Skip to main content

Recognizing facial expressions from images, videos and real-time stream

Project description

Cerebro

Cerebro is a python package for Facial Expression Detection, we provide a trained model with accuracy around 98% of 8 emotions [Happy, surprise, contempt, sad ,angry,disgust,Neutral,Fear], with a very simple interface for detection from image,video with any rotation and Real time streaming.

Documentation

Example In this Example we get an image , predict an emotion then save it with the emotion.

from interface import video_stream as vs
from interface import process_image as pi

def main():
	im = cv2.imread("interface/7.jpg")
	items =pi.extract_faces_emotions(im)
	im =pi.mark_faces_emotions(im)
	cv2.imwrite("interface/77.jpg",im)
	cv2.imshow("detected emotions",im)
	cv2.waitKey(0)

if __name__ == '__main__': main()

alt text

Installition Cerebro depends on some python packages, once you install Cerebro any missing Module will be automatically installed, for FFmpeg use this link.

Installation by hand: download the sources, either from PyPI or, if you want the development version, from GitHub, clone the project then use this command in terminal to setup.

$ (sudo) python setup.py install

Installation with pip: if you have pip installed, just type this in a terminal:

$ (sudo) pip install CEREBRO8 Using Model : once You install Cerebro You have to dowenload our trained model from this link and full model link then add them to new foldercalled saved-models Using Landmark : if you want to use Landmark feature extractor you have to dowenload this file landmarks with 68 point using this link in this path saved-models/face-landmarks "create new folder called landmarks in saved-models"

Video demo

Real Time demo

Maintainers

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

CEREBRO8-0.0.1.tar.gz (14.0 kB view details)

Uploaded Source

Built Distribution

CEREBRO8-0.0.1-py3-none-any.whl (31.8 kB view details)

Uploaded Python 3

File details

Details for the file CEREBRO8-0.0.1.tar.gz.

File metadata

  • Download URL: CEREBRO8-0.0.1.tar.gz
  • Upload date:
  • Size: 14.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.6.8

File hashes

Hashes for CEREBRO8-0.0.1.tar.gz
Algorithm Hash digest
SHA256 823187a2beea405dc49553528d6dcaa50d7f6e22d7d8b5c7a35977760bb88a8a
MD5 e6c42b51557c084af1dda3920018a010
BLAKE2b-256 21df7a588c5d6de116ad78f2ad84bc85898a4dbfabb38ca14ebfe51d44816cdd

See more details on using hashes here.

File details

Details for the file CEREBRO8-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: CEREBRO8-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 31.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.6.8

File hashes

Hashes for CEREBRO8-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 d1ed548924bd1ff54f34ea447ba91610cc9eb6d7bae344c6571dcd8dd19d8677
MD5 5996ec119044942fd1693bd4056f7ccc
BLAKE2b-256 b3e8f12e6685b8a7e2dfa04b4f0865711f0391ed8eb6d16c53fe695fd817513f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page