Supervision Draw
Draw detections onto an image with Roboflow supervision's own annotators, over HTTP and MCP....
我该使用它吗
质量与安全性
A
基于对工具定义和协议合规性的自动分析。
上下文开销
~821token 数(工具定义)
~8.3 KB典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 0.64%)
这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。
安装
一键安装
将以下内容添加到你的 `claude_desktop_config.json` 文件中:
{
"mcpServers": {
"supervision-draw": {
"url": "https://supervision-draw.saastemly.com/mcp"
}
}
}远程端点
https://supervision-draw.saastemly.com/mcpstreamable-http它能做什么
工具清单
工具(1)
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⚪annotate(image, detections, annotators, class_names, format, ...)
Annotate an image with detections using supervision's annotators (box, round_box, box_corner, circle, dot, ellipse, triangle, label, color, mask, polygon, halo, background_overlay, blur, pixelate, percentage_bar), applied in order. Input: base64 image up to 4 megapixels, up to 500 detections with xyxy pixel boxes and optional class_id, confidence, ASCII label, polygon. Returns the annotated image (base64 PNG or JPEG), size and counts per class. Price: $0.003 a call (3 free calls a day without an API key).
输入模式
{
"type": "object",
"properties": {
"image": {
"type": "string",
"description": "Base64 of a PNG, JPEG, BMP or WebP file (a data: URI also works), up to 4 million pixels and about 2 MB"
},
"detections": {
"type": "array",
"description": "Up to 500 detections, drawn in this order",
"items": {
"type": "object",
"properties": {
"xyxy": {
"type": "array",
"items": {
"type": "number"
},
"description": "Box [x1, y1, x2, y2] in pixels from the top-left corner; may extend past the image"
},
"class_id": {
"type": "integer",
"description": "Class number, 0 or more; picks the colour and the name from class_names"
},
"confidence": {
"type": "number",
"description": "0 to 1; shown in the label unless label is given"
},
"label": {
"type": "string",
"description": "Label text, printable ASCII, up to 64 characters (replaces the generated one)"
},
"tracker_id": {
"type": "integer",
"description": "Tracker id, used when color_lookup is track"
},
"polygon": {
"type": "array",
"items": {
"type": "array",
"items": {
"type": "number"
}
},
"description": "Outline [[x, y], ...] (3 to 512 points) that mask, polygon and halo draw; required on every detection when one of them is used"
}
},
"required": [
"xyxy"
]
}
},
"annotators": {
"type": "array",
"description": "Annotators applied in order, each a type name or an object {\"type\": ..., options}. Default [box, label]. Put blur, pixelate, color, mask or background_overlay before box and label. Types: box, round_box, box_corner, circle, dot, ellipse, triangle, label, color, mask, polygon, halo, background_overlay, blur, pixelate, percentage_bar. Options use supervision's names: color, color_lookup, thickness, opacity, roundness, corner_length, radius, position, start_angle, end_angle, base, height, width, kernel_size, pixel_size, outline_thickness, outline_color, border_color, border_thickness, force_box, text_color, text_scale, text_thickness, text_padding, text_position, border_radius, smart_position. color: A hex colour like \"#ff8800\" or a name: black, blue, green, grey, red, roboflow, white, yellow (default: supervision's class palette). color_lookup: What picks the colour: \"class\" (default when every detection has a class_id), \"index\" (position in the list) or \"track\" (tracker_id). position and text_position: Anchor point: center, center_left, center_right, top_center, top_left, top_right, bottom_left, bottom_center, bottom_right, center_of_mass",
"items": {
"type": "object",
"properties": {
"type": {
"type": "string",
"description": "Annotator type"
}
},
"required": [
"type"
]
}
},
"class_names": {
"type": "array",
"items": {
"type": "string"
},
"description": "Names indexed by class_id, used in generated labels and in counts.byClass (printable ASCII)"
},
"format": {
"type": "string",
"enum": [
"png",
"jpeg"
],
"description": "Output format (default png)"
},
"quality": {
"type": "integer",
"description": "JPEG quality 1-100 (default 90)"
}
},
"required": [
"image",
"detections"
]
}社区
证据
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