Merge branch 'develop'

Author: xd009642

.github/FUNDING.yml

@@ -0,0 +1,12 @@
+# These are supported funding model platforms
+
+github: xd009642
+patreon: xd009642
+open_collective: # Replace with a single Open Collective username
+ko_fi: # Replace with a single Ko-fi username
+tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel
+community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry
+liberapay: # Replace with a single Liberapay username
+issuehunt: # Replace with a single IssueHunt username
+otechie: # Replace with a single Otechie username
+custom: # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2']

.travis.yml

@@ -5,6 +5,7 @@ addons:
     apt:
         packages:
             - libssl-dev
+            - gfortran
 cache: cargo
 rust:
   - stable
@@ -14,18 +15,21 @@ matrix:
   allow_failures:
     - rust: nightly
 
-before_cache: |
-  if [[ "$TRAVIS_RUST_VERSION" == nightly ]]; then
-    RUSTFLAGS="--cfg procmacro2_semver_exempt" cargo install cargo-tarpaulin
-  fi
+before_install: 
+  - curl https://blas-lapack-rs.github.io/travis/fortran.sh | bash
+
+#before_cache: |
+# if [[ "$TRAVIS_RUST_VERSION" == nightly ]]; then
+#   cargo install cargo-tarpaulin
+# fi
 
 script:
 - cargo clean
 - cargo build
 - cargo test
 
-after_success: |
-  if [[ "$TRAVIS_RUST_VERSION" == nightly ]]; then
+# after_success: |
+# if [[ "$TRAVIS_RUST_VERSION" == nightly ]]; then
     # Uncomment the following line for coveralls.io
-    cargo tarpaulin --ciserver travis-ci --coveralls $TRAVIS_JOB_ID
-  fi
+    # cargo tarpaulin --ciserver travis-ci --coveralls $TRAVIS_JOB_ID
+# fi

CHANGELOG.md

@@ -0,0 +1,50 @@
+# Change Log
+
+## [Unreleased]
+### Added
+
+### Changed
+
+### Removed
+
+## [0.2.0] 2020-06-06
+### Added
+* Padding strategies (`NoPadding`, `ConstantPadding`, `ZeroPadding`)
+* Threshold module with Otsu and Mean threshold algorithms
+* Image transformations and functions to create affine transform matrices
+* Type alias `Image` for `ImageBase<OwnedRepr<T>, _>` replicated old `Image` type
+* Type alias `ImageView` for `ImageBase<ViewRepr<&'a T>, _>`
+* Morphology module with dilation, erosion, union and intersection of binary images
+
+### Changed
+* Integrated Padding strategies into convolutions
+* Updated `ndarray-stats` to 0.2.0 adding `noisy_float` for median change
+* [INTERNAL] Disabled code coverage due to issues with tarpaulin and native libraries
+* Renamed `Image` to `ImageBase` which can take any implementor of the ndaray `Data` trait
+* Made images have `NoPadding` by default
+* No pad behaviour now keeps pixels near the edges the same as source value instead of making them black
+* Various performance enhancements in convolution and canny functions
+
+### Removed 
+
+## [0.1.1] - 2019-07-31
+### Added
+
+### Changed
+* Applied zero padding by default in convolutions
+
+### Removed 
+
+## [0.1.0] - 2019-03-24
+### Added
+* Image type
+* Colour Models (RGB, Gray, HSV, CIEXYZ, Channel-less)
+* Histogram equalisation
+* Image convolutions
+* `PixelBound` type to aid in rescaling images
+* Canny edge detector
+* `KernelBuilder` and `FixedDimensionKernelBuilder` to create kernels
+* Builder implementations for Sobel, Gaussian, Box Linear filter, Laplace
+* Median filter
+* Sobel Operator
+* PPM encoding and decoding for images

Cargo.toml

@@ -1,20 +1,26 @@
 [package]
 name = "ndarray-vision"
-version = "0.1.1"
+version = "0.2.0"
 authors = ["xd009642 <danielmckenna93@gmail.com>"]
 description = "A computer vision library built on top of ndarray"
 repository = "https://github.com/xd009642/ndarray-vision"
 readme = "README.md"
 license = "MIT/Apache-2.0"
 keywords = ["image", "vision", "image-processing"]
-categories = ["Science", "Multimedia"]
+categories = ["science", "science::robotics", "multimedia", "multimedia::images", "graphics"]
 edition = "2018"
 
 [dependencies]
-ndarray = "0.12"
-ndarray-stats = "0.1"
-num-traits = "0.2"
+ndarray = { version = "0.13", default-features = false }
+ndarray-stats = { version = "0.3", default-features = false }
+ndarray-linalg = { version = "0.12", default-features = false }
+noisy_float = { version = "0.1", default-features = false }
+num-traits = { version = "0.2", default-features = false }
 
 [dev-dependencies]
-ndarray-rand = "0.9.0"
-rand = "0.6.5"
+ndarray-rand = "0.11.0"
+rand = "0.7"
+assert_approx_eq = "1.1.0"
+noisy_float = "0.1.11"
+png = "0.16"
+ndarray-linalg = { version = "0.12", features = ["intel-mkl"] }

examples/transforms.rs

@@ -0,0 +1,64 @@
+use ndarray_vision::core::*;
+use ndarray_vision::format::netpbm::*;
+use ndarray_vision::format::*;
+use ndarray_vision::transform::affine::*;
+use ndarray_vision::transform::*;
+use std::env::current_exe;
+use std::f64::consts::FRAC_PI_4;
+use std::fs::File;
+use std::io::BufWriter;
+use std::path::{Path, PathBuf};
+
+fn get_lena() -> Option<Image<u8, RGB>> {
+    if let Ok(mut root) = current_exe() {
+        root.pop();
+        root.pop();
+        root.pop();
+        root.pop();
+        let mut lena = PathBuf::from(&root);
+        lena.push("images/lena.ppm");
+
+        let decoder = PpmDecoder::default();
+        let image: Image<u8, _> = decoder.decode_file(lena).expect("Couldn't open Lena.ppm");
+        Some(image)
+    } else {
+        None
+    }
+}
+
+fn main() {
+    let lena = get_lena().expect("Couldn't load lena");
+
+    // Create transformation matrix
+    let x = 0.5 * (lena.cols() as f64) - 0.5;
+    let y = 0.5 * (lena.rows() as f64) - 0.5;
+    let trans = rotate_around_centre(FRAC_PI_4, (x, y)).dot(&scale(0.7, 0.7));
+
+    let transformed = lena
+        .transform(trans.view(), None)
+        .expect("Transform failed");
+
+    // save
+    let path = Path::new("transformed_lena.png");
+    let file = File::create(path).expect("Couldn't create output file");
+    let ref mut w = BufWriter::new(file);
+
+    let mut encoder = png::Encoder::new(w, transformed.cols() as u32, transformed.rows() as u32);
+    encoder.set_color(png::ColorType::RGB);
+    encoder.set_depth(png::BitDepth::Eight);
+
+    println!(
+        "Writing image with resolution {}x{}",
+        transformed.cols(),
+        transformed.rows()
+    );
+
+    let mut writer = encoder.write_header().expect("Failed to write file header");
+    if let Some(data) = transformed.data.view().to_slice() {
+        writer
+            .write_image_data(data)
+            .expect("Failed to write image data");
+    } else {
+        println!("Failed to get image slice");
+    }
+}