People Emotion Recognition
Raise your platform’s efficiency with the fast and powerful sentiment recognition
With this CNN for facial emotion recognition, you can save expenses for video analytics automation and raise the effectiveness of your business, customer satisfaction, and sales.
Applications The PER model can recognize on video streams, records, and images all types of people’s emotions according to Dr. Ekman:
It also recognizes all combinations of these emotions.
You can best use this model in retail marketing for:
- analyzing customers’ reaction to your commodities and services
- creating heat maps Installation and Use
- assessing your marketing strategy
Installation and Use (Linux/MacOS)
1) download project / library
2) Install library `pip install *.whl` OR `python setup.py install`
How to use
- Python interface
import cv2 from model import Model import argparse import sys image = cv2.imread('../tests/surprised.jpg') model = Model() ret = model.process_sample(image) print(ret) # Text Output image = cv2.putText(image, str(ret), (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2, cv2.LINE_AA) cv2.imshow('Emotions', image) key = cv2.waitKey(5000) #pauses for 5 seconds before fetching next image
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