Skip to content

QMIND-Team/MaterialDetection

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MaterialDetection

VGG16 CNN with dense top trained on subset of data The user will have to update train_loc and test_loc with the file path to the train and test folders. The reduced data set is available through Google Drive at: https://drive.google.com/open?id=1MhvONKcaX6F6q0O1VKzht8_n9M4QTvex. It should already be in the correct format, so just download it.

VGG_demo.py: Holds a pretrained VGG16 network that can be used to classify an object, edit line 11 with desired directory

VGG_try1.py: 1st attempt at a fine tuned VGG16 network, froze all convolutional weights and only working with the dense layer on top

About

VGG16 CNN with dense top trained on subset of data

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages