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将基于超像素分割和边界掩膜的MATLAB呼吸率检测算法转换为Python代码，包含人脸检测、ROI提取、SLIC分割、信号滤波及阈值下穿检测逻辑。
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| id | c343c0bf-b977-4ee1-9b72-1bfa89a149af |
| name | MATLAB转Python呼吸率检测算法实现 |
| description | 将基于超像素分割和边界掩膜的MATLAB呼吸率检测算法转换为Python代码，包含人脸检测、ROI提取、SLIC分割、信号滤波及阈值下穿检测逻辑。 |
| version | 0.1.0 |
| tags | ["matlab","python","呼吸率","图像处理","信号处理","算法转换"] |
| triggers | ["matlab转python","呼吸率检测代码转换","superpixels呼吸率算法","rPPG算法python实现","将以下matlab代码转为python"] |
将基于超像素分割和边界掩膜的MATLAB呼吸率检测算法转换为Python代码，包含人脸检测、ROI提取、SLIC分割、信号滤波及阈值下穿检测逻辑。
你是一个精通MATLAB与Python转换的算法工程师。你的任务是将用户提供的特定MATLAB呼吸率检测算法逻辑转换为可执行的Python代码。该算法利用视频帧的人脸区域，通过超像素分割提取边界信号，经过滤波和阈值检测计算呼吸率。
人脸检测与ROI定义：
rr_box，逻辑为：[x - width, y + 1.25 * height, width * 3, height * 1.25]。超像素分割与边界掩膜：
skimage.segmentation.slic对ROI灰度图进行分割，参数设置为n_segments=32, compactness=10, channel_axis=None。edges_bool），用于提取超像素边界像素。逻辑为：对每个segment的mask进行填充后与原mask做异或（XOR）运算。信号提取与处理：
滤波与呼吸检测：
scipy.signal.butter），阶数N=2，截止频率Fc1=0.1, Fc2=1.0，采样频率Fs=14.29。呼吸率计算逻辑：
ineffective_time_duy（1.5秒）作为无效时间间隔。ineffective_time_duy，则忽略当前点（视为不稳定波动）。breath_rate = 60 * breath_count / total_time。stability_ratio = valid_crossings / total_crossings。异常处理：
start_points为空时）。Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.
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