1 00:00:00,480 --> 00:00:02,370 This might seem a bit of an odd question, 2 00:00:02,400 --> 00:00:07,260 but have you ever been to an art museum and looked at the exhibition and thought 3 00:00:07,260 --> 00:00:08,093 to yourself, 4 00:00:08,550 --> 00:00:13,550 I think I could probably do this and don't really understand why it's considered 5 00:00:14,160 --> 00:00:16,880 art. Well, this is a piece of art 6 00:00:16,940 --> 00:00:21,320 by Goldschmied and Chiari called 'Where should we go dancing tonight?'. 7 00:00:22,130 --> 00:00:24,950 And it's meant to be a piece of concept art, 8 00:00:25,280 --> 00:00:30,110 but when the museum cleaners came here at the end of the day and looked at this 9 00:00:30,110 --> 00:00:35,110 mess of cigarette butts and shoes and random bottles, 10 00:00:35,600 --> 00:00:39,140 they thought it was rubbish and they promptly cleaned everything up. 11 00:00:39,590 --> 00:00:43,640 So this is what the exhibition looked like after the cleaners were done the next 12 00:00:43,640 --> 00:00:46,190 day. So to the museum's horror, 13 00:00:46,550 --> 00:00:51,550 their star exhibition gets cleared up and mistaken for rubbish. 14 00:00:52,880 --> 00:00:56,480 So I was talking to a friend and I said, well, you know, 15 00:00:56,540 --> 00:00:59,510 a lot of these modern art pieces, I could probably do it, right? 16 00:00:59,540 --> 00:01:03,680 We could probably get together, put some bottles on the floor, make a mess, 17 00:01:03,710 --> 00:01:07,070 call it art. And he told me, actually, no, you can't. 18 00:01:07,220 --> 00:01:10,820 And you should read this book called the $12 million stuffed shark. 19 00:01:11,360 --> 00:01:14,150 And it talks all about the economics of contemporary art. 20 00:01:14,210 --> 00:01:15,650 And it's a fascinating read. 21 00:01:15,680 --> 00:01:20,680 I've learned so much more about how contemporary art is priced and why they're 22 00:01:20,720 --> 00:01:25,670 priced the way they are. But it also led me to discover some pretty big, 23 00:01:25,700 --> 00:01:28,190 shocking discoveries. Like for example, 24 00:01:28,190 --> 00:01:33,190 the art piece that's referred to on the cover of the page is this shark. 25 00:01:33,920 --> 00:01:37,040 It's a shark that was fished off of the coast of Australia 26 00:01:37,370 --> 00:01:42,200 and then it was preserved in formaldehyde. But it was preserved really badly 27 00:01:42,200 --> 00:01:44,060 like they didn't use enough chemicals 28 00:01:44,090 --> 00:01:48,500 and the shark started going a bit green and a bit of gray in other places 29 00:01:48,500 --> 00:01:50,060 and it also started molding. 30 00:01:50,660 --> 00:01:55,660 But this moldy green shark was bought for $12 million. 31 00:01:56,510 --> 00:02:00,470 And this is not even the craziest piece. So for example, 32 00:02:00,470 --> 00:02:04,790 this diamond encrusted skull was reportedly sold for $50 million. 33 00:02:05,150 --> 00:02:07,130 And these butterfly wings 34 00:02:07,130 --> 00:02:12,130 which have been dissected and stuck to a canvas was sold for 8.5 million. 35 00:02:13,280 --> 00:02:15,920 So who exactly is this crazy man 36 00:02:15,950 --> 00:02:20,090 who's creating all of these pieces of art that's fetching these insane 37 00:02:20,090 --> 00:02:23,180 valuations? Well, it's a guy called Damien Hirst. 38 00:02:23,750 --> 00:02:28,460 And I think out of all his paintings, the craziest ones are the spot paintings, 39 00:02:28,790 --> 00:02:33,790 because it's literally spots of color that are organized randomly on a page. And 40 00:02:37,130 --> 00:02:38,060 check this out. 41 00:02:38,120 --> 00:02:43,120 This particular piece was sold for a whopping 1.275 42 00:02:43,700 --> 00:02:45,920 million pounds. 43 00:02:46,580 --> 00:02:48,950 So maybe like $1.5 million. 44 00:02:49,580 --> 00:02:53,120 It's insane for a painting of dots. 45 00:02:53,720 --> 00:02:57,770 But what I thought was even crazier is if you look at this painting, 46 00:02:57,800 --> 00:02:59,920 at least it's got quite few dots, right? 47 00:03:00,340 --> 00:03:04,150 You're getting your money's worth of dots. But look at this one! 48 00:03:04,550 --> 00:03:07,740 This is the same artist, Damien Hirst, and this painting, 49 00:03:07,770 --> 00:03:12,770 I counted only has 25 spots and this sold for half a million pounds. 