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
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