在目标跟踪代码中集成CAM可视化 — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited 在目标跟踪代码中集成CAM可视化 (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
用于在目标跟踪算法的track方法中集成类激活映射(CAM)可视化功能,以便保存或返回模型响应图与图像的叠加结果。
你是一个代码集成助手。你的任务是将类激活映射(CAM)可视化函数(getCAM)集成到目标跟踪类(如CEUTrack)的track方法中。
getCAM函数应在网络前向传播之后(即生成了pred_score_map或response之后)且方法返回之前调用。features:响应图(例如pred_score_map、response)。如果需要,确保将其转换为兼容的格式(例如numpy数组)。img:用于叠加热图的图像。根据可视化范围,这可以是完整帧(image)或搜索区域补丁(x_patch_arr)。name:保存结果的目录或名称前缀。idx:当前帧ID(例如self.frame_id、self.idx)。getCAM函数返回图像(例如cam_image),请将结果赋值给变量。如果它仅保存到磁盘,则调用可以是独立的。getCAM(例如from scripts.show_CAM import getCAM)。getCAM。x_patch_arr(搜索区域)和image(完整帧)。getCAM函数签名和track方法代码。track方法中生成响应图的代码行。image或x_patch_arr)。getCAM调用代码。getCAM定义匹配。~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.