Struct opencv::core::Ptr

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pub struct Ptr<T: ?Sized>where
    Self: PtrExtern,{ /* private fields */ }

Expand description

This is similar to Rust Box, but handled by the C++. Some OpenCV functions insist on accepting Ptr instead of a heap allocated object so we need to satisfy those.

docs.opencv.org 3.x docs.opencv.org 4.x

Implementations§

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impl<T: ?Sized> Ptr<T>where Self: PtrExtern,

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pub fn new(val: T) -> Selfwhere T: OpenCVTypeExternContainerMove + Sized, Self: PtrExternCtor<T>,

Create a new Ptr from the object

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pub fn inner_as_raw(&self) -> *const c_void

Get raw pointer to the inner object

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pub fn inner_as_raw_mut(&mut self) -> *mut c_void

pub fn total_cmp(&self, other: &f32) -> Ordering

Return the ordering between self and other.

Unlike the standard partial comparison between floating point numbers, this comparison always produces an ordering in accordance to the totalOrder predicate as defined in the IEEE 754 (2008 revision) floating point standard. The values are ordered in the following sequence:

negative quiet NaN
negative signaling NaN
negative infinity
negative numbers
negative subnormal numbers
negative zero
positive zero
positive subnormal numbers
positive numbers
positive infinity
positive signaling NaN
positive quiet NaN.

The ordering established by this function does not always agree with the PartialOrd and PartialEq implementations of f32. For example, they consider negative and positive zero equal, while total_cmp doesn’t.

The interpretation of the signaling NaN bit follows the definition in the IEEE 754 standard, which may not match the interpretation by some of the older, non-conformant (e.g. MIPS) hardware implementations.

Example

struct GoodBoy {
    name: String,
    weight: f32,
}

let mut bois = vec![
    GoodBoy { name: "Pucci".to_owned(), weight: 0.1 },
    GoodBoy { name: "Woofer".to_owned(), weight: 99.0 },
    GoodBoy { name: "Yapper".to_owned(), weight: 10.0 },
    GoodBoy { name: "Chonk".to_owned(), weight: f32::INFINITY },
    GoodBoy { name: "Abs. Unit".to_owned(), weight: f32::NAN },
    GoodBoy { name: "Floaty".to_owned(), weight: -5.0 },
];

bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));

Set/initialize anneal RNG

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impl ANN_MLPTraitConst for Ptr<ANN_MLP>

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ANNEAL: Update iteration per step. It must be >0 . Default value is 10. Read more

Apply high-dimensional filtering using adaptive manifolds. Read more

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See also Read more

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impl AdaptiveManifoldFilterTraitConst for Ptr<AdaptiveManifoldFilter>

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See also Read more

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impl AffineFeature2DTrait for Ptr<AffineFeature2D>

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fn as_raw_mut_AffineFeature2D(&mut self) -> *mut c_void

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fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in the image using the wrapped detector and performs affine adaptation to augment them with their elliptic regions. Read more

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fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes descriptors for their surrounding regions, after warping them into circles. Read more

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impl AffineFeature2DTrait for Ptr<TBMR>

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fn as_raw_mut_AffineFeature2D(&mut self) -> *mut c_void

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fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, mask: &impl ToInputArray ) -> Result<()>

Detects keypoints in the image using the wrapped detector and performs affine adaptation to augment them with their elliptic regions. Read more

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fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>

Detects keypoints and computes descriptors for their surrounding regions, after warping them into circles. Read more

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fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

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fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

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