Comments (3)
Thanks for your interest! You can train your classifier similarly to conventional image recognition techniques with pre-trained neural nets. You have two options:
- Extract emotional features with on of my models, and then train a classifier from scikit-learn on top of this features. Example is available at train_emotions-pytorch-afew-vgaf.ipynb. Here the features are extracted from video frames, so I need to aggregate them into a single descriptor (see function create_dataset), but you could skip this step if you have a dataset with static photos.
- Fine-tune the model (head only or the whole model). Example is available at train_emotions-pytorch.ipynb. Just replace the cell starting from "model=timm.create_model('tf_efficientnet_b0_ns', pretrained=False)" to "model=torch.load('../../models/affectnet_emotions/enet_b0_8_best_afew.pt')", and use your own train_dir and test_dir
from face-emotion-recognition.
Thanks for your interest! You can train your classifier similarly to conventional image recognition techniques with pre-trained neural nets. You have two options:
- Extract emotional features with on of my models, and then train a classifier from scikit-learn on top of this features. Example is available at train_emotions-pytorch-afew-vgaf.ipynb. Here the features are extracted from video frames, so I need to aggregate them into a single descriptor (see function create_dataset), but you could skip this step if you have a dataset with static photos.
- Fine-tune the model (head only or the whole model). Example is available at train_emotions-pytorch.ipynb. Just replace the cell starting from "model=timm.create_model('tf_efficientnet_b0_ns', pretrained=False)" to "model=torch.load('../../models/affectnet_emotions/enet_b0_8_best_afew.pt')", and use your own train_dir and test_dir
copy that~so many thanks!! OvO
from face-emotion-recognition.
Closing due to inactivity
from face-emotion-recognition.
Related Issues (20)
- afew test accuracy is around 55% HOT 4
- Accuracy on AffectNet is worse than expected HOT 3
- running code on colab HOT 4
- Time of training HOT 9
- specifications of computer HOT 2
- Missing enet_b0_8_va_mtl.ptl HOT 2
- 'DepthwiseSeparableConv' object has no attribute 'act1'
- range of valence and arousal HOT 4
- How to apply Adaptive Frame Rate model on new dataset? HOT 1
- Fine tuning code HOT 2
- Request for a demo code HOT 3
- Request for guidelines on training on multitask classification HOT 2
- Request for help in the Training Script for enet_b0_8_best_afew.onnx model HOT 2
- docker image HOT 3
- Is it possible to predict action units? HOT 4
- Realtime Performance
- Additional files HOT 4
- Problem with the version of TensorFlow. HOT 2
- The issue with converting .pt to .onnx. HOT 4
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from face-emotion-recognition.