Keypoint Detection
Run inference on your object detection models hosted on Roboflow.
To run inference through our hosted API using Python, use the roboflow
Python package:
from roboflow import Roboflow
rf = Roboflow(api_key="API_KEY")
project = rf.workspace().project("MODEL_ENDPOINT")
model = project.version(VERSION).model
# infer on a local image
print(model.predict("your_image.jpg", confidence=40, overlap=30).json())
# visualize your prediction
# model.predict("your_image.jpg", confidence=40, overlap=30).save("prediction.jpg")
# infer on an image hosted elsewhere
# print(model.predict("URL_OF_YOUR_IMAGE", hosted=True, confidence=40, overlap=30).json())
Response Object Format
The hosted API inference route returns a JSON
object containing an array of predictions. Each prediction has the following properties:
x
= the horizontal center point of the detected objecty
= the vertical center point of the detected objectwidth
= the width of the bounding boxheight
= the height of the bounding boxclass
= the class label of the detected objectconfidence
= the model's confidence that the detected object has the correct label and position coordinateskeypoints
= an array of keypoint predictionsx
= horizontal center of keypoint (relative to image top-left corner)y
= vertical center of keypoint (relative to image top-left corner)class_name
= name of keypointclass_id
= id of keypoint, maps to skeletonvertices
in version record, to map vertex color and skeleton edges, View your Project Versionconfidence
= confidence that the keypoint has correct position, and is visible (not occluded or deleted)
Here is an example response object from the REST API:
{
"predictions": [
{
"x": 189.5,
"y": 100,
"width": 163,
"height": 186,
"class": "helmet",
"confidence": 0.544,
"keypoints": [
{
"x": 189,
"y": 20,
"class_name": "top",
"class_id": 0,
"confidence": 0.91
},
{
"x": 188,
"y": 180,
"class_name": "bottom",
"class_id": 1,
"confidence": 0.93
}
]
}
],
"image": {
"width": 2048,
"height": 1371
}
}
The image
attribute contains the height and width of the image sent for inference. You may need to use these values for bounding box calculations.
Inference API Parameters
Using the Inference API
POST
https://detect.roboflow.com/:datasetSlug/:versionNumber
You can POST a base64 encoded image directly to your model endpoint. Or you can pass a URL as the image
parameter in the query string if your image is already hosted elsewhere.
Path Parameters
datasetSlug
string
The url-safe version of the dataset name. You can find it in the web UI by looking at the URL on the main project view or by clicking the "Get curl command" button in the train results section of your dataset version after training your model.
version
number
The version number identifying the version of of your dataset
Query Parameters
image
string
URL of the image to add. Use if your image is hosted elsewhere. (Required when you don't POST a base64 encoded image in the request body.) Note: don't forget to URL-encode it.
classes
string
Restrict the predictions to only those of certain classes. Provide as a comma-separated string. Example: dog,cat Default: not present (show all classes)
overlap
number
The maximum percentage (on a scale of 0-100) that bounding box predictions of the same class are allowed to overlap before being combined into a single box. Default: 30
confidence
number
A threshold for the returned predictions on a scale of 0-100. A lower number will return more predictions. A higher number will return fewer high-certainty predictions. Default: 40
stroke
number
The width (in pixels) of the bounding box displayed around predictions (only has an effect when format
is image
).
Default: 1
labels
boolean
Whether or not to display text labels on the predictions (only has an effect when format
is image
).
Default: false
format
string
json - returns an array of JSON predictions. (See response format tab).
image - returns an image with annotated predictions as a binary blob with a Content-Type
of image/jpeg
. image_and_json - returns an array of JSON predictions, including a visualization field in base64.
Default: json
api_key
string
Your API key (obtained via your workspace API settings page)
Request Body
string
A base64 encoded image. (Required when you don't pass an image URL in the query parameters).
{
"predictions": [{
"x": 234.0,
"y": 363.5,
"width": 160,
"height": 197,
"class": "hand",
"confidence": 0.943
}, {
"x": 504.5,
"y": 363.0,
"width": 215,
"height": 172,
"class": "hand",
"confidence": 0.917
}, {
"x": 1112.5,
"y": 691.0,
"width": 139,
"height": 52,
"class": "hand",
"confidence": 0.87
}, {
"x": 78.5,
"y": 700.0,
"width": 139,
"height": 34,
"class": "hand",
"confidence": 0.404
}]
}
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