[][src]Trait opencv::rgbd::Linemod_DetectorTrait

pub trait Linemod_DetectorTrait {
    pub fn as_raw_Linemod_Detector(&self) -> *const c_void;
pub fn as_raw_mut_Linemod_Detector(&mut self) -> *mut c_void; pub fn match_(
        &self,
        sources: &Vector<Mat>,
        threshold: f32,
        matches: &mut Vector<Linemod_Match>,
        class_ids: &Vector<String>,
        quantized_images: &mut dyn ToOutputArray,
        masks: &Vector<Mat>
    ) -> Result<()> { ... }
pub fn add_template(
        &mut self,
        sources: &Vector<Mat>,
        class_id: &str,
        object_mask: &Mat,
        bounding_box: &mut Rect
    ) -> Result<i32> { ... }
pub fn add_synthetic_template(
        &mut self,
        templates: &Vector<Linemod_Template>,
        class_id: &str
    ) -> Result<i32> { ... }
pub fn get_modalities(&self) -> Result<Vector<Ptr<dyn Linemod_Modality>>> { ... }
pub fn get_t(&self, pyramid_level: i32) -> Result<i32> { ... }
pub fn pyramid_levels(&self) -> Result<i32> { ... }
pub fn get_templates(
        &self,
        class_id: &str,
        template_id: i32
    ) -> Result<Vector<Linemod_Template>> { ... }
pub fn num_templates(&self) -> Result<i32> { ... }
pub fn num_templates_1(&self, class_id: &str) -> Result<i32> { ... }
pub fn num_classes(&self) -> Result<i32> { ... }
pub fn class_ids(&self) -> Result<Vector<String>> { ... }
pub fn read(&mut self, fn_: &FileNode) -> Result<()> { ... }
pub fn write(&self, fs: &mut FileStorage) -> Result<()> { ... }
pub fn read_class(
        &mut self,
        fn_: &FileNode,
        class_id_override: &str
    ) -> Result<String> { ... }
pub fn write_class(
        &self,
        class_id: &str,
        fs: &mut FileStorage
    ) -> Result<()> { ... }
pub fn read_classes(
        &mut self,
        class_ids: &Vector<String>,
        format: &str
    ) -> Result<()> { ... }
pub fn write_classes(&self, format: &str) -> Result<()> { ... } }

\brief Object detector using the LINE template matching algorithm with any set of modalities.

Required methods

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Provided methods

pub fn match_(
    &self,
    sources: &Vector<Mat>,
    threshold: f32,
    matches: &mut Vector<Linemod_Match>,
    class_ids: &Vector<String>,
    quantized_images: &mut dyn ToOutputArray,
    masks: &Vector<Mat>
) -> Result<()>
[src]

\brief Detect objects by template matching.

Matches globally at the lowest pyramid level, then refines locally stepping up the pyramid.

\param sources Source images, one for each modality. \param threshold Similarity threshold, a percentage between 0 and 100. \param[out] matches Template matches, sorted by similarity score. \param class_ids If non-empty, only search for the desired object classes. \param[out] quantized_images Optionally return vector of quantized images. \param masks The masks for consideration during matching. The masks should be CV_8UC1 where 255 represents a valid pixel. If non-empty, the vector must be the same size as sources. Each element must be empty or the same size as its corresponding source.

C++ default parameters

  • class_ids: std::vector()
  • quantized_images: noArray()
  • masks: std::vector()

pub fn add_template(
    &mut self,
    sources: &Vector<Mat>,
    class_id: &str,
    object_mask: &Mat,
    bounding_box: &mut Rect
) -> Result<i32>
[src]

\brief Add new object template.

\param sources Source images, one for each modality. \param class_id Object class ID. \param object_mask Mask separating object from background. \param[out] bounding_box Optionally return bounding box of the extracted features.

\return Template ID, or -1 if failed to extract a valid template.

C++ default parameters

  • bounding_box: NULL

pub fn add_synthetic_template(
    &mut self,
    templates: &Vector<Linemod_Template>,
    class_id: &str
) -> Result<i32>
[src]

\brief Add a new object template computed by external means.

pub fn get_modalities(&self) -> Result<Vector<Ptr<dyn Linemod_Modality>>>[src]

\brief Get the modalities used by this detector.

You are not permitted to add/remove modalities, but you may dynamic_cast them to tweak parameters.

pub fn get_t(&self, pyramid_level: i32) -> Result<i32>[src]

\brief Get sampling step T at pyramid_level.

pub fn pyramid_levels(&self) -> Result<i32>[src]

\brief Get number of pyramid levels used by this detector.

pub fn get_templates(
    &self,
    class_id: &str,
    template_id: i32
) -> Result<Vector<Linemod_Template>>
[src]

\brief Get the template pyramid identified by template_id.

For example, with 2 modalities (Gradient, Normal) and two pyramid levels (L0, L1), the order is (GradientL0, NormalL0, GradientL1, NormalL1).

pub fn num_templates(&self) -> Result<i32>[src]

pub fn num_templates_1(&self, class_id: &str) -> Result<i32>[src]

pub fn num_classes(&self) -> Result<i32>[src]

pub fn class_ids(&self) -> Result<Vector<String>>[src]

pub fn read(&mut self, fn_: &FileNode) -> Result<()>[src]

pub fn write(&self, fs: &mut FileStorage) -> Result<()>[src]

pub fn read_class(
    &mut self,
    fn_: &FileNode,
    class_id_override: &str
) -> Result<String>
[src]

C++ default parameters

  • class_id_override: ""

pub fn write_class(&self, class_id: &str, fs: &mut FileStorage) -> Result<()>[src]

pub fn read_classes(
    &mut self,
    class_ids: &Vector<String>,
    format: &str
) -> Result<()>
[src]

C++ default parameters

  • format: "templates_%s.yml.gz"

pub fn write_classes(&self, format: &str) -> Result<()>[src]

C++ default parameters

  • format: "templates_%s.yml.gz"
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Implementors

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