91 lines
1.7 KiB
Plaintext
91 lines
1.7 KiB
Plaintext
{
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"cells": [
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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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"from PIL import Image\n",
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"import numpy as np"
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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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"img = Image.open('uiuc.png').convert('RGB')"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(200, 720, 3)"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.shape(img)"
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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": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"f = open('uiuc_array.c', 'w')\n",
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"for y in range(np.shape(img)[0]):\n",
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" for x in range(np.shape(img)[1]):\n",
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" r, g, b = np.array(img)[y, x, :]\n",
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" data = ((r >> 3) << 11) + ((g >> 2) << 5) + (b >> 3)\n",
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"# data = (r << 16) + (g << 8) + b\n",
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" f.write('%s,' % hex(data))\n",
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" if(24 == x % 30):\n",
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" f.write('\\n')\n",
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" f.write('\\n')\n",
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"f.close()"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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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": "3.7.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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