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ML Models for Single-Line Drawings

Project description

singleline_models

Install

pip install singleline_models

Models

Sketch RNN

PyTorch implementation of the SketchRNN paper, A Neural Representation of Sketch Drawings.

Sketch RNN learns to reconstruct stroke-based drawings, by predicting a series of strokes. It uses a sequence-to-sequence LSTM model, with gaussian mixture heads to produce a sequence of stroke coordinates.

seq2seq model

Datasets

  • data/quickdraw/: Sample data from Quick, Draw! Dataset
  • data/look/: Custom dataset of single-line drawings by @andrewlook

All data is stored in stroke-3 format, meaning a list with three columns:

  • delta_x
  • delta_y
  • lift_pen (if 1, “lift the pen” and start a new stroke; otherwise 0)

stroke-3 turtle

Acknowledgements

Improvements

  • Log epoch and learning rate
  • LR decay
  • ETA decay (for KL loss)
  • Dropout
  • Layer Normalization
  • Recurrent Dropout

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