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160 changes: 160 additions & 0 deletions groep6/DSmeetup_waterdetectie.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Detectie van water\n",
"\n",
"\n",
"Schaal van plaatjes: 1 pixel is 10x10cm \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"from PIL import Image\n",
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"# Load image to np-data frame (function from tiff.py)\n",
"\n",
"def img2df(path):\n",
" ''' read an image into a dataframe '''\n",
" img = Image.open(path)\n",
" img.size = (1024, 1024)\n",
" #img.show() # to see image\n",
" arr = np.array(img.getdata())\n",
" df = pd.DataFrame(arr)\n",
" return df\n",
"\n",
"# Specify coordinates and load image:\n",
"coords = '163600.0_563400.0'\n",
"\n",
"# read image\n",
"img = img2df('tegels100x100/data/%s.tif' % coords)\n",
"\n",
"img.columns = ['R', 'G', 'B']\n",
"\n",
"# img.shape = (1048576, 3), which is length (1024x1024) by width 3 (RGB)\n",
"\n",
"# View \n",
"img.head()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Using openCV\n",
"\n",
"\n",
"https://media.readthedocs.org/pdf/opencv-python-tutroals/latest/opencv-python-tutroals.pdf\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
"import cv2\n",
"\n",
"coords = '163600.0_563400.0'\n",
"\n",
"img = cv2.imread('tegels100x100/data/%s.tif' % coords)\n",
"imglabel = cv2.imread('tegels100x100/labels/WaterVlakkenRasterUitBGT_%s.tif' % coords)\n",
"\n",
"def show(image):\n",
" cv2.imshow('image %s.tif' %coords,image) \n",
" # Show image, press ESC to exit\n",
" k = cv2.waitKey(0)\n",
" if k == 27: # wait for ESC key to exit\n",
" cv2.destroyAllWindows()"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"# To see the image:\n",
"show(img)\n",
"show(imglabel)\n",
"\n",
"# Get to the first pixels BGR values, get the green value: (NOTE: order is here BGR instead of RGB)\n",
"img[0,0], img[0,0,1]\n",
"\n",
"# Take red color out:\n",
"#img[:,:,2] =0\n"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [],
"source": [
"# Compare image with its label:\n",
"\n",
"img1 = img\n",
"img2 = imglabel\n",
"dst = cv2.addWeighted(img1,0.5,img2,0.5,0)\n",
"cv2.imshow('dst',dst)\n",
"\n",
"cv2.imwrite('overlapwithlabel.png',dst)\n",
"\n",
"cv2.waitKey(0)\n",
"cv2.destroyAllWindows()\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"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": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}