Cardz is my take on playing card localization and classification in a scence with multiple cards.
The model consists of an UNet trained with random card ensembles and their segmentation masks. The trained models can be found in results.
This repository contains a notebook explaining the biggest model and analysing its perfomance using Captum.
Here is a basic table of contents:
- Classifier: Training the model
- Captum: Evaluating the model quality using Captum
The dataset was generated using several decks of cards and the DTD dataset.
@Davanchama (thank you very much) and I made photos of these decks and wrote a script to genrate the dataset.
You can find the dataset on kaggle.
- [1] U-Net: Convolutional Networks for Biomedical Image Segmentation, Olaf Ronneberger, Philipp Fischer, Thomas Brox
- [2] Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization, Ramprasaath R. Selvaraju, Michael Cogswell, et al.