Update nalgebra and the rest of dependencies to have the crates compile

.github/workflows/lints.yml

@@ -1,12 +1,14 @@
-# Cargo fmt and cargo clippy
-
-on: [push, pull_request]
+on:
+  push:
+    branches:
+      - master
+  pull_request:
 
 name: lints
 
 jobs:
-  combo:
-    name: Clippy + rustfmt
+  rustfmt:
+    name: rustfmt
     runs-on: ubuntu-latest
     steps:
       - name: Checkout sources
@@ -18,25 +20,38 @@ jobs:
           profile: minimal
           toolchain: nightly
           override: true
-          components: rustfmt, clippy
-
-      - name: Cache lints
-        uses: actions/cache@v2
+          components: rustfmt
+
+      - uses: Swatinem/rust-cache@v1
         with:
-          path: |
-            ~/.cargo/registry
-            ~/.cargo/git
-            target
-          key: lints-${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
+          cache-on-failure: true
 
       - name: Run cargo fmt
         uses: actions-rs/cargo@v1
         with:
           command: fmt
           args: --all -- --check
+  clippy:
+    name: clippy
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout sources
+        uses: actions/checkout@v2
+
+      - name: Install nightly toolchain
+        uses: actions-rs/toolchain@v1
+        with:
+          profile: minimal
+          toolchain: nightly
+          override: true
+          components: clippy
+
+      - uses: Swatinem/rust-cache@v1
+        with:
+          cache-on-failure: true
 
       - name: Run cargo clippy
         uses: actions-rs/cargo@v1
         with:
           command: clippy
-          args: --all-features -- -D warnings
+          args: -- -D warnings

.github/workflows/unit-test.yml → .github/workflows/tests.yml

@@ -1,14 +1,20 @@
-# Cargo test
+on:
+  push:
+    branches:
+      - master
+  pull_request:
 
-on: [push, pull_request]
-
-name: unit tests
+name: tests
 
 jobs:
-  test:
-    name: Test
+  tests:
+    name: tests
     runs-on: ubuntu-latest
     steps:
+      - name: Install system dependencies
+        run: |
+          sudo apt-get -y install libxkbcommon-dev
+
       - name: Checkout sources
         uses: actions/checkout@v2
 
@@ -19,14 +25,9 @@ jobs:
           toolchain: nightly
           override: true
 
-      - name: Cache test
-        uses: actions/cache@v2
+      - uses: Swatinem/rust-cache@v1
         with:
-          path: |
-            ~/.cargo/registry
-            ~/.cargo/git
-            target
-          key: test-${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
+          cache-on-failure: true
 
       - name: Run cargo test
         uses: actions-rs/cargo@v1

README.md

@@ -1,6 +1,6 @@
 # Rust CV
 
-[![Discord][dci]][dcl] [![Crates.io][ci]][cl] [![docs.rs][di]][dl] ![LoC][lo] ![Tests][btl] ![Lints][bll] ![Build][bbl]
+[![Discord][dci]][dcl] [![Crates.io][ci]][cl] [![docs.rs][di]][dl] ![LoC][lo] ![Tests][btl] ![Lints][bll]
 
 [ci]: https://img.shields.io/crates/v/cv.svg
 [cl]: https://crates.io/crates/cv/
@@ -13,9 +13,8 @@
 [dci]: https://img.shields.io/discord/550706294311485440.svg?logo=discord&colorB=7289DA
 [dcl]: https://discord.gg/d32jaam
 
-[btl]: https://github.com/rust-cv/cv/workflows/unit%20tests/badge.svg
+[btl]: https://github.com/rust-cv/cv/workflows/tests/badge.svg
 [bll]: https://github.com/rust-cv/cv/workflows/lints/badge.svg
-[bbl]: https://github.com/rust-cv/cv/workflows/build/badge.svg
 
 Rust CV is a project to implement computer vision algorithms, abstractions, and systems in Rust. `#[no_std]` is supported where possible.
 
