Image classification tool for Classificationbox.
- Read the blog post: Build a machine learning image classifier from photos on your hard drive very quickly
- Prepare teaching images
- Run Classificationbox
- Teach and test
Create a directory structure that organizes the images into classes, with each folder as the class name:
/teaching-images
/class1
class1example1.jpg
class1example2.jpg
class1example3.jpg
/class2
class2example1.jpg
class2example2.jpg
class2example3.jpg
/class3
class3example1.jpg
class3example2.jpg
class3example3.jpg
In a terminal do:
docker run -p 8080:8080 -e "MB_KEY=$MB_KEY" machinebox/classificationbox
- Get yourself an
MB_KEY
from https://machinebox.io/account
Use the imgclass
tool to teach the
imgclass -teachratio 0.8 -src ./teaching-images
The tool will post a random 80% (-teachratio 0.8
) of the images to Classificationbox for teaching, and the
remaining images will be used to test the model.
You will be prompted a few times as the tool goes through its various stages. The tool will:
- Create a new model
- Use a percentage of the data to teach the model
- Use the remaining images to validate the model
- Display the results, including the percentage accurary of the model