], p_row: &mut PatternRow) {
|
||||
fn GetPatternRow<T: Into<PatternType> + Copy + Default + From<T>>(b_row: &[T], p_row: &mut PatternRow) {
|
||||
p_row.0.clear();
|
||||
|
||||
if Color::from(p_row.0.first().copied().unwrap_or_default()) == Color::Black {
|
||||
@@ -542,20 +582,22 @@ fn GetPatternRow<T: Into<u16> + Copy + Default + From<T>>(b_row: &[T], p_row: &m
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::{GetPatternRow, PatternRow};
|
||||
use crate::common::cpp_essentials::PatternType;
|
||||
|
||||
use super::{GetPatternRow, PatternRow, PatternView};
|
||||
const N: usize = 33;
|
||||
|
||||
#[test]
|
||||
fn all_white() {
|
||||
for s in 1..=N {
|
||||
// for (int s = 1; s <= N; ++s) {
|
||||
let t_in = vec![0_u16; s];
|
||||
let t_in:Vec<PatternType> = vec![0; s];
|
||||
// std::vector<uint8_t> in(s, 0);
|
||||
let mut pr = PatternRow::default();
|
||||
GetPatternRow(&t_in, &mut pr);
|
||||
|
||||
assert_eq!(pr.0.len(), 1);
|
||||
assert_eq!(pr.0[0], s as u16);
|
||||
assert_eq!(pr.0[0], s as PatternType);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -563,13 +605,13 @@ mod tests {
|
||||
fn all_black() {
|
||||
for s in 1..=N {
|
||||
// for (int s = 1; s <= N; ++s) {
|
||||
let t_in: Vec<u16> = vec![0xff; s];
|
||||
let t_in: Vec<PatternType> = vec![0xff; s];
|
||||
let mut pr = PatternRow::default();
|
||||
GetPatternRow(&t_in, &mut pr);
|
||||
|
||||
assert_eq!(pr.0.len(), 3);
|
||||
assert_eq!(pr.0[0], 0);
|
||||
assert_eq!(pr.0[1], s as u16);
|
||||
assert_eq!(pr.0[1], s as PatternType);
|
||||
assert_eq!(pr.0[2], 0);
|
||||
}
|
||||
}
|
||||
@@ -578,7 +620,7 @@ mod tests {
|
||||
fn black_white() {
|
||||
for s in 1..=N {
|
||||
// for (int s = 1; s <= N; ++s) {
|
||||
let mut t_in = vec![0_u16; N];
|
||||
let mut t_in : Vec<PatternType> = vec![0; N];
|
||||
t_in[..s].copy_from_slice(&vec![1; s]);
|
||||
// std::fill_n(in.data(), s, 0xff);
|
||||
let mut pr = PatternRow::default();
|
||||
@@ -586,8 +628,8 @@ mod tests {
|
||||
|
||||
assert_eq!(pr.0.len(), 3);
|
||||
assert_eq!(pr.0[0], 0);
|
||||
assert_eq!(pr.0[1], s as u16);
|
||||
assert_eq!(pr.0[2], (N - s) as u16);
|
||||
assert_eq!(pr.0[1], s as PatternType);
|
||||
assert_eq!(pr.0[2], (N - s) as PatternType);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -595,15 +637,36 @@ mod tests {
|
||||
fn white_black() {
|
||||
for s in 0..N {
|
||||
// for (int s = 0; s < N; ++s) {
|
||||
let mut t_in: Vec<u16> = vec![0xff; N];
|
||||
let mut t_in: Vec<PatternType> = vec![0xff; N];
|
||||
t_in[..s].copy_from_slice(&vec![0; s]);
|
||||
let mut pr = PatternRow::default();
|
||||
GetPatternRow(&t_in, &mut pr);
|
||||
|
||||
assert_eq!(pr.0.len(), 3);
|
||||
assert_eq!(pr.0[0], s as u16);
|
||||
assert_eq!(pr.0[1], (N - s) as u16);
|
||||
assert_eq!(pr.0[0], s as PatternType);
|
||||
assert_eq!(pr.0[1], (N - s) as PatternType);
|
||||
assert_eq!(pr.0[2], 0);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn basic_pattern_view() {
|
||||
let mut p_row = PatternRow::default();
|
||||
GetPatternRow(&vec![0_u16,1,0,1,0,0,1,1,1,0,0,1,1,1,1,1,1,0,0,0,0,1], &mut p_row);
|
||||
|
||||
let mut pv = PatternView::new(&p_row);