@@ -74,10 +73,11 @@ Here are some of the domains of computer vision that Rust CV intends to persue a
     * [ ] Equirectangular ([Wikipedia](https://en.wikipedia.org/wiki/Equirectangular_projection))
   * [ ] Matching ([Wikipedia](https://en.wikipedia.org/wiki/Point_feature_matching))
     * [x] Descriptor matching strategies
-      * [x] [Brute force](https://docs.rs/space/0.10.3/space/fn.linear_knn.html) (for camera traking with binary features)
-      * [x] [HNSW](https://docs.rs/hnsw/0.6.1/hnsw/struct.HNSW.html) (for loop closure)
+      * [x] [Brute force](https://docs.rs/space/0.13.1/space/struct.LinearKnn.html) (for camera traking with binary features)
+      * [x] [HGG](https://docs.rs/hgg/0.2.0/hgg/) (for loop closure)
+      * [x] [HNSW](https://docs.rs/hnsw/0.9.1/hnsw/struct.Hnsw.html) (for loop closure)
     * [ ] Filtering strategies
-      * [ ] Symmetric matching (exists [within cv-reconstruction](https://github.com/rust-cv/cv/blob/58444de1cb174622ac34cc705ab9142e081f412c/cv-reconstruction/src/lib.rs#L1337))
+      * [ ] Symmetric matching/uniquely best match (exists [within cv-reconstruction](https://github.com/rust-cv/cv/blob/58444de1cb174622ac34cc705ab9142e081f412c/cv-reconstruction/src/lib.rs#L1337), but not reusable)
       * [ ] Lowe's ratio test matching
   * [ ] Geometric verification (utilized abstractions in [sample-consensus](https://docs.rs/sample-consensus/0.2.0/sample_consensus/))
     * [ ] [Consensus algorithms](https://docs.rs/sample-consensus/0.2.0/sample_consensus/trait.Consensus.html)
@@ -129,9 +129,10 @@ Here are some of the domains of computer vision that Rust CV intends to persue a
     * [ ] Surface refinement
     * [ ] Texturing ([related Wikipedia](https://en.wikipedia.org/wiki/Texture_mapping))
 * [ ] Pattern recognition
-  * [x] k-NN search
-    * [x] [Brute force](https://docs.rs/space/0.10.3/space/fn.linear_knn.html)
-    * [x] [HNSW](https://docs.rs/hnsw/0.6.1/hnsw/struct.HNSW.html)
+  * [x] [k-NN search](https://docs.rs/space/0.13.1/space/trait.Knn.html)
+    * [x] [Brute force](https://docs.rs/space/0.13.1/space/struct.LinearKnn.html)
+    * [x] [HGG](https://docs.rs/hgg/0.2.0/hgg/) (for loop closure)
+    * [x] [HNSW](https://docs.rs/hnsw/0.9.1/hnsw/struct.Hnsw.html)
     * [x] [FLANN](https://docs.rs/flann/0.1.0/flann/)
   * [ ] Face recognition ([Wikipedia](https://en.wikipedia.org/wiki/Facial_recognition_system))
   * [ ] Articulated body pose estimation ([Wikipedia](https://en.wikipedia.org/wiki/Articulated_body_pose_estimation))

akaze/Cargo.toml

@@ -16,25 +16,24 @@ cv-core = { version = "0.15.0", path = "../cv-core" }
 image = { version = "0.23.14", default-features = false }
 log = { version = "0.4.14", default-features = false }
 primal = { version = "0.3.0", default-features = false }
-derive_more = { version = "0.99.11", default-features = false }
-nshare = { version = "0.2.0", features = ["ndarray", "image"] }
-ndarray = { version = "0.14.0", default-features = false }
-float-ord = { version = "0.2.0", default-features = false }
-space = "0.10.3"
-bitarray = "0.2.6"
+derive_more = { version = "0.99.16", default-features = false }
+nshare = { version = "0.7.0", features = ["ndarray", "image"] }
+ndarray = { version = "0.15.3", default-features = false }
+float-ord = { version = "0.3.1", default-features = false }
+space = "0.14.0"
+bitarray = "0.5.1"
 
 
 [dev-dependencies]
 eight-point = { version = "0.8.0", path = "../eight-point" }
 cv-pinhole = { version = "0.6.0", path = "../cv-pinhole" }
-arrsac = "0.6.1"
-space = "0.10.3"
-rand = "0.8.3"
-rand_pcg = "0.3.0"
+arrsac = "0.7.0"
+rand = "0.8.4"
+rand_pcg = "0.3.1"
 criterion = "0.3.4"
 pretty_env_logger = "0.4.0"
 image = "0.23.14"
-bitarray = { version = "0.2.6", features = ["space"] }
+bitarray = { version = "0.5.1", features = ["space"] }
 
 [[bench]]
 name = "criterion"

akaze/src/derivatives.rs

@@ -13,7 +13,7 @@ use ndarray::{s, Array2, ArrayView2, ArrayViewMut2};
 /// Output image derivative (an image.)
 pub fn scharr_horizontal(image: &GrayFloatImage, sigma_size: u32) -> GrayFloatImage {
     let img_horizontal = scharr_axis(
-        &image,
+        image,
         sigma_size,
         FilterDirection::Horizontal,
         FilterOrder::Main,
@@ -38,7 +38,7 @@ pub fn scharr_horizontal(image: &GrayFloatImage, sigma_size: u32) -> GrayFloatIm
 /// Output image derivative (an image.)
 pub fn scharr_vertical(image: &GrayFloatImage, sigma_size: u32) -> GrayFloatImage {
     let img_horizontal = scharr_axis(
-        &image,
+        image,
         sigma_size,
         FilterDirection::Horizontal,
         FilterOrder::Off,

akaze/src/descriptors.rs

@@ -59,7 +59,7 @@ impl Akaze {
                 co,
                 si,
                 scale,
-                &evolutions,
+                evolutions,
             );
             mldb_binary_comparisons(
                 &values,

