Trait opencv::dnn::ClassificationModelTrait
source · pub trait ClassificationModelTrait: ClassificationModelTraitConst + ModelTrait {
// Required method
fn as_raw_mut_ClassificationModel(&mut self) -> *mut c_void;
// Provided methods
fn set_enable_softmax_post_processing(
&mut self,
enable: bool
) -> Result<ClassificationModel> { ... }
fn classify(&mut self, frame: &dyn ToInputArray) -> Result<Tuple<(i32, f32)>> { ... }
fn classify_1(
&mut self,
frame: &dyn ToInputArray,
class_id: &mut i32,
conf: &mut f32
) -> Result<()> { ... }
}
Expand description
Mutable methods for crate::dnn::ClassificationModel
Required Methods§
fn as_raw_mut_ClassificationModel(&mut self) -> *mut c_void
Provided Methods§
sourcefn set_enable_softmax_post_processing(
&mut self,
enable: bool
) -> Result<ClassificationModel>
fn set_enable_softmax_post_processing( &mut self, enable: bool ) -> Result<ClassificationModel>
Set enable/disable softmax post processing option.
If this option is true, softmax is applied after forward inference within the classify() function to convert the confidences range to [0.0-1.0]. This function allows you to toggle this behavior. Please turn true when not contain softmax layer in model.
Parameters
- enable: Set enable softmax post processing within the classify() function.
sourcefn classify(&mut self, frame: &dyn ToInputArray) -> Result<Tuple<(i32, f32)>>
fn classify(&mut self, frame: &dyn ToInputArray) -> Result<Tuple<(i32, f32)>>
Given the @p input frame, create input blob, run net and return top-1 prediction.
Parameters
- frame: The input image.
sourcefn classify_1(
&mut self,
frame: &dyn ToInputArray,
class_id: &mut i32,
conf: &mut f32
) -> Result<()>
fn classify_1( &mut self, frame: &dyn ToInputArray, class_id: &mut i32, conf: &mut f32 ) -> Result<()>
Given the @p input frame, create input blob, run net and return top-1 prediction.
Parameters
- frame: The input image.