mirror of
https://github.com/wassname/IndicoIo-python.git
synced 2026-06-27 16:10:34 +08:00
Chris Lee
37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
import requests
|
|
|
|
from indicoio.utils.api import api_handler
|
|
from indicoio.utils.image import image_preprocess
|
|
import indicoio.config as config
|
|
|
|
def fer(image, cloud=None, batch=False, api_key=None, **kwargs):
|
|
"""
|
|
Given a grayscale input image of a face, returns a probability distribution over emotional state.
|
|
Input should be in a list of list format, resizing will be attempted internally but for best
|
|
performance, images should be already sized at 48x48 pixels..
|
|
|
|
Example usage:
|
|
|
|
.. code-block:: python
|
|
|
|
>>> from indicoio import fer
|
|
>>> import numpy as np
|
|
>>> face = np.zeros((48,48)).tolist()
|
|
>>> emotions = fer(face)
|
|
>>> emotions
|
|
{u'Angry': 0.6340586827229989, u'Sad': 0.1764309536057839,
|
|
u'Neutral': 0.05582989039191157, u'Surprise': 0.0072685938275375344,
|
|
u'Fear': 0.08523385724298838, u'Happy': 0.04117802220878012}
|
|
|
|
:param image: The image to be analyzed.
|
|
:type image: list of lists
|
|
:rtype: Dictionary containing emotion probability pairs
|
|
"""
|
|
|
|
image = image_preprocess(image, batch=batch,
|
|
size=None if kwargs.get("detect") else (48, 48)
|
|
)
|
|
|
|
url_params = {"batch": batch, "api_key": api_key}
|
|
return api_handler(image, cloud=cloud, api="fer", url_params=url_params, **kwargs)
|