Skip to content

This task involves the use of binary leaf images and extracted features, including shape, margin & texture, to accurately identify 99 species of plants. Leaves, due to their volume, prevalence, and unique characteristics, are an effective means of differentiating plant species.

Notifications You must be signed in to change notification settings

abhmul/LeafClassification

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

52 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

NOTE: This was written before Keras v2 and will likely not run anymore with an updated version of Keras. Please see the JuPyter Kernel for an overview of the code in this repository

LeafClassification

This task involves the use of binary leaf images and extracted features, including shape, margin & texture, to accurately identify 99 species of plants. Leaves, due to their volume, prevalence, and unique characteristics, are an effective means of differentiating plant species.

My current convolutional model performs very well, with nearly 100% accuracy and a .009 logloss on the Kaggle Competition testset. It works by first inputting the images into two convolutional layers, then concatenating the embedding that comes out with the numerical extracted features. Then it goes through one last dense layer before calculating the outputs.

Training the model

To train the combined model simply run

cd src
python kfold_train.py

Visualization

To run the visualization script to see what the neural network is doing in the convolutional layers, run

cd src
python visualization.py

JuPyter Kernel

Check out my JuPyter Kernel outlining this solution on Kaggle!

About

This task involves the use of binary leaf images and extracted features, including shape, margin & texture, to accurately identify 99 species of plants. Leaves, due to their volume, prevalence, and unique characteristics, are an effective means of differentiating plant species.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages