[−][src]Trait opencv::cudaoptflow::prelude::CUDA_NvidiaOpticalFlow_1_0

pub trait CUDA_NvidiaOpticalFlow_1_0: CUDA_NvidiaHWOpticalFlow {
    pub fn as_raw_CUDA_NvidiaOpticalFlow_1_0(&self) -> *const c_void;

    pub fn as_raw_mut_CUDA_NvidiaOpticalFlow_1_0(&mut self) -> *mut c_void;

    pub fn up_sampler(
        &mut self, 
        flow: &dyn ToInputArray, 
        width: i32, 
        height: i32, 
        grid_size: i32, 
        upsampled_flow: &mut dyn ToInputOutputArray
    ) -> Result<()> { ... }
}

Class for computing the optical flow vectors between two images using NVIDIA Optical Flow hardware and Optical Flow SDK 1.0.

Note:

  • A sample application demonstrating the use of NVIDIA Optical Flow can be found at opencv_source_code/samples/gpu/nvidia_optical_flow.cpp
  • An example application comparing accuracy and performance of NVIDIA Optical Flow with other optical flow algorithms in OpenCV can be found at opencv_source_code/samples/gpu/optical_flow.cpp

Required methods

pub fn as_raw_CUDA_NvidiaOpticalFlow_1_0(&self) -> *const c_void[src]

pub fn as_raw_mut_CUDA_NvidiaOpticalFlow_1_0(&mut self) -> *mut c_void[src]

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Provided methods

pub fn up_sampler(
    &mut self,
    flow: &dyn ToInputArray,
    width: i32,
    height: i32,
    grid_size: i32,
    upsampled_flow: &mut dyn ToInputOutputArray
) -> Result<()>[src]

The NVIDIA optical flow hardware generates flow vectors at granularity gridSize, which can be queried via function getGridSize(). Upsampler() helper function converts the hardware-generated flow vectors to dense representation (1 flow vector for each pixel) using nearest neighbour upsampling method.

Parameters

  • flow: Buffer of type CV_16FC2 containing flow vectors generated by calc().
  • width: Width of the input image in pixels for which these flow vectors were generated.
  • height: Height of the input image in pixels for which these flow vectors were generated.
  • gridSize: Granularity of the optical flow vectors returned by calc() function. Can be queried using getGridSize().
  • upsampledFlow: Buffer of type CV_32FC2, containing upsampled flow vectors, each flow vector for 1 pixel, in the pitch-linear layout.
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Implementations

impl<'_> dyn CUDA_NvidiaOpticalFlow_1_0 + '_[src]

pub fn create(
    width: i32,
    height: i32,
    perf_preset: CUDA_NvidiaOpticalFlow_1_0_NVIDIA_OF_PERF_LEVEL,
    enable_temporal_hints: bool,
    enable_external_hints: bool,
    enable_cost_buffer: bool,
    gpu_id: i32,
    input_stream: &mut Stream,
    output_stream: &mut Stream
) -> Result<Ptr<dyn CUDA_NvidiaOpticalFlow_1_0>>[src]

Instantiate NVIDIA Optical Flow

Parameters

  • width: Width of input image in pixels.
  • height: Height of input image in pixels.
  • perfPreset: Optional parameter. Refer NV OF SDK documentation for details about presets. Defaults to NV_OF_PERF_LEVEL_SLOW.
  • enableTemporalHints: Optional parameter. Flag to enable temporal hints. When set to true, the hardware uses the flow vectors generated in previous call to calc() as internal hints for the current call to calc(). Useful when computing flow vectors between successive video frames. Defaults to false.
  • enableExternalHints: Optional Parameter. Flag to enable passing external hints buffer to calc(). Defaults to false.
  • enableCostBuffer: Optional Parameter. Flag to enable cost buffer output from calc(). Defaults to false.
  • gpuId: Optional parameter to select the GPU ID on which the optical flow should be computed. Useful in multi-GPU systems. Defaults to 0.
  • inputStream: Optical flow algorithm may optionally involve cuda preprocessing on the input buffers. The input cuda stream can be used to pipeline and synchronize the cuda preprocessing tasks with OF HW engine. If input stream is not set, the execute function will use default stream which is NULL stream;
  • outputStream: Optical flow algorithm may optionally involve cuda post processing on the output flow vectors. The output cuda stream can be used to pipeline and synchronize the cuda post processing tasks with OF HW engine. If output stream is not set, the execute function will use default stream which is NULL stream;

C++ default parameters

  • perf_preset: cv::cuda::NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL::NV_OF_PERF_LEVEL_SLOW
  • enable_temporal_hints: false
  • enable_external_hints: false
  • enable_cost_buffer: false
  • gpu_id: 0
  • input_stream: Stream::Null()
  • output_stream: Stream::Null()

Implementors

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