Skip to content

2 missing full stop . #3

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
harsh-kr-jha wants to merge 1 commit into
base: main
Choose a base branch
from
Open

2 missing full stop . #3

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions face-emotion.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,12 +9,12 @@ If you don't have much experience with OpenCV or CNNs, don't worry about it, we
- ### OpenCV
Only the basics of OpenCV would be required for this project. You can learn them [here](https://www.pyimagesearch.com/2018/07/19/opencv-tutorial-a-guide-to-learn-opencv/)
- ### Deep Learning Library (PyTorch/Tensorflow)
Not sure what PyTorch is? Do [this](https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html) tutorial on their website, to get to know the basics. But you need to know about Nerual Networks first. Oh here's where you can learn about NNs, just do [Week 1](https://github.com/wncc/learn-gan#week-1--getting-started) and you're good to go. Also, you need to know what Convolutional Neural Networks are, read and implement [this](https://adventuresinmachinelearning.com/convolutional-neural-networks-tutorial-in-pytorch/) to get an understanding
Not sure what PyTorch is? Do [this](https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html) tutorial on their website, to get to know the basics. But you need to know about Nerual Networks first. Oh here's where you can learn about NNs, just do [Week 1](https://github.com/wncc/learn-gan#week-1--getting-started) and you're good to go. Also, you need to know what Convolutional Neural Networks are, read and implement [this](https://adventuresinmachinelearning.com/convolutional-neural-networks-tutorial-in-pytorch/) to get an understanding .

## Pathway
- First we need a dataset. Download it from [here](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data?select=fer2013.tar.gz). You can use also type this in your CLI instead
`kaggle competitions download -c challenges-in-representation-learning-facial-expression-recognition-challenge`
- Split the data into *training* and *validation* sets, this is can be done in a ratio of about 10:1 or less
- Split the data into *training* and *validation* sets, this is can be done in a ratio of about 10:1 or less .
- Now augment the image data using Pytorch. Learn it [here](https://pytorch.org/docs/stable/torchvision/transforms.html)
- Now, code a CNN model, based on what you learnt from the link in prerequisites. A block would contain a Conv2D layer, Activation layer, BatchNorm, MaxPool, Dropout(optional). Create several such blocks (with successive blocks having double filters in Conv2D layer). Finally include a Flatten Layer, Dense layer, Activation layer. This, of course, is just a blueprint to give you direction. We'd encourage to try out different parameters and tinker around with the model to get some more practical knowledge.
- Now come the standard training, testing, and hyperparameter training. After this, you can save the model to be used to create the emotion detector.
Expand Down