akaze/src/image.rs

@@ -257,7 +257,7 @@ pub fn gaussian_blur(image: &GrayFloatImage, r: f32) -> GrayFloatImage {
     // a separable Gaussian kernel
     let kernel_size = (f32::ceil(r) as usize) * 2 + 1usize;
     let kernel = gaussian_kernel(r, kernel_size);
-    let img_horizontal = horizontal_filter(&image, &kernel);
+    let img_horizontal = horizontal_filter(image, &kernel);
     vertical_filter(&img_horizontal, &kernel)
 }
 

akaze/src/lib.rs

@@ -230,7 +230,7 @@ impl Akaze {
     /// ```
     ///
     pub fn extract(&self, image: &DynamicImage) -> (Vec<KeyPoint>, Vec<BitArray<64>>) {
-        let float_image = GrayFloatImage::from_dynamic(&image);
+        let float_image = GrayFloatImage::from_dynamic(image);
         let mut evolutions = self.allocate_evolutions(image.width(), image.height());
         self.create_nonlinear_scale_space(&mut evolutions, &float_image);
         trace!("Finding image keypoints.");

akaze/src/scale_space_extrema.rs

@@ -141,7 +141,7 @@ impl Akaze {
     /// The resulting keypoints.
     pub fn detect_keypoints(&self, evolutions: &mut Vec<EvolutionStep>) -> Vec<KeyPoint> {
         let mut keypoints = self.find_scale_space_extrema(evolutions);
-        keypoints = do_subpixel_refinement(&keypoints, &evolutions);
+        keypoints = do_subpixel_refinement(&keypoints, evolutions);
         keypoints
     }
 }
@@ -332,7 +332,7 @@ fn do_subpixel_refinement(
         in_keypoints.len()
     );
     for mut keypoint in result.iter_mut() {
-        compute_main_orientation(&mut keypoint, &evolutions);
+        compute_main_orientation(&mut keypoint, evolutions);
     }
     result
 }

akaze/tests/estimate_pose.rs

@@ -7,6 +7,7 @@ use cv_core::{CameraModel, FeatureMatch};
 use log::*;
 use rand::SeedableRng;
 use rand_pcg::Pcg64;
+use space::Knn;
 use std::path::Path;
 
 const LOWES_RATIO: f32 = 0.5;
@@ -73,16 +74,11 @@ fn estimate_pose() {
 }
 
 fn match_descriptors(ds1: &[Descriptor], ds2: &[Descriptor]) -> Vec<(usize, usize)> {
-    use space::Neighbor;
     let two_neighbors = ds1
         .iter()
         .map(|d1| {
-            let mut neighbors = [Neighbor::invalid(); 2];
-            assert_eq!(
-                space::linear_knn(d1, &mut neighbors, ds2).len(),
-                2,
-                "there should be at least two matches"
-            );
+            let neighbors = space::LinearKnn(ds2.iter()).knn(d1, 2);
+            assert_eq!(neighbors.len(), 2, "there should be at least two matches");
             neighbors
         })
         .enumerate();

cv-core/Cargo.toml

@@ -15,11 +15,12 @@ readme = "README.md"
 serde-serialize = ["serde", "nalgebra/serde-serialize"]
 
 [dependencies]
-nalgebra = { version = "0.25.3", default-features = false, features = ["libm"] }
-derive_more = "0.99.11"
+# TODO: Fix this once alloc feature is working again.
+nalgebra = { version = "0.28.0", default-features = false, features = ["std"] }
+derive_more = "0.99.16"
 sample-consensus = "1.0.1"
 num-traits = { version = "0.2.14", default-features = false }
-serde = { version = "1.0.124", default-features = false, features = ["derive"], optional = true }
+serde = { version = "1.0.126", default-features = false, features = ["derive"], optional = true }
 
 [package.metadata.docs.rs]
 all-features = true

cv-core/src/camera.rs

@@ -51,6 +51,7 @@ impl Bearing for Unit<Vector3<f64>> {
         Unit::new_normalize(bearing)
     }
 
+    #[allow(clippy::wrong_self_convention)]
     fn from_bearing_unit_vector(bearing: Unit<Vector3<f64>>) -> Self {
         bearing
     }

cv-geom/Cargo.toml

@@ -13,4 +13,4 @@ readme = "README.md"
 
 [dependencies]
 cv-core = { version = "0.15.0", path = "../cv-core" }
-float-ord = "0.2.0"
+float-ord = "0.3.1"

cv-optimize/Cargo.toml

@@ -5,11 +5,10 @@ authors = ["Geordon Worley <vadixidav@gmail.com>"]
 edition = "2018"
 
 [dependencies]
-levenberg-marquardt = "0.8.0"
+levenberg-marquardt = "0.10.0"
 cv-core = { version = "0.15.0", path = "../cv-core" }
-nalgebra = { version = "0.25.3", features = ["alloc"], default-features = false }
+nalgebra = { version = "0.28.0", features = ["alloc"], default-features = false }
 num-traits = "0.2.14"
-argmin = { version = "0.4.1", features = ["ndarrayl"] }
-ndarray = "0.14.0"
-average = "0.10.6"
-itertools = "0.10.0"
+argmin = "0.4.5"
+average = "0.13.1"
+itertools = "0.10.1"