No description, website, or topics provided.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
deep-learning-models
training
.gitignore
README.md
predict.py

README.md

Product Category Classification Engine

This is a snapshot of the product category classification engine used by Two Tap. It uses glove word vectors and images to categorize a product to a unified taxonomy.

Known issues

The current model is trained mostly on Apparel. It's really bad at electronics and other categories. There's an internal effort to improve this by adding new data.

How to use the it with the pre-trained weights.

  • Clone the repo.
  • Download the pretrained weights from here, unpack them, and place them in the models/ directory.
  • Run: python predict.py.
  • You can edit things there.

The models/ directory should look like below:

models-dir

How to train the model.

  • Download training.csv from here and place it in the ml-data/ directory.
  • Download the glove pre-trained vectors from here and place them in the ml-data/ directory.
  • Run training/download_images.py to fetch all the images.
  • Run training/train.py. This might take a long time.

Check the models/ directory for the model json and weights afterward.

The ml-data/ directory should look like below, but with more images:

ml-data-dir

Want access to the product images so you don't have to download them from the retailers? Email support@twotap.com.