Added solution for ex1 and 2
This commit is contained in:
Jakob Krause
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assignments/01_assignment_sample_solution.ipynb
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422
assignments/01_assignment_sample_solution.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Image Processing SS 16 - Assignment - 01\n",
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"\n",
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"### Deadline is 27.4.2016 at 16:00\n",
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"\n",
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"Please solve the assignments together with a partner.\n",
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"I will run every notebook. Make sure the code runs through, when clicked on `Kernel` -> `Restart & Run All`.\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Introduction to Python / Numpy\n",
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"\n",
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"* [Learn Python in 15 minutes](https://learnxinyminutes.com/docs/python/)\n",
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"* [Numpy for Matlab Users](https://docs.scipy.org/doc/numpy-dev/user/numpy-for-matlab-users.html#general-purpose-equivalents)\n",
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"* [Numpy Quickstart](https://docs.scipy.org/doc/numpy-dev/user/quickstart.html)\n",
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"\n",
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"## Libraries\n",
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"\n",
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"We will use the following libraries:\n",
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"\n",
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"* matplotlib\n",
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"* numpy\n",
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"* scipy\n",
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"* skimage\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exercise 0 - Setup Development Enviroment - [1 Point]\n",
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"\n",
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"Find a partner, follow the steps in the [README](https://github.com/) and paste a link to your repository, names and matriculation numbers into the KVV assignment box.\n",
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"You do not need to upload any files to the KVV. I will clone your repository. "
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"# display the plots inside the notebook\n",
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"%matplotlib inline"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import pylab\n",
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"import copy\n",
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"pylab.rcParams['figure.figsize'] = (12, 12) # This makes the plot bigger"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The [skimage](http://scikit-image.org/) library comes with multiple useful test images. Let's start with an image of an astronaut. "
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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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"from skimage.data import astronaut"
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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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"source": [
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"img = astronaut() # Get the image\n",
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"print(img.shape) # the dimension of the image\n",
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"print(img.dtype) # the image type"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We have a `(512, 512, 3)` array of unsigned bytes. At `img[x, y]` there are three values for R,G and B."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We will always work with floating point arrays between 0 and 1. "
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"img = img / 255."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Lets display the image."
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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": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"plt.imshow(img)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This is [Eileen Collins](https://en.wikipedia.org/wiki/Eileen_Collins). She was the first astronaut \n",
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" to fly the Space Shuttle through a complete 360-degree pitch maneuver. What an inspiring woman."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exercise 1 - Plot - [1 Point]\n",
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"\n",
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"Plot the R, G and B channels separately."
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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": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"img_red = copy.deepcopy(img)\n",
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"img_red[:,:,1] = 0\n",
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"img_red[:,:,2] = 0\n",
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"plt.imshow(img_red)\n",
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"plt.show()\n",
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"\n",
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"img_green = copy.deepcopy(img);\n",
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"img_green[:,:,0] = 0\n",
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"img_green[:,:,2] = 0\n",
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"plt.imshow(img_green)\n",
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"plt.show()\n",
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"\n",
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"img_blue = copy.deepcopy(img);\n",
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"img_blue[:,:,0] = 0\n",
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"img_blue[:,:,1] = 0\n",
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"plt.imshow(img_blue)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exercise 2 - RGB to HSV [6 Points]\n",
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"\n",
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"Implement the `rgb_to_hsv` and `hsv_to_rgb` functions. Don't use any color conversion functions from a library.\n"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def rgb_to_hsv(x):\n",
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" \"\"\"\n",
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" Converts the numpy array `x` from RGB to the HSV. \n",
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" \"\"\"\n",
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" hsv=[]\n",
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" for line in x:\n",
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" newLine=[]\n",
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" for pixel in line:\n",
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" r= pixel[0]/255\n",
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" g= pixel[1]/255\n",
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" b= pixel[2]/255\n",
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" cMax = np.amax([r,g,b])\n",
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" cMin = min([r,g,b])\n",
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" delta = cMax-cMin\n",
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" v = cMax\n",
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" h=0\n",
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" s=0\n",
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" if v > 0:\n",
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" s = delta/cMax\n",
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" if s>0 :\n",
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" if r == cMax:\n",
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" h= ((g-b)/delta)%6\n",
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" elif g==cMax:\n",
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" h= ((b-r)/delta)+2\n",
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" elif b==cMax:\n",
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" h=((r-g)/delta)+4\n",
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" h=h*60\n",
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" if h<0:\n",
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" h=h+360\n",
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" newLine.append([h,s,v])\n",
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" hsv.append(newLine)\n",
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" return hsv\n",
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" "
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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": 9,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def hsv_to_rgb(x):\n",
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" \"\"\"\n",
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" Converts the numpy array `x` from HSV to the RGB. \n",
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" \"\"\"\n",
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" rgb = []\n",
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" for line in x:\n",
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" newLine=[]\n",
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" for pixel in line:\n",
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" h= pixel[0]\n",
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" s= pixel[1]\n",
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" v= pixel[2]\n",
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" c = v*s\n",
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" x=c*(1-abs(((h/60)%2)-1))\n",
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" m= v-c\n",
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" tmpPixel= [0,0,0]\n",
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" if h >= 0 and h <60:\n",
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" tmpPixel=[c,x,0]\n",
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" elif h >= 60 and h <120:\n",
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" tmpPixel=[x,c,0]\n",
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" elif h >= 120 and h <180:\n",
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" tmpPixel=[0,c,x]\n",
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" elif h >= 180 and h <240:\n",
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" tmpPixel=[0,x,c]\n",
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" elif h >= 240 and h <300:\n",
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" tmpPixel=[x,0,c]\n",
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" elif h >= 300 and h <360:\n",
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" tmpPixel=[c,0,x]\n",
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" newLine.append([(tmpPixel[0]+m)*255,(tmpPixel[1]+m)*255,(tmpPixel[2]+m)*255])\n",
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" rgb.append(newLine)\n",
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" return rgb"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Plot the saturation of the astronaut image"
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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": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"img_as_hsv = rgb_to_hsv(img)\n",
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"\n",
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" # your code\\n\",\n",
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"\n",
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"img_saturation=copy.deepcopy(np.array(img_as_hsv))\n",
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"img_saturation[:,:,0]=0\n",
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"img_saturation[:,:,2]=0\n",
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"plt.imshow(img_saturation[:, :, 1], cmap='gray')\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Increase the saturation by a factor of 2, convert it back to RGB and plot the result."
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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": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"img_as_hsv = rgb_to_hsv(img)\n",
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"# your code\\n\",\n",
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"img_saturation = []\n",
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"for line in img_as_hsv:\n",
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" newLine=[]\n",
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" for pixel in line:\n",
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" newPixel=[]\n",
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" newPixel.append(pixel[0]) \n",
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" newSaturation = pixel[1]*2\n",
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" if newSaturation >1:\n",
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" newSaturation=1\n",
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"\n",
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" newPixel.append(newSaturation)\n",
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" newPixel.append(pixel[2])\n",
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" newLine.append(newPixel)\n",
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" img_saturation.append(newLine)\n",
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"\n",
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"img_as_rgb= hsv_to_rgb(img_saturation)\n",
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"plt.imshow(img_as_rgb)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exercise 3 - Callculation [2 Points]\n",
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"\n",
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"In the figure below you can see the [CIE-XYZ](https://de.wikipedia.org/wiki/CIE-Normvalenzsystem) color space.\n",
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"\n",
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"\n",
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"What are the approximate x,y,z values for the following Adobe RGB colors:\n",
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"* `(0, 0.5, 0.5)`\n",
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"* `(0.33, 0.33, 0.33)`\n",
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"\n",
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"A sodium-vapor lamp shines with double the intensity of a mercury-vapor lamp\n",
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". The light from the sodium lamp only contains \n",
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"the spectral line at `589,00nm` and the light from the mercury lamp only the\n",
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"spectral line at `435,83 nm`.\n",
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"\n",
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"What color does a human experience? What are the approximate x,y,z values? \n"
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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": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"T=np.matrix([[2.04159, -0.56501, -0.34473],[-0.96924, 1.87597, 0.04156],[0.01344, -0.11836, 1.01517]])"
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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": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"ARGB1 = np.array([0, 0.5, 0.5])\n",
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"ARGB2 = np.array([0.33, 0.33, 0.33])\n",
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"\n",
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"XYZ1 = (T.I).dot(ARGB1)\n",
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"print(XYZ1)\n",
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"\n",
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"XYZ2 = (T.I).dot(ARGB2)\n",
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"print(XYZ2)"
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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": 14,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# For a sodium-vapor lamp and a mercury-vapor lamp a human does experience a bright red.\n",
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"# The approximate x,y,z values are 0.5, 0.32, 0.18\n",
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"# You can read the values directly from the XYZ-diagram. Connect the two spectral lines with a line.\n",
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"# The resulting color is on this line. \n",
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"# As the two colors mix and the sodium lamp has double intensity, the color that a human experience is nearer to \n",
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"# the sodium lamp.\n",
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"# It is exactly 1/3 of the total line length from the sodium spectral line away. "
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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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"collapsed": true
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},
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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": "3.5.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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Reference in New Issue
Block a user