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Unreleased

Fixed

  • Evision.Mat.clip/3: upper bound no longer collapses to the lower bound (typo where both branches compared against lower).
  • Evision.Mat.dot/2: now actually computes a dot product. The previous implementation called cv::Mat::cross despite being named dot, so it only worked for 3-element vectors and returned a Mat. See Breaking changes below.
  • Evision.Mat.arange/4,5: range count is now computed with ceiling division, so the final stepped value is included when the interval is not evenly divisible (e.g. arange(0, 5, 2) now returns [0, 2, 4] instead of [0, 2]). step == 0 and direction mismatches are rejected explicitly.
  • Evision.Mat.negate/1, Evision.Mat.ceil/1, Evision.Mat.floor/1, Evision.Mat.round/1: now traverse every scalar in multi-channel matrices instead of only the first channel of each pixel.
  • Evision.Mat.ceil/1, Evision.Mat.floor/1, Evision.Mat.round/1: added support for CV_16F (half-precision float) inputs.
  • Evision.Mat.at/2: added bounds checking (was previously undefined behaviour past the end) and a clone-on-non-continuous fallback so the scalar index lands on the right element. CV_16F is now supported.
  • Evision.Mat.from_binary_by_shape/3: rejects binaries whose byte size does not match the declared shape (previously created a Mat that read past the binary).
  • Evision.Mat.from_binary/5: the declared rows × cols × channels × bytes_per_element is now computed with overflow checks.
  • Evision.Mat.to_binary/1,2:
    • The limit parameter is now honored on the NIF path (was previously ignored).
    • Non-continuous matrices are cloned before serialisation so the returned binary contains contiguous element data rather than the underlying buffer's interleaved padding.
    • The nx_tensor branch in Elixir now interprets limit as the number of elements (multiplying by elem_size), matching the NIF path and the Backend.inspect/2 caller.
  • Evision.Mat.to_batched/3 (3-arg): now works on multi-channel matrices (previously the shape(mat) it derived internally always failed the size check). The 3-arg wrapper also no longer passes a tuple where a list is expected.
  • Evision.Mat.to_batched/4 repeat mode: no longer reads past the source matrix when batch_size × slice_size exceeds the source size; the source is now safely repeated as many times as needed.
  • Evision.Mat.update_roi/3: the caller's Mat data is no longer mutated in place — update_roi always returns a new Mat and leaves the input untouched. Previously the underlying buffer was modified through the shared reference, silently mutating any other reference to the same Mat.
  • Evision.Mat.transpose/3 with as_shape:: rejects as_shape whose total byte size does not match the source matrix, preventing out-of-bounds reads from cv::transposeND.
  • Evision.Mat.expm1/1: removed a dead/buggy fallback that called cv::exp a second time without exception protection after the wrapped call had already failed.
  • Evision.Mat.last_dim_as_channel/1: now uses src.depth() (instead of the full type) when re-tagging the channels and explicitly rejects channel counts outside [1, CV_CN_MAX].
  • Evision.CUDA.GpuMat.from_pointer/3: the resource is now released on the error path (previously leaked) and the OOM path returns a proper error term.
  • evision::nif::get_tuple for std::vector<int64_t>: now reads each element as int64_t (was int), so large 64-bit values in tuples are no longer truncated/rejected.
  • evision_highgui thread initialisation: races between concurrent start_native_gui callers are now serialised behind an EVISION_INITIATING state, and evision_main_loop notifies all waiters (was notify_one, which could leave additional waiters stuck).
  • alloc_resource for cv::Mat *: explicitly initialises tmp->val = nullptr so a release before assignment does not free uninitialised memory.

Added

  • Evision.Mat.matmul/2: convenience wrapper around cv::Mat::operator* (matrix multiplication via cv::gemm). Both inputs must be 2-D and share a CV_32F or CV_64F depth. For element-wise dot-product semantics use Evision.Mat.dot/2.

Breaking changes

  • Evision.Mat.dot/2 now returns a number() (the scalar dot product) instead of a %Evision.Mat{}. This matches the C++ cv::Mat::dot definition. The previous behaviour was a bug: the function was implemented with cv::Mat::cross, which only accepted 3-element vectors and returned a Mat. Callers who actually wanted matrix multiplication should switch to the new Evision.Mat.matmul/2.
  • Evision.Mat.to_batched/4 (4-arg, explicit as_shape) now requires as_shape to include channels as a dimension for multi-channel matrices, and the resulting batches are single-channel Mats with the channel axis at the end. Concretely:
    • Old: to_batched(cv_8uc3_mat, batch_size, {N, H, W}, ...) → batches of CV_8UC3 mats with shape {batch_size, H, W}.
    • New: to_batched(cv_8uc3_mat, batch_size, {N, H, W, 3}, ...) → batches of CV_8U mats with shape {batch_size, H, W, 3}.
    • The old to_batched(cv_8uc3_mat, batch_size, {N, H, W}, ...) call now returns {:error, "to_batched failed: cannot treated matrix as the request shape"}.
    • Evision.Backend (Nx) workflows are not affected: tensors entering through from_nx/from_binary are always single-channel Mats with the logical Nx shape, so the old and new size-checks evaluate identically.

v0.2.14 (2025-08-15)

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Changes

  • Added support for newer generation of CUDA architectures, including sm_100 and sm_120.

v0.2.13 (2025-05-15)

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Fixed

  • Allowing Features2D parameters to be nil when they have default values or as output parameters.

v0.2.12 (2025-04-14)

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Added

  • Precompiled binaries for x86_64-unknown-freebsd.

v0.2.11 (2025-01-18)

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Changes

  • Bump OpenCV to v4.11.0. Some APIs may have changed, please see OpenCV's release note for more information.
  • Removed aarch64-windows-msvc and ppc64le-linux-gnu target from the precompiled binaries.

