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β’
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Boilerplate for Trainer and Model classes
Browse files- README.md +5 -0
- notebooks/model.ipynb +56 -0
- notebooks/{preprocessing.ipynb β trainer.ipynb} +0 -0
README.md
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@@ -13,3 +13,8 @@ Create and deploy to production a simple neural network for Computer Vision
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* [LabelMe 12 50k](https://www.kaggle.com/datasets/dschettler8845/labelme-12-50k)
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* [City-Scapes](https://www.cityscapes-dataset.com/dataset-overview/)
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* [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/)
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* [LabelMe 12 50k](https://www.kaggle.com/datasets/dschettler8845/labelme-12-50k)
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* [City-Scapes](https://www.cityscapes-dataset.com/dataset-overview/)
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* [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/)
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# References
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* [DSNet-Fast](https://www.researchgate.net/figure/The-architecture-of-fast-dense-segmentation-network-DSNet-fast-The-encoder-is_fig1_347180093)
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* [DSNet](https://www.researchgate.net/figure/The-architecture-of-dense-segmentation-network-DSNet-The-encoder-is-a-fully-convolutional_fig1_347180092)
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notebooks/model.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true,
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"import random\n",
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"\n",
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"import numpy as np\n",
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"from jax import numpy as jnp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"outputs": [],
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"source": [
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"class"
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],
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"metadata": {
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"collapsed": false,
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"pycharm": {
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"name": "#%%\n"
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}
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}
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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notebooks/{preprocessing.ipynb β trainer.ipynb}
RENAMED
File without changes
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