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Give the function an input and it will return a dictionary of detected faces and expression predictions.
This is a python3 cli for Facial Expression Recognition (FER) using Keras and OpenCV.
This project uses the haarcascade xml for facial detection.
We recommend using our model for this application, but you may use your own as well. This project could be easily modified to do other types of object detection if you wish.
If you fork this project, please contribute back with any fixes or features the community may find useful. All PRs will go through a member of our Engineering team.
Please follow GitHub's template for bug reporting.
Note this requires the installation of Tensorflow 2+
$ pip3 install fer-capture
$ git clone git@github.com:IntrospectData/id-fer-capture.git
$ python3 -m venv env
$ source env/bin/activate
(env) $ pip3 install id-fer-capture
id-fer_capture[cpu]
for cpu based tensorflowid-fer_capture[gpu]
for gpu based tensorflow>>> from fer_capture.main import check_stream
>>> from fer_capture.main import check_image
>>> check_stream("/mnt/storage/face_test.mp4")
[{'faces': {...}}, ...]
>>> check_image("/mnt/storage/face.jpeg")
{'faces': {...}}
Append the argument show=True
to either function to have a window display. You can press/hold any key for the frame to update in this mode.
FAQs
Takes an image or video/stream as input and returns detected faces and emotions.
We found that id-fer demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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