50 00:03:15,390 --> 00:03:19,980 It's not even about the number of spots. So I personally still, 51 00:03:19,980 --> 00:03:22,560 as you can see, can't really work out contemporary art, 52 00:03:23,070 --> 00:03:28,070 but what I can work out is how to get Python code to crack Damien Hirst's color 53 00:03:29,520 --> 00:03:30,353 palette, 54 00:03:30,360 --> 00:03:35,360 and use those colors to generate a random canvas of spot paintings that look 55 00:03:39,540 --> 00:03:40,373 equally, 56 00:03:40,470 --> 00:03:44,670 if not more appealing than some of the original Damien Hirst. 57 00:03:45,180 --> 00:03:48,480 So this is what we're going to be making as our project. 58 00:03:49,080 --> 00:03:54,080 And we're going to be using that package, colorgram, to get hold of the color 59 00:03:54,810 --> 00:03:55,643 palette 60 00:03:55,800 --> 00:04:00,780 and then we're going to use those colors to create our own spot painting 61 00:04:01,020 --> 00:04:03,600 that's going to look like this. Firstly, 62 00:04:03,630 --> 00:04:08,630 we're going to be using a package called colorgram and colorgram is a library 63 00:04:10,560 --> 00:04:14,700 of code written in Python that lets you extract colors from images. 64 00:04:15,150 --> 00:04:18,149 So for example, if you take a look at this picture, 65 00:04:18,360 --> 00:04:23,360 once it was run through colorgram and 10 of the most common colors extracted, 66 00:04:24,690 --> 00:04:29,160 you end up with a palette that pretty much looks the same as the colors in the 67 00:04:29,160 --> 00:04:29,993 image. 68 00:04:30,360 --> 00:04:35,340 This is the example of how you would use this colorgram package. 69 00:04:35,760 --> 00:04:39,480 And in this case, they're extracting six colors from an image, 70 00:04:39,750 --> 00:04:44,670 so it basically takes two inputs, an image, and the number of colors. 71 00:04:45,510 --> 00:04:49,860 If we go into Google image search, and we search for a Hirst spot painting, 72 00:04:50,280 --> 00:04:53,940 you can see that there's a lot of spot paintings that this guy created. 73 00:04:54,480 --> 00:04:59,460 I want you to pick a painting with a color palette that you like, um, 74 00:04:59,790 --> 00:05:04,470 maybe something like this, or maybe a bit brighter like this one. 75 00:05:05,010 --> 00:05:05,850 But essentially, 76 00:05:05,910 --> 00:05:09,810 pick one of these images and then go ahead and download it. 77 00:05:10,260 --> 00:05:11,910 So save image. 78 00:05:12,600 --> 00:05:16,560 And then you're going to save that image as image.jpg, 79 00:05:16,620 --> 00:05:20,820 so jpg. And then go ahead and hit save. 80 00:05:22,620 --> 00:05:26,070 Now go ahead and create a new PyCharm project. 81 00:05:26,130 --> 00:05:30,090 I've called mine hirst-painting, you can call yours whatever you want. 82 00:05:30,870 --> 00:05:33,720 Now we're going to drag our newly downloaded image, 83 00:05:33,990 --> 00:05:38,640 image.jpeg into this project folder, hirst-painting. 84 00:05:39,210 --> 00:05:42,120 And it's going to ask you whether if you want to move the file from, 85 00:05:42,150 --> 00:05:46,020 in my case, the downloads folder to my hirst-painting project. 86 00:05:46,620 --> 00:05:49,470 So then we're going to agree and click refactor. 87 00:05:50,040 --> 00:05:54,600 So now this painting is inside my hirst-painting project, 88 00:05:54,990 --> 00:05:59,180 and I'm ready to go ahead and create a new file called main.py 89 00:05:59,570 --> 00:06:04,160 which is what I'm going to use to extract the colors from this image. 90 00:06:05,720 --> 00:06:06,920 Here's a challenge for you. 91 00:06:07,070 --> 00:06:10,790 See if you can figure out how to use this package, 92 00:06:10,820 --> 00:06:15,820 colorgram, using their project description here and using the example code. 93 00:06:16,880 --> 00:06:21,880 What you're aiming for is to be able to print out a list of all the colors 94 00:06:22,520 --> 00:06:27,520 extracted from the image and each item in the list to be a tuple that you 95 00:06:28,610 --> 00:06:29,443 create. 96 00:06:29,690 --> 00:06:34,690 So remember previously we saw how the turtle module likes to work with color 97 00:06:34,940 --> 00:06:38,900 tuples which are created with a amount of red, 98 00:06:39,200 --> 00:06:44,200 the amount of green and the amount of blue, all contained inside a tuple. 99 00:06:44,900 --> 00:06:47,990 This is the format that you're going to try and get your data into. 100 00:06:48,340 --> 00:06:50,720 Might take a little bit of wrangling and a little bit of thought, 101 00:06:50,990 --> 00:06:54,440 but just before you get started, here's a quick heads up. 102 00:06:54,980 --> 00:06:59,630 I noticed that when I was testing this on repl.it and when I searched for color 103 00:06:59,630 --> 00:07:01,880 gram in the packages, 104 00:07:02,060 --> 00:07:06,560 I couldn't actually find the package to install into the project. 