Skip to content

🥸✅ 🐵❌Developing a babysitting algorithm to preprocess CIFAR10 and FDDB Dataset and train them on Alexnet using Pytorch

License

Notifications You must be signed in to change notification settings

MathewAaron/Babysitting-A-Dataset-Using-Pytorch-and-Alexnet

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

How to run the code?

Dataset:

Extract the FDDB_dataset.zip. There will be two folders called training and testing respectively.

**Copy the local directory till ../../dataset/ **

*Change the argparse in the main.py file*

 parser.add_argument("directory", help="Directory of the dataset",nargs = '?',default = " *Add directory here*/dataset/")

main.py

change the sys.append() to the directory of the project.

Run the code:

python3 main.py

The default argparser will run for FDDB dataset, with SGD optimizer. Change the optimizer to SGD in the default value.

The code for CIFAR10 is run on google collab due to GPU.

About

🥸✅ 🐵❌Developing a babysitting algorithm to preprocess CIFAR10 and FDDB Dataset and train them on Alexnet using Pytorch

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages