{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " Loading BokehJS ...\n", "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", "(function(global) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", " if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", " window._bokeh_onload_callbacks = [];\n", " window._bokeh_is_loading = undefined;\n", " }\n", "\n", "\n", " \n", " if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n", " window._bokeh_timeout = Date.now() + 5000;\n", " window._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", " \"
\\n\"+\n", " \"

\\n\"+\n", " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", " \"

\\n\"+\n", " \"\\n\"+\n", " \"\\n\"+\n", " \"from bokeh.resources import INLINE\\n\"+\n", " \"output_notebook(resources=INLINE)\\n\"+\n", " \"\\n\"+\n", " \"
\"}};\n", "\n", " function display_loaded() {\n", " if (window.Bokeh !== undefined) {\n", " var el = document.getElementById(\"3bd33ccb-f982-481a-a275-ddb87e4df923\");\n", " el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n", " } else if (Date.now() < window._bokeh_timeout) {\n", " setTimeout(display_loaded, 100)\n", " }\n", " }\n", "\n", " function run_callbacks() {\n", " window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", " delete window._bokeh_onload_callbacks\n", " console.info(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(js_urls, callback) {\n", " window._bokeh_onload_callbacks.push(callback);\n", " if (window._bokeh_is_loading > 0) {\n", " console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", " if (js_urls == null || js_urls.length === 0) {\n", " run_callbacks();\n", " return null;\n", " }\n", " console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", " window._bokeh_is_loading = js_urls.length;\n", " for (var i = 0; i < js_urls.length; i++) {\n", " var url = js_urls[i];\n", " var s = document.createElement('script');\n", " s.src = url;\n", " s.async = false;\n", " s.onreadystatechange = s.onload = function() {\n", " window._bokeh_is_loading--;\n", " if (window._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: all BokehJS libraries loaded\");\n", " run_callbacks()\n", " }\n", " };\n", " s.onerror = function() {\n", " console.warn(\"failed to load library \" + url);\n", " };\n", " console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", " }\n", " };var element = document.getElementById(\"3bd33ccb-f982-481a-a275-ddb87e4df923\");\n", " if (element == null) {\n", " console.log(\"Bokeh: ERROR: autoload.js configured with elementid '3bd33ccb-f982-481a-a275-ddb87e4df923' but no matching script tag was found. \")\n", " return false;\n", " }\n", "\n", " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.js\"];\n", "\n", " var inline_js = [\n", " function(Bokeh) {\n", " Bokeh.set_log_level(\"info\");\n", " },\n", " \n", " function(Bokeh) {\n", " \n", " },\n", " \n", " function(Bokeh) {\n", " \n", " document.getElementById(\"3bd33ccb-f982-481a-a275-ddb87e4df923\").textContent = \"BokehJS is loading...\";\n", " },\n", " function(Bokeh) {\n", " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n", " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n", " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n", " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n", " }\n", " ];\n", "\n", " function run_inline_js() {\n", " \n", " if ((window.Bokeh !== undefined) || (force === true)) {\n", " for (var i = 0; i < inline_js.length; i++) {\n", " inline_js[i](window.Bokeh);\n", " }if (force === true) {\n", " display_loaded();\n", " }} else if (Date.now() < window._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", " } else if (!window._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", " window._bokeh_failed_load = true;\n", " } else if (force !== true) {\n", " var cell = $(document.getElementById(\"3bd33ccb-f982-481a-a275-ddb87e4df923\")).parents('.cell').data().cell;\n", " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", " }\n", "\n", " }\n", "\n", " if (window._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", " run_inline_js();\n", " } else {\n", " load_libs(js_urls, function() {\n", " console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n", " run_inline_js();\n", " });\n", " }\n", "}(this));" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "from PIL import Image\n", "from requests import get\n", "from bokeh.plotting import figure, show, output_notebook\n", "from bokeh.layouts import layout\n", "from bokeh.palettes import gray\n", "\n", "output_notebook()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## algorithm" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def image_dither(path, black='#000000', white='#ffffff'):\n", " image_rgb = read_image(path)\n", " image_gray = grayscale(image_rgb)\n", " image_bw = floyd_steinberg(image_gray)\n", "\n", " show(layout([[\n", " plot(image_gray, palette=gray(256)),\n", " plot(image_bw, palette=[black, white]) \n", " ]]))" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def floyd_steinberg(image):\n", " image = image.copy()\n", " distribution = np.array([7, 3, 5, 1], dtype=float) / 16\n", " u = np.array([0, 1, 1, 1])\n", " v = np.array([1, -1, 0, 1])\n", " \n", " for y in range(image.shape[0] - 1):\n", " for x in range(image.shape[1] - 1):\n", " value = np.round(image[y, x])\n", " error = image[y, x] - value\n", " image[y, x] = value\n", " image[y + u, x + v] += error * distribution\n", " \n", " image[:, -1] = 1\n", " image[-1, :] = 1\n", "\n", " return image" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def grayscale(image):\n", " height, width, _ = image.shape\n", " \n", " image = np.array(image, dtype=np.float32) / 255\n", " image = image[:, :, 0] * .21 + image[:, :, 1] * .72 + image[:, :, 2] * .07\n", " \n", " return image.reshape(height, width)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def read_image(path, size=400):\n", " if path.startswith('https://'):\n", " image = Image.open(get(path, stream=True).raw)\n", " else:\n", " image = Image.open(path)\n", " \n", " width, height = image.size\n", " width, height = size, int(size * height / width)\n", " image = image.resize((width, height), Image.ANTIALIAS)\n", " \n", " data = image.getdata()\n", " assert data.bands in [3, 4], 'RGB or RGBA image is required'\n", " \n", " raw = np.array(data, dtype=np.uint8)\n", " return raw.reshape(height, width, data.bands)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def plot(image, palette):\n", " y, x = image.shape\n", "\n", " plot = figure(x_range=(0, x), y_range=(0, y), plot_width=x, plot_height=y)\n", " plot.axis.visible = False\n", " plot.toolbar_location = None\n", " plot.min_border = 0\n", " plot.image([np.flipud(image)], x=0, y=0, dw=x, dh=y, palette=palette)\n", " \n", " return plot" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## run" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "URL = lambda name: 'https://raw.githubusercontent.com/coells/100days/master/resource/day 96 - %s.jpg' % (name,)\n", "# URL = lambda name: './resource/day 96 - %s.jpg' % (name,)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "
\n", "
\n", "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "image_dither(URL('valinka'))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "
\n", "
\n", "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "image_dither(URL('eagle'), white='#ffebcd')" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "
\n", "
\n", "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "image_dither(URL('winter'), white='#f0f0ff')" ] }, { "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": "3.6.1" } }, "nbformat": 4, "nbformat_minor": 2 }