v0.2.10 (2024-09-22)

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Changes

  • Bump req to 0.5 and updated examples accordingly. Thanks @mnishiguchi for PR #266

v0.2.9 (2024-08-17)

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Fixes

  • Include the c_src/evision_consts.h in the package.

v0.2.8 (2024-08-04)

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Fixes

  • Fixed inheritance issues for classes that have any of the following base classes:
    • cv::img_hash::ImgHashBase
    • cv::legacy::Tracker
    • cv::phase_unwrapping::PhaseUnwrapping
    • cv::rapid::Tracker
    • cv::reg::Map
    • cv::reg::Mapper
    • cv::structured_light::StructuredLightPattern
    • BackgroundSubtractor

v0.2.7 (2024-07-03)

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Breaking changes (compile-time and CUDA users only)

  • EVISION_CUDA_VERSION, now it should be the major version of CUDA, e.g., 12.
  • EVISION_CUDNN_VERSION, it should be the major version of cuDNN, e.g., 9.

Changes

  • Added precompiled version with CUDA 12.x and cudnn 9.x for aarch64-linux-gnu.

v0.2.5 (2024-07-01)

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Changes

  • Validate possible keyword arguments for functions that accept named arguments.

      iex> img = Evision.imread("test/testdata/dog.jpg")

  # valid keyword argument
  iex> Evision.applyColorMap(src: img, colormap: Evision.Constant.cv_COLORMAP_AUTUMN)
  %Evision.Mat{
    channels: 3,
    dims: 2,
    type: {:u, 8},
    raw_type: 16,
    shape: {576, 768, 3},
    ref: #Reference<0.97833242.1116078104.245977>
  }
  
  # list all possible keyword arguments if the user provides any invalid ones
  iex> Evision.applyColorMap(src: img, colorMap: Evision.Constant.cv_COLORMAP_AUTUMN)
  ** (ArgumentError) unknown keys [:colorMap] in [src: %Evision.Mat{channels: 3, dims: 2, type: {:u, 8}, raw_type: 16, shape: {576, 768, 3}, ref: #Reference<0.97833242.1116078110.246705>}, colorMap: 0], the allowed keys are: [:dst, :colormap, :userColor, :src]
      (elixir 1.18.0-dev) lib/keyword.ex:362: Keyword.validate!/2
      (evision 0.2.4) lib/generated/evision.ex:4603: Evision.applyColorMap/1
      iex:4: (file)

  • Generated typed enums for OpenCV's cv::flann.

  • This should include the following enums and place them in the corresponding modules.

    • flann_algorithm_t
    • flann_centers_init_t
    • flann_log_level_t
    • flann_distance_t
    • flann_datatype_t

    For example, flann_algorithm_t will be put in the Evision.Flann.Algorithm module:

    defmodule Evision.Flann.Algorithm do
  @type enum :: integer()
  @doc enum: true
  def cv_FLANN_INDEX_LINEAR, do: 0
  @doc enum: true
  def cv_FLANN_INDEX_KDTREE, do: 1
  @doc enum: true
  def cv_FLANN_INDEX_KMEANS, do: 2
  @doc enum: true
  def cv_FLANN_INDEX_COMPOSITE, do: 3
  @doc enum: true
  def cv_FLANN_INDEX_KDTREE_SINGLE, do: 4
  @doc enum: true
  def cv_FLANN_INDEX_HIERARCHICAL, do: 5
  @doc enum: true
  def cv_FLANN_INDEX_LSH, do: 6
  @doc enum: true
  def cv_FLANN_INDEX_SAVED, do: 254
  @doc enum: true
  def cv_FLANN_INDEX_AUTOTUNED, do: 255
end

v0.2.4 (2024-06-20)

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Changes

  • Allow users to use named arguments.

v0.2.3 (2024-06-17)

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Added

  • Experimental support for use shared CUDA memory via Evision.CUDA.GpuMat.from_pointer/{3,4}.

v0.2.2 (2024-06-15)

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Added

  • Experimental support for CUDA shared memory via Evision.CUDA.GpuMat.to_pointer/{1,2}.
  • Experimental support for Gleam. See gleam_evision_demo for more information.

Changes

  • General improvements to the typespecs. Enumerators now also have their own modules.

  • Experimental support for using Nx.tensor directly without calling helper functions like Evision.Mat.from_nx/1, Evision.Mat.from_nx_2d/1 and Evision.Mat.last_dim_as_channel/1 .

  • Support /AOS (arithmetic op src) marks in OpenCV source code.

    This should make evision's behaviour in line with OpenCV (C++ and Python).

    For example, in Evision.add/2, the expected behaviour should be different when src1/src2 are single number and they are tuple/array.

    add(src, X) where X is a number (or Nx.tensor(X)), it means add(src, {X,X,X,X})

    while add(src, {X}) (or add(src, Nx.tensor([X]))) means add(src, {X,0,0,0}).

  • Allow a single number to be passed as Evision.Mat.maybe_mat_in() and Evision.scalar().

  • Allow a n-tuple (containing n numbers) to be passed as Evision.Mat.maybe_mat_in() and Evision.scalar().

  • Evision.Mat now implements Nx.LazyContainer protocol.

Fixes

  • Fixed Erlang bindings when converting from Elixir structs to Erlang records and vice versa.

v0.2.1 (2024-06-04)

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Fixes

  • Fixed function specs where type hints for sub-classes were using the type of their parent-classes.

v0.2.0 (2024-06-03)

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Changes

  • Uses OpenCV 4.10.0. Some APIs may have changed, please see OpenCV's release note for more information.

Change logs for v0.1.x can be found in the CHANGELOG.v0.1.md