116 строки
2.6 KiB
Plaintext
116 строки
2.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Visualizing Rotated MINST samples"
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"#Common imports\n",
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"import os\n",
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"import random\n",
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"import copy\n",
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"import numpy as np\n",
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"\n",
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"#Pillow\n",
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"from PIL import Image \n",
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"import PIL \n",
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"\n",
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"#Matplotlib\n",
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"from matplotlib.pyplot import imshow\n",
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"\n",
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"#Pytorch\n",
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"import torch\n",
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"import torch.utils.data as data_utils\n",
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"from torchvision import datasets, transforms"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"data_obj= datasets.MNIST('../../data/rot_mnist',\n",
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" train=True,\n",
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" download=False,\n",
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" transform=transforms.ToTensor()\n",
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" )\n",
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"train_loader = torch.utils.data.DataLoader(data_obj,\n",
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" batch_size=60000,\n",
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" shuffle=False)\n",
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"\n",
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"\n",
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"for i, (x, y) in enumerate(train_loader):\n",
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" mnist_imgs = x\n",
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" mnist_labels = y"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"to_pil= transforms.Compose([\n",
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" transforms.ToPILImage(),\n",
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" ])\n",
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"angles=[0, 15, 30, 45, 60, 75, 90]"
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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": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"indice= random.randint(0, mnist_imgs.shape[0])\n",
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"mnist_img= mnist_imgs[indice]\n",
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"rotated_imgs=[]\n",
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"for angle in angles:\n",
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" rotated_imgs.append( transforms.functional.rotate( to_pil(mnist_img), angle) )"
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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": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"counter=0\n",
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"for img in rotated_imgs:\n",
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" img.save('../../results/rot_mnist/images/' + str(angles[counter]) + '.jpg')\n",
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" counter+=1"
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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": 3
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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": "ipython3",
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"version": "3.7.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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