#ifndef _PL_BlockGrouping_H_
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#define _PL_BlockGrouping_H_
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#include "PipeLine.h"
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#include "MaterialBuffer.h"
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#include "GraphicHelper.h"
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#include <vector>
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#include <list>
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typedef bool (*user_test_grouping_func_t)();
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typedef float (*user_score_func_t)(const MB_Frame* ptr_frame, const PLGH_Rect& rects, uint8_t* croppedData);
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#define PLBG_MAX_CACHE_FRAMES 10//#todo
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#define PLBG_MAX_GROUPS 10
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struct RectWrapper
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{
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PLGH_Rect rect;
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float user_score_1;
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void* userData;
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typedef void (*user_data_deleter_func_t)(RectWrapper& rw);
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user_data_deleter_func_t user_data_deleter;
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RectWrapper() :
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rect(), user_score_1(0.0f), userData(nullptr), user_data_deleter(nullptr)
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{ }
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};
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typedef void (*plbg_get_rect_func_t)(const PipeMaterial& ptr_pm, const MB_Frame& data_frame, std::list<RectWrapper>& rects);
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struct PLBG_Output
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{
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uint16_t groupID;
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uint16_t blockID;
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RectWrapper rectInOriginFrame;
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MB_Frame* originframe;
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float score;
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uint8_t* croppedData;
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size_t croppedDataSize;
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PLBG_Output() :
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groupID(0), blockID(0),
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rectInOriginFrame(), originframe(nullptr),
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score(0.0f), croppedData(nullptr), croppedDataSize(0)
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{
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}
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};
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typedef std::vector<PLBG_Output> plbg_output_vec_t;
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struct PL_BlockGrouping_Config
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{
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bool copyData;
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int precfg_fps;
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int precfg_interval;
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int precfg_delay;
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plbg_get_rect_func_t get_rect_func;
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int group_size_min; // group内数量需要产生输出，但数量小于group_size_min时，丢弃组
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int group_size_max; // 一组block的数量，当测试组中累积block数量大于等于group_size_max时，产生输出
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int frame_count_max; // 对于一组block，当输入帧数量大于此值时，产生输出
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int group_top_n; // 对于不容忍的变化，组内产生group_top_n个输出
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// tolerance for grouping
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int block_center_x_diff; // block中心X容忍的移动距离
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int block_center_y_diff; // block中心Y容忍的移动距离
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int block_area_diff; // block面积容忍的变化
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int continuity_max; // 输入连续性的最大间隔
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int accept_blocks_max_per_frame; // 每帧每组接受的最大block数量
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user_test_grouping_func_t user_test_group_accept_rect;
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// scoring
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// user_score_rate = 1 - canny_focus - histogram_uniformy;
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// score = canny_focus * canny(image) +
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// histogram_uniformy * histogram(image) +
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// user_score_rate * user_score_func(image)
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float canny_focus; // 对焦度（模糊度）评分所占比例，返回0~1.0得分（边缘锐度）
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float histogram_uniformy; // 直方图幅度????
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float user_score_1_rate;
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user_score_func_t user_score_2_func; // 用户评分函数评分，返回0~1.0得分
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PL_BlockGrouping_Config() :
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//copyData(false),
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//get_rect_func(nullptr),
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//group_size_max(10), frame_count_max(10), group_top_n(2),
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//block_center_x_diff(5), block_center_y_diff(5),
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//block_area_diff(500), continuity_max(2), accept_blocks_max_per_frame(1),
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//canny_focus(0.4), histogram_uniformy(0.0), user_score_func(nullptr)
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// camera 640x480,fps=30,dist=1(meter),interval=25
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//copyData(false),
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//get_rect_func(nullptr),
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//group_size_min(2), group_size_max(20), frame_count_max(fps * 6), group_top_n(1),
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//block_center_x_diff(100), block_center_y_diff(100),
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//block_area_diff(20000), continuity_max(2.0 * rect_interval), accept_blocks_max_per_frame(1), user_test_group_accept_rect(),
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//canny_focus(0.3), user_score_1_rate(0.4), histogram_uniformy(0.0), user_score_2_func(nullptr)
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// dahua 1920x1080,fps=25,dist=3,i=10
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precfg_fps(25), precfg_interval(2), precfg_delay(4),
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copyData(false),
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get_rect_func(nullptr),
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group_size_min(1 + precfg_interval), group_size_max(2 * (precfg_fps * precfg_delay) / precfg_interval), frame_count_max(precfg_fps * precfg_delay), group_top_n(1),
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block_center_x_diff(100), block_center_y_diff(100),
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block_area_diff(20000), continuity_max(8.0 * precfg_interval), accept_blocks_max_per_frame(1), user_test_group_accept_rect(),
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canny_focus(0.3), user_score_1_rate(0.4), histogram_uniformy(0.0), user_score_2_func(nullptr)
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{ }
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};
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class PL_BlockGrouping : public PipeLineElem
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{
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public:
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PL_BlockGrouping();
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virtual ~PL_BlockGrouping();
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virtual bool init(void* args);
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virtual void finit();
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virtual bool pay(const PipeMaterial& pm);
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virtual bool gain(PipeMaterial& pm);
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private:
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static bool pay_breaker_MBFT_YUV(const PipeMaterial* pm, void* args);
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private:
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void* internal;
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};
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PipeLineElem* create_PL_BlockGrouping();
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#endif
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