跳转到主要内容
RT-DETR 检测节点使用 RT-DETR 模型对输入图像执行目标检测。它能识别物体、绘制边界框,并根据 COCO 数据集类别进行标注。您可以根据置信度分数、目标类别进行过滤,并限制检测总数。

输入

参数描述数据类型是否必需取值范围
模型用于目标检测的 RT-DETR 模型。MODEL不适用
图像要检测目标的输入图像。该节点最多可批量处理 32 张图像。IMAGE不适用
阈值检测结果必须达到的最低置信度分数,才会被包含在结果中(默认值:0.5)。FLOAT不适用
类别名称按类别过滤检测结果。设置为 ‘all’ 可禁用过滤(默认值:“all”)。COMBO"all"
"person"
"bicycle"
"car"
"motorcycle"
"airplane"
"bus"
"train"
"truck"
"boat"
"traffic light"
"fire hydrant"
"stop sign"
"parking meter"
"bench"
"bird"
"cat"
"dog"
"horse"
"sheep"
"cow"
"elephant"
"bear"
"zebra"
"giraffe"
"backpack"
"umbrella"
"handbag"
"tie"
"suitcase"
"frisbee"
"skis"
"snowboard"
"sports ball"
"kite"
"baseball bat"
"baseball glove"
"skateboard"
"surfboard"
"tennis racket"
"bottle"
"wine glass"
"cup"
"fork"
"knife"
"spoon"
"bowl"
"banana"
"apple"
"sandwich"
"orange"
"broccoli"
"carrot"
"hot dog"
"pizza"
"donut"
"cake"
"chair"
"couch"
"potted plant"
"bed"
"dining table"
"toilet"
"tv"
"laptop"
"mouse"
"remote"
"keyboard"
"cell phone"
"microwave"
"oven"
"toaster"
"sink"
"refrigerator"
"book"
"clock"
"vase"
"scissors"
"teddy bear"
"hair drier"
"toothbrush"
最大检测数每张图像返回的最大检测数量。按置信度分数降序排列(默认值:100)。INT不适用

输出

输出名称描述数据类型
bboxes每个输入图像的边界框列表。每个框包含坐标 (x, y, 宽度, 高度)、类别标签和置信度分数。BOUNDINGBOX
本文档由 AI 生成。如果您发现任何错误或有改进建议,欢迎贡献! 在 GitHub 上编辑

Source fingerprint (SHA-256): 0c32aa9e17b8ea81e52cb45df2a40f7c1faeb39fdf18dfc643d1d31ed0bfdefd