resize_motionpatches.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import cv2\n",
"from glob import glob\n",
"import os \n",
"\n",
"motionpatch_location = './motionpatch/*.png'\n",
"output_location = './smallone/'\n",
"count = 0\n",
"for f in glob(motionpatch_location):\n",
" count += 1\n",
" image = cv2.imread(f)\n",
" small = cv2.resize(image,dsize=(25,25))\n",
" dst = os.path.join(output_location +str(count)+\".png\")\n",
" cv2.imwrite(dst,small)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
" def __init__(self, data_files):\n",
" IMAGE_WIDTH = 25\n",
" IMAGE_HEIGHT = 25\n",
" self.image_mode = 'RGB'\n",
" image_channels = 3\n",
" self.data_files = data_files\n",
" self.shape = len(data_files), IMAGE_WIDTH, IMAGE_HEIGHT, image_channels\n",
" \n",
" def get_image(iself,image_path, width, height, mode):\n",
" image = Image.open(image_path)\n",
" image = Image.im2double(image)\n",
" return np.array(image)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"from PIL import Image\n",
"import numpy as np\n",
"from matplotlib import pyplot\n",
"\n",
"imgloc = './smallone/5004.png'\n",
"image = Image.open(imgloc)\n",
"dst = os.path.join(\"./samples/5004.png\")\n",
"pyplot.imsave(dst,image)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}