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.
Datasets
data/quickdraw/: Sample data from Quick, Draw! Datasetdata/look/: Custom dataset of single-line drawings by @andrewlook
All data is stored in stroke-3 format, meaning a list with three columns:
delta_xdelta_ylift_pen(if1, “lift the pen” and start a new stroke; otherwise0)
Acknowledgements
- PyTorch Sketch RNN project by Alexis David Jacq
- Annotated Sketch RNN in PyTorch by LabML
- Tensorflow SketchRNN by Magenta Team and David Ha
- sketch-rnn-datasets by David Ha
- SketchRNN-Pytorch by OhataKenji
Improvements
- Log epoch and learning rate
- LR decay
- ETA decay (for KL loss)
- Dropout
- Layer Normalization
- Recurrent Dropout
1 maintainer
Release files for singleline-models 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| singleline_models-0.0.2.tar.gz | 37.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| singleline_models-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 85.0 kB
Release files / singleline_models-0.0.2.tar.gz
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| Size | 37.7 kB |
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Release files / singleline_models-0.0.2-py3-none-any.whl
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| Size | 47.3 kB |
| Tags | Python 3 |
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