Nodeflux Cloud Client Library for Python.
Project description
Nodeflux Cloud Client Library for Python
Installation
pip install nodeflux-cloud
Usage
Set the environment variable NODEFLUX_ACCESS_KEY
and NODEFLUX_SECRET_KEY
to your keys.
from nodeflux.cloud.clients import ImageAnalyticClient
from nodeflux.cloud.requests import ImageAnalyticRequest, AnalyticTypes
client = cloud.ImageAnalyticClient()
with open("some-image.jpg", "rb") as image_file:
image_content = image_file.read()
requests = [
ImageAnalyticRequest(
image=image_content,
analytics=[
AnalyticTypes.FACE_DETECTION,
AnalyticTypes.FACE_DEMOGRAPHY,
]
)
]
response = client.batch_image_analytic(requests)
print(response)
API Reference
class ImageAnalyticClient(transport=None)
Service that performs Nodeflux Cloud image analytics.
Parameters | Type | Description |
---|---|---|
transport |
ImageAnalyticGrpcTransport |
Transport for the API call. The default transport uses gRPC protocol. |
batch_image_analytic
Run analytics to a batch of images.
Parameters | Type | Description |
---|---|---|
requests |
List[ImageAnalyticRequest] |
A batch of Nodeflux Cloud image analytic request. |
class ImageAnalyticRequest(image: bytes, analytics: List[AnalyticTypes])
Individual image request to be analyzed by Nodeflux Cloud.
Parameters | Type | Description |
---|---|---|
image |
bytes |
Image to be analyzed in the Nodeflux Cloud. |
analytics |
List[AnalyticTypes] |
A list of analytics to be performed to the image. |
class AnalyticTypes
Enums of analytic types supported by Nodeflux Cloud.
Enums | Description |
---|---|
FACE_DETECTION |
Detect faces from an image. |
FACE_DEMOGRAPHY |
Predict age and gender from faces in the image. |
FACE_RECOGNITION |
Search for similar faces in the face recognition database. |
VEHICLE_RECOGNITION |
Detect vehicles from an image. |
LICENSE_PLATE_RECOGNITION |
Recognize license plate number of vehicles in an image. |
class BatchmageAnalyticResponse
Response from Nodeflux Cloud image analytic request.
face_detections: List[FaceDetection]
If present, face detection analytic has completed successfully.
face_demographics: List[FaceDemography]
If present, face demography analytic has completed successfully.
face_recognitions: List[FaceRecognition]
If present, face recognition analytics has completed successfully.
vehicle_detections: List[VehicleDetection]
If present, vehicle detection analytics has completed successfully.
license_plate_recognitions: List[LicensePlateRecognition]
If present, license plate recognition analytics has completed successfully.
class FaceDetection
bounding_box: BoundingBox
Bounding box around the detected face.
confidence: float
Confidence of the face detection.
class FaceDemography
gender: Gender
Detected gender from a face.
gender_confidence: float
Confidence of gender detection
age_range: AgeRange
The estimated age range.
class FaceRecognition
candidates: List[FaceCandidate]
List of candidates that matches the requested face. If candidates is set, the face recognition analytic has been successful.
class FaceCandidate
id: int64
Unique id of the recognized face.
confidence: float
Confidence of the recognition.
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