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A python client for doc.ai's Imagine API

Project description

Imagine Client for Python

This library allows you to easily connect to doc.ai's Imagine API.

Supported Image Models

Model Id Type Description
phenomenal-face image Given a facial image, this model infers the age, sex, height, and weight of a person
happy-face image Given a facial image, this model infers the mood of a person
manna image Given a food image, this model infers whether the food is healthy/unhealthy
face-detector image Given an image, this model detects whether a face is present
food-detector image Given an image, this model detects whether food is present

API

ImageBasedModel.create(imagine_client, model_id)

Given an ImagineClient (imagine_client) and string (model_id), creates an image model. See the "Supported Image Models" section for a list of supported model ids.

ImageBasedModel.infer(image_file_stream, store=false, metadata=None)

Performs the model's inference on an image. A read stream should be passed as the parameter (image_file_stream).

ImageBasedModel.insert_correction(corrections_dict, metadata=None)

Uploads a correction label to the imagine API, for a given inference.

ImageBasedModel.insert_prediction(predictions_dict, metadata=None)

(FOR EDGE PREDICTIONS) Uploads a prediction label to the imagine API, for a given inference.

Example

from imagine_client_py import ImagineClient, ImageBasedModel

# Required parameters
API_KEY = <VALID_IMAGINE_API_KEY>
IMAGE_PATH = <IMAGE_FILE_PATH>
CLIENT_ID = <ANY_CLIENT_ID>

# Initialize imagine client
imagine_client = ImagineClient({
  'api_key': API_KEY,
  'client_id': CLIENT_ID
})

# Create the 'happy-face' model interface
model = ImageBasedModel.create(imagine_client, 'happy-face')

# Create a read stream to a image file
with open(IMAGE_PATH, 'rb') as image_face_file:
  # Perform the model's inference, on the image.
  result = model.infer(image_face_file)

##Tests

To run tests:

export IMAGINE_API_KEY=<API key> IMAGINE_CLIENT_ID=test
pytest

Project details


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