Created
March 6, 2016 08:27
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"import numpy as np\n", | |
"import pandas as pd" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([[[ 36, 28, 237],\n", | |
" [ 29, 230, 181],\n", | |
" [ 0, 0, 0]],\n", | |
"\n", | |
" [[ 36, 28, 237],\n", | |
" [ 29, 230, 181],\n", | |
" [ 29, 230, 181]]], dtype=uint8)" | |
] | |
}, | |
"execution_count": 2, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"img = np.array([\n", | |
" [[36,28,237],[29,230,181],[0,0,0]],\n", | |
" [[36,28,237],[29,230,181],[29,230,181]]\n", | |
"], np.uint8)\n", | |
"img" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([[1, 0, 0],\n", | |
" [1, 0, 0]], dtype=uint8)" | |
] | |
}, | |
"execution_count": 3, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"alpha = np.array([[1,0,0],[1,0,0]],np.uint8)\n", | |
"alpha" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>a</th>\n", | |
" <th>b</th>\n", | |
" <th>g</th>\n", | |
" <th>r</th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>0</th>\n", | |
" <td>1</td>\n", | |
" <td>237</td>\n", | |
" <td>28</td>\n", | |
" <td>36</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>1</th>\n", | |
" <td>0</td>\n", | |
" <td>181</td>\n", | |
" <td>230</td>\n", | |
" <td>29</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2</th>\n", | |
" <td>0</td>\n", | |
" <td>0</td>\n", | |
" <td>0</td>\n", | |
" <td>0</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3</th>\n", | |
" <td>1</td>\n", | |
" <td>237</td>\n", | |
" <td>28</td>\n", | |
" <td>36</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>4</th>\n", | |
" <td>0</td>\n", | |
" <td>181</td>\n", | |
" <td>230</td>\n", | |
" <td>29</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>5</th>\n", | |
" <td>0</td>\n", | |
" <td>181</td>\n", | |
" <td>230</td>\n", | |
" <td>29</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" a b g r\n", | |
"0 1 237 28 36\n", | |
"1 0 181 230 29\n", | |
"2 0 0 0 0\n", | |
"3 1 237 28 36\n", | |
"4 0 181 230 29\n", | |
"5 0 181 230 29" | |
] | |
}, | |
"execution_count": 4, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"# tohle asi neni uplne efektivni, nejspis se da 3. dimenze vyselektovat nejak lip...\n", | |
"img_f = np.ndarray.flatten(img)\n", | |
"alpha_f = np.ndarray.flatten(alpha)\n", | |
"rgba = pd.DataFrame({\"r\": img_f[0::3],\"g\": img_f[1::3], \"b\": img_f[2::3], \"a\": alpha_f})\n", | |
"rgba" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>a</th>\n", | |
" <th>b</th>\n", | |
" <th>g</th>\n", | |
" <th>r</th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>0</th>\n", | |
" <td>1</td>\n", | |
" <td>237</td>\n", | |
" <td>28</td>\n", | |
" <td>36</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3</th>\n", | |
" <td>1</td>\n", | |
" <td>237</td>\n", | |
" <td>28</td>\n", | |
" <td>36</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" a b g r\n", | |
"0 1 237 28 36\n", | |
"3 1 237 28 36" | |
] | |
}, | |
"execution_count": 5, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"rgba.loc[rgba[\"a\"]==1]" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 2", | |
"language": "python", | |
"name": "python2" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 2 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython2", | |
"version": "2.7.9" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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