search

SEERNET / deepaffects-python

Python library for DeepAffects API
https://developers.deepaffects.com
MIT License
11 stars 9 forks source link

readme

deepaffects-python

Build Status PyPI version

Python client library for DeepAffects APIs

Requirements.

Python 2.7 and 3.3+

pymediainfo >= 2.1.9, this is a wrapper library around mediainfo, which we use to extract the sampling rate and codec information from audio files.

Installation

pip install

The python package can be installed directly from pip using:

pip install deepaffects

pip install from github

The python package is hosted on Github, you can install directly from Github

pip install git+https://github.com/SEERNET/deepaffects-python.git

(you may need to run pip with root permission: sudo pip install git+https://github.com/SEERNET/deepaffects-python.git)

Then import the package:

import deepaffects

Setuptools

Install via Setuptools.

python setup.py install --user

(or sudo python setup.py install to install the package for all users)

Then import the package:

import deepaffects

Documentation for Authorization

DeepAffects API authenticates all the api requests via API Key.

For API key registration and setup, checkout our quickstart guide

UserSecurity

Getting Started

Please follow the installation instruction and execute the following python code:

from __future__ import print_function
import time
import deepaffects
from deepaffects.rest import ApiException
from pprint import pprint

# Configure API key authorization: UserSecurity
deepaffects.configuration.api_key['apikey'] = 'YOUR_API_KEY'
# create an instance of the API class
api_instance = deepaffects.DenoiseApi()
body = deepaffects.Audio.from_file('/path/to/file') # Audio | Audio object that needs to be denoised.
webhook = 'webhook_example' # str | The webhook url where result from async resource is posted
request_id = 'request_id_example' # str | Unique identifier for the request (optional)

try:
    # Denoise an audio file
    api_response = api_instance.async_denoise_audio(body, webhook, request_id=request_id)
    pprint(api_response)
except ApiException as e:
    print("Exception when calling DenoiseApi->async_denoise_audio: %s\n" % e)

Documentation for API Endpoints

All URIs are relative to https://localhost

Class Method HTTP request Description
DenoiseApi async_denoise_audio POST /api/v1/async/denoise Denoise an audio file
DenoiseApi sync_denoise_audio POST /api/v1/sync/denoise Denoise an audio file
DiarizeApiV2 async_diarize_audio POST /api/v2/async/diarize Diarize an audio file
DiarizeApi async_diarize_audio POST /api/v1/async/diarize Diarize an audio file (Legacy)
DiarizeApi sync_diarize_audio POST /api/v1/sync/diarize Diarize an audio file (Legacy)
EmotionApi async_recognise_emotion POST /api/v1/async/recognise_emotion Find emotion in an audio file
EmotionApi sync_recognise_emotion POST /api/v1/sync/recognise_emotion Find emotion in an audio file
FeaturizeApi async_featurize_audio POST /api/v1/async/featurize featurize an audio file
FeaturizeApi sync_featurize_audio POST /api/v1/sync/featurize featurize an audio file

Documentation For Models

UserSecurity

About

DeepAffects is an emotional intelligence analysis engine that measures the effect emotional intelligence has on team dynamics, and provides emotional analytics that serve as the basis of insights to improve project management, performance and satisfaction across organizations, projects, and teams. To watch DeepAffects in action: check out DeepAffects Atlassian JIRA addon and our Github addon.