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* Add tinypose model * Add PPTinypose python API * Fix picodet preprocess bug && Add Tinypose examples * Update tinypose example code * Update ppseg preprocess if condition * Update ppseg backend support type * Update permute.h * Update README.md * Update code with comments * Move files dir * Delete premute.cc * Add single model pptinypose * Delete pptinypose old code in ppdet * Code format * Add ppdet + pptinypose pipeline model * Fix bug for posedetpipeline * Change Frontend to ModelFormat * Change Frontend to ModelFormat in __init__.py * Add python posedetpipeline/ * Update pptinypose example dir name * Update README.md * Update README.md * Update README.md * Update README.md * Create keypointdetection_result.md * Create README.md * Create README.md * Create README.md * Update README.md * Update README.md * Create README.md * Fix det_keypoint_unite_infer.py bug * Create README.md * Update PP-Tinypose by comment * Update by comment * Add pipeline directory * Add pptinypose dir * Update pptinypose to align accuracy * Addd warpAffine processor * Update GetCpuMat to GetOpenCVMat * Add comment for pptinypose && pipline * Update docs/main_page.md * Add README.md for pptinypose * Add README for det_keypoint_unite * Remove ENABLE_PIPELINE option * Remove ENABLE_PIPELINE option * Change pptinypose default backend * PP-TinyPose Pipeline support multi PP-Detection models * Update pp-tinypose comment * Update by comments * Add single test example Co-authored-by: Jason <jiangjiajun@baidu.com>
46 lines
2.0 KiB
Markdown
46 lines
2.0 KiB
Markdown
# KeyPointDetectionResult 目标检测结果
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KeyPointDetectionResult 代码定义在`fastdeploy/vision/common/result.h`中,用于表明图像中目标行为的各个关键点坐标和置信度。
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## C++ 定义
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`fastdeploy::vision::KeyPointDetectionResult`
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```c++
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struct KeyPointDetectionResult {
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std::vector<std::array<float, 2>> keypoints;
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std::vector<float> scores;
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int num_joints = -1;
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void Clear();
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std::string Str();
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};
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```
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- **keypoints**: 成员变量,表示识别到的目标行为的关键点坐标。`keypoints.size()= N * J * 2`,
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- `N`:图片中的目标数量
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- `J`:num_joints(一个目标的关键点数量)
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- `3`:坐标信息[x, y]
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- **scores**: 成员变量,表示识别到的目标行为的关键点坐标的置信度。`scores.size()= N * J`
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- `N`:图片中的目标数量
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- `J`:num_joints(一个目标的关键点数量)
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- **num_joints**: 成员变量,一个目标的关键点数量
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- **num_joints**: 成员变量,一个目标的关键点数量
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- **Clear()**: 成员函数,用于清除结构体中存储的结果
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- **Str()**: 成员函数,将结构体中的信息以字符串形式输出(用于Debug)
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## Python 定义
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`fastdeploy.vision.KeyPointDetectionResult`
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- **keypoints**(list of list(float)): 成员变量,表示识别到的目标行为的关键点坐标。
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`keypoints.size()= N * J * 2`
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`N`:图片中的目标数量
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`J`:num_joints(关键点数量)
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`3`:坐标信息[x, y, conf]
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- **scores**(list of float): 成员变量,表示识别到的目标行为的关键点坐标的置信度。
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`scores.size()= N * J`
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`N`:图片中的目标数量
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`J`:num_joints(一个目标的关键点数量)
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- **num_joints**(int): 成员变量,一个目标的关键点数量
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