|
||||
|
||||
assert_eq!(pv.data().0,p_row.0);
|
||||
|
||||
assert_eq!(pv[0], 1_u16);
|
||||
assert_eq!(pv[1], 1_u16);
|
||||
assert_eq!(pv[4], 2_u16);
|
||||
assert_eq!(pv[7], 6_u16);
|
||||
|
||||
assert_eq!(pv.index(), 0);
|
||||
assert!(pv.shift(1));
|
||||
assert_eq!(pv.index(), 1);
|
||||
assert!(pv.skipPair());
|
||||
assert_eq!(pv.index(),3);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
use crate::common::Result;
|
||||
use crate::Point;
|
||||
use crate::{Point, point};
|
||||
|
||||
pub trait RegressionLine {
|
||||
// points: Vec<Point>,
|
||||
@@ -11,8 +11,18 @@ pub trait RegressionLine {
|
||||
// PointF _directionInward;
|
||||
// PointF::value_t a = NAN, b = NAN, c = NAN;
|
||||
|
||||
// fn intersect<T: RegressionLine, T2: RegressionLine>(&self, l1: &T, l2: &T2)
|
||||
// -> Point;
|
||||
fn intersect<T: RegressionLine, T2: RegressionLine>( l1: &T, l2: &T2)
|
||||
-> Option<Point>{
|
||||
if !(l1.isValid() && l2.isValid()) {
|
||||
return None;
|
||||
}
|
||||
|
||||
let d = l1.a() * l2.b() - l1.b() * l2.a();
|
||||
let x = (l1.c() * l2.b() - l1.b() * l2.c()) / d;
|
||||
let y = (l1.a() * l2.c() - l1.c() * l2.a()) / d;
|
||||
|
||||
Some(point(x, y))
|
||||
}
|
||||
|
||||
// fn evaluate_begin_end(&self, begin: Point, end: Point) -> bool;// {
|
||||
// {
|
||||
@@ -131,4 +141,7 @@ pub trait RegressionLine {
|
||||
// // due to aliasing we get bad extrapolations if the line is short and too close to vertical/horizontal
|
||||
// return steps > 2 || len > 50;
|
||||
// }
|
||||
fn a(&self) -> f32;
|
||||
fn b(&self) -> f32;
|
||||
fn c(&self) -> f32;
|
||||
}
|
||||
|
||||
@@ -208,6 +208,28 @@ impl Quadrilateral {
|
||||
|
||||
!(x || y)
|
||||
}
|
||||
|
||||
pub fn blend(a: &Quadrilateral, b:&Quadrilateral) -> Self {
|
||||
let c = a[0];
|
||||
let dist2First = | a, b| { Point::distance(a, c) < Point::distance(b, c) };
|
||||
// rotate points such that the the two topLeft points are closest to each other
|
||||
let min_element = b.0.iter().copied().min_by(|a,b| {
|
||||
match dist2First(*a,*b) {
|
||||
true => std::cmp::Ordering::Less,
|
||||
false => std::cmp::Ordering::Greater,
|
||||
}
|
||||
}).unwrap_or_default();
|
||||
let offset = b.0.iter().position(|v| *v == min_element).unwrap_or_default();
|
||||
// let offset = std::min_element(b.begin(), b.end(), dist2First) - b.begin();
|
||||
|
||||
let mut res= Quadrilateral::default();
|
||||
for i in 0..4 {
|
||||
// for (int i = 0; i < 4; ++i){
|
||||
res[i] = (a[i] + b[(i + offset) % 4]) / 2.0;
|
||||
}
|
||||
|
||||
res
|
||||
}
|
||||
}
|
||||
|
||||
impl Default for Quadrilateral {
|
||||
@@ -215,3 +237,17 @@ impl Default for Quadrilateral {
|
||||
Self([Point { x: 0.0, y: 0.0 }; 4])
|
||||
}
|
||||
}
|
||||
|
||||
impl std::ops::Index<usize> for Quadrilateral {
|
||||
type Output = Point;
|
||||
|
||||
fn index(&self, index: usize) -> &Self::Output {
|
||||
&self.0[index]
|
||||
}
|
||||
}
|
||||
|
||||
impl std::ops::IndexMut<usize> for Quadrilateral {
|
||||
fn index_mut(&mut self, index: usize) -> &mut Self::Output {
|
||||
&mut self.0[index]
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user