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165 lines
5.8 KiB
165 lines
5.8 KiB
#pragma once
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#include <fsdk/IObject.h>
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#include <fsdk/FSDKError.h>
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#include <fsdk/Optional.h>
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#include <fsdk/Types.h>
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namespace fsdk {
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#ifndef DOXYGEN_SHOULD_SKIP_THIS
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DECLARE_SMARTPTR(IQualityEstimator);
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#endif
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/**
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* @brief Quality estimation structure
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* Each estimation is given in normalized [0, 1] range. Parameter meanings:
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* \li \c light: image overlighting degree. 1 - ok, 0 - overlighted;
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* \li \c dark: image darkness degree. 1 - ok, 0 - too dark;
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* \li \c gray: image grayness degree 1 - ok, 0 - too gray;
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* \li \c blur: image blur degree. 1 - ok, 0 - too blured.
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* */
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struct Quality {
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float light;
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float dark;
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float gray;
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float blur;
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/**
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* @return complex estimation of quality (minimin of flor estimations). 0 - low quality, 1 - high quality.
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* */
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inline float getQuality() const noexcept;
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};
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/**
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* @brief Subjective Quality estimation structure
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* Each estimation is given in normalized [0, 1] range. Parameter meanings:
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* \li \c blur: image blur degree. 1 - ok, 0 - too blured.
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* \li \c light: image brightness degree. 1 - ok, 0 - too bright;
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* \li \c darkness: image darkness degree. 1 - ok, 0 - too dark;
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* \li \c illumination: image illumination uniformity degree. 1 - ok, 0 - is too illuminated;
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* \li \c specularity: image specularity degree. 1 - ok, 0 - is not specular;
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* \li \c isBlurred image is blurred flag;
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* \li \c isHighlighted image is overlighted flag;
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* \li \c isDark image image is too dark flag;
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* \li \c isIlluminated image is too illuminated flag;
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* \li \c isNotSpecular image is not specular flag;
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* */
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struct SubjectiveQuality {
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float blur;
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float light;
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float darkness;
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float illumination;
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float specularity;
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bool isBlurred;
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bool isHighlighted;
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bool isDark;
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bool isIlluminated;
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bool isNotSpecular;
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/**
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* @return if all boolean flags are false returns true - high quality, else false - low quality.
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* */
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inline bool isGood() const noexcept;
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};
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/**
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* @brief Image quality estimator interface.
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* @note This estimator is designed to work with a person face image; you should pass a warped face detection image.
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* @see IWarper for details.
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* Quality estimator detects the same attributes as all the other estimators:
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* \li over/under exposure;
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* \li blurriness;
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* \li natural/unnatural colors;
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* It is different in the sense that it computes all the estimations at once and returns the results merged somehow
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* into a single value instead of several separate values. This way one can obtain a single scalar quality metric of
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* a person face image. The estimated value is a probability that the image is good for both recognition and viewing
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* purposes.
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* */
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struct IQualityEstimator : IRefCounted {
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/**
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* @brief Estimate the quality.
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* @param [in] warp image with warped face.
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* @param [out] quality output structure with quality params. Complex quality estimation available by method getQuality.
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* @return Result with error code.
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* @see Quality, Image, Result and FSDKError for details.
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* @note warp format must be R8G8B8, @see Format.
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* */
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virtual Result<FSDKError>
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estimate(const Image& warp, Quality& quality) const noexcept = 0;
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/**
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* @brief Estimate the quality of multiple warped images in a single estimate function call
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* @param [in] warps span of images with warped faces.
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* @param [out] quality output quality span.
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* @return Result with error code.
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* @see Span, Quality, Image, Result and FSDKError for details.
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* @note warps format must be R8G8B8, @see Format.
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* @note all spans should be based on user owned continuous collections.
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* @note all spans should be equal size.
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* */
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virtual Result<FSDKError>
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estimate(
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Span<const Image> warps,
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Span<Quality> quality) const noexcept = 0;
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/**
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* @brief Estimate the quality.
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* @param [in] warp image with warped face.
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* @param [out] quality output structure with subjective quality params.
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* @return Result with error code.
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* @see SubjectiveQuality, Image, Result and FSDKError for details.
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* @note warp format must be R8G8B8, @see Format.
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* */
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virtual Result<FSDKError> estimate(
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const Image& warp,
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SubjectiveQuality& quality) const noexcept = 0;
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/**
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* @brief Estimate the subjective quality of multiple warped images in a single estimate function call
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* @param [in] warps span of images with warped faces.
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* @param [out] quality output SubjectiveQuality span.
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* @return Result with error code.
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* @see Span, SubjectiveQuality, Image, Result and FSDKError for details.
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* @note warps format must be R8G8B8, @see Format.
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* @note all spans should be based on user owned continuous collections.
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* @note all spans should be equal size.
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* */
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virtual Result<FSDKError>
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estimate(
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Span<const Image> warps,
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Span<SubjectiveQuality> quality) const noexcept = 0;
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/**
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* @brief Validate input of multiple frames in a single function call.
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* @param [in] warps span of images with warped faces.
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* @param [out] errors output span of errors for each image.
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* @return Result with error code.
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* @see Span, Image, Result and FSDKError for details.
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* @note warps format must be R8G8B8, @see Format.
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* @note all spans should be based on user owned continuous collections.
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* @note all spans should be equal size.
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* */
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virtual Result<FSDKError>
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validate(
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Span<const Image> warps,
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Span<Result<FSDKError>> errors) const noexcept = 0;
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};
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/*
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Implementation details.
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*/
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float Quality::getQuality() const noexcept {
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float min1 = std::min(dark, light);
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float min2 = std::min(gray, blur);
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return std::min(min1, min2);
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}
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/*
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Implementation details.
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*/
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bool SubjectiveQuality::isGood() const noexcept {
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if (!isBlurred && !isHighlighted && !isDark && !isIlluminated && !isNotSpecular)
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return true;
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return false;
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}
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} // namespace fsdk
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