face-emotion-recognition
Efficient face emotion recognition in photos and videos (by av-savchenko)
malaya
Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/ (by mesolitica)
face-emotion-recognition | malaya | |
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1 | 1 | |
581 | 457 | |
- | 1.3% | |
5.8 | 9.0 | |
19 days ago | 7 days ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
face-emotion-recognition
Posts with mentions or reviews of face-emotion-recognition.
We have used some of these posts to build our list of alternatives
and similar projects.
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[Research] Emotion recognition using videos on mobile devices
Yes, the training code is available in the co-author's github repository: https://github.com/HSE-asavchenko/face-emotion-recognition/tree/main/src There's code for several models that we tried training using the proposed approach. The best one turned out to be the EfficientNet-B0 model.
malaya
Posts with mentions or reviews of malaya.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Public Sentiment regarding COVID19 from Malay Tweets vs Daily Case Numbers of Malaysia
Hey guys! I've been doing some web scraping on Malay tweets regarding COVID19. I decided to do some sentiment analysis using a NLP model (model is publicly available at https://github.com/huseinzol05/malaya). What the model does is taking in a chunk of text and outputs a sentiment score between 0 to 1 (1 being the text has 100% positive sentiment and 0 being the text is 100% negative). The model is not 100% accurate but it is considered to be comparable to other state-of-the-art models.
What are some alternatives?
When comparing face-emotion-recognition and malaya you can also consider the following projects:
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
human - Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition
afinn - AFINN sentiment analysis in Python
fer - Facial Expression Recognition with a deep neural network as a PyPI package
tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).