https://github.com/en10/cifar
CIFAR 10 image dataset
https://github.com/en10/cifar
cifar cifar-10 cifar10 gradient-descent logistic-regression sigmoid
Last synced: 6 months ago
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CIFAR 10 image dataset
- Host: GitHub
- URL: https://github.com/en10/cifar
- Owner: EN10
- Created: 2017-10-12T12:09:49.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2024-11-20T20:25:23.000Z (7 months ago)
- Last Synced: 2024-12-05T16:13:21.997Z (7 months ago)
- Topics: cifar, cifar-10, cifar10, gradient-descent, logistic-regression, sigmoid
- Language: Python
- Homepage:
- Size: 28.3 KB
- Stars: 48
- Watchers: 4
- Forks: 12
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# CIFAR 10 in Python
The CIFAR-10 dataset consists of 60000 32x32 colour images in [10 classes](https://github.com/EN10/CIFAR#classes), with 6000 images per class.
There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images.
[CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html)
### Download
wget -c https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
* [CIFAR 10 Python](https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz)
### Extract
tar -xvzf cifar-10-python.tar.gz
### Files:
* `sigmoid.py` : [Based on DL.ai cats.py](https://github.com/EN10/DL.ai/blob/master/w2/cats.py)
* `5_layer.py:` : [Based on DL.ai 5_layer_model.py](https://github.com/EN10/DL.ai/blob/master/w4/5_layer_model.py)
* `load_cifar.py` : load `data_batch_1` data (images) and labels (classes) into a np.array
* `imsave.py` : save an image from CIFAR-10 as JPG
* `class_labels.py` : load `batches.meta` label_names (classes) and print them
* `filter_class.py` : write class label index from `data_batch_1` to class_label.txt
### Accuracy
`load_cifar.py` uses `random.seed(1)` for consistant accuracy
`sigmoid.py:`
train accuracy: 89.0 %
test accuracy: 72.0 %
`5_layer.py:`
train accuracy: 99.0 %
test accuracy: 70.0 %
### Classes:
0 : airplane
1 : automobile
2 : bird
3 : cat
4 : deer
5 : dog
6 : frog
7 : horse
8 : ship
9 : truck
### Ref:
[Batch to Array Code](https://gist.github.com/juliensimon/273bef4c5b4490c687b2f92ee721b546)
### Compatability
[imsave.py](https://github.com/EN10/CIFAR/blob/master/imsave.py) uses `from scipy.misc import imsave` which is deprecated
this requires `sudo pip install scipy==0.16.1`
[save.py](https://github.com/EN10/KerasCIFAR/blob/master/save.py) PIL version