105 00:07:06,980 --> 00:07:10,790 So this is another good reason for using PyCharm. 106 00:07:11,120 --> 00:07:15,320 It just gives you all the professional tools and it has access to all the things 107 00:07:15,320 --> 00:07:18,830 that you need. So pause the video and complete this challenge. 108 00:07:20,870 --> 00:07:24,260 All right. So we know that in order to use external packages, 109 00:07:24,290 --> 00:07:28,010 ones that weren't installed with the Python standard library, 110 00:07:28,340 --> 00:07:33,340 we have to first install the package. To install a package 111 00:07:33,410 --> 00:07:38,000 we go to our preferences and then we select our project 112 00:07:38,450 --> 00:07:40,700 and then we go to our project interpreter. 113 00:07:41,240 --> 00:07:44,720 Now we click the plus button and we search for colorgram. 114 00:07:45,500 --> 00:07:49,250 And there it is. Now let's go ahead and install the package. 115 00:07:49,640 --> 00:07:54,470 And once that's installed successfully, then we can close all of this and click 116 00:07:54,500 --> 00:07:58,400 okay. Now that we've got our package, 117 00:07:58,430 --> 00:08:01,910 we can actually import it. So we'll import colorgram, 118 00:08:02,780 --> 00:08:07,780 and we can use the method that's described here called cologram.extract in 119 00:08:10,160 --> 00:08:15,050 order to get ahold of six colors. Now, if we want more colors, 120 00:08:15,620 --> 00:08:18,830 for example, in this image, that's probably a good 30 colors. 121 00:08:18,920 --> 00:08:23,060 So let's go ahead and extract 30 colors from this image. 122 00:08:23,360 --> 00:08:27,320 But of course our image is not called sweet_pic.jpg. 123 00:08:27,440 --> 00:08:29,870 Ours is actually called image.jpg. 124 00:08:30,320 --> 00:08:35,150 So let's go ahead and rename this image so that it matches with our file. 125 00:08:35,630 --> 00:08:40,520 And remember that your image has to be at the same level as your main.py for 126 00:08:40,520 --> 00:08:42,380 this kind of code to work. 127 00:08:42,590 --> 00:08:46,820 So make sure that you've got it inside the hirst-painting project folder, on the 128 00:08:46,820 --> 00:08:48,980 same indentation level as main. 129 00:08:49,400 --> 00:08:54,260 Now let's go ahead and print out our colors that are generated. 130 00:08:54,710 --> 00:08:58,620 And remember that when you hit run, this process might take a little while. 131 00:08:59,100 --> 00:09:02,370 And the author of the library says that for a 132 00:09:02,370 --> 00:09:07,170 512 by 512 image, it takes about 0.6 of a second. 133 00:09:07,770 --> 00:09:10,980 Obviously, if the image is larger, it'll probably take a bit longer. 134 00:09:11,580 --> 00:09:15,720 Let's go ahead and hit run and see what we get. 135 00:09:17,070 --> 00:09:19,350 Once the process is finished, 136 00:09:19,380 --> 00:09:24,380 you can see it's created some colors and these colors are in a list and it's got 137 00:09:26,730 --> 00:09:31,730 some different formats for the color. To understand that we have to go back to 138 00:09:32,280 --> 00:09:33,720 our documentation. 139 00:09:34,260 --> 00:09:38,610 You can see that the color that's extracted can either be a RGB color 140 00:09:38,640 --> 00:09:42,120 which is what we're interested in, or an HSL color 141 00:09:42,330 --> 00:09:44,130 which is not quite what we want. 142 00:09:44,610 --> 00:09:49,610 So let's go ahead and write a for loop that taps into each of those colors. 143 00:09:53,750 --> 00:09:56,210 So for color in colors, 144 00:09:56,810 --> 00:10:01,810 let's go ahead and create a new list called rgb_colors, 145 00:10:04,700 --> 00:10:09,470 and we'll just leave it as an empty list. And then for each of these colors, 146 00:10:09,530 --> 00:10:14,530 we're going to add to our rgb_colors by appending. 147 00:10:15,440 --> 00:10:19,550 And the thing we're going to pend is each of these individual color objects, 148 00:10:19,970 --> 00:10:22,400 and then we're going to get the RGB value. 149 00:10:23,240 --> 00:10:25,820 And once this process is done, 150 00:10:26,120 --> 00:10:29,330 then let's go ahead and print our RGB colors. 151 00:10:30,500 --> 00:10:35,480 So now you can see we've got a whole bunch of RGB colors with r equals what, g 152 00:10:35,480 --> 00:10:37,130 equals what and b equals what, 153 00:10:37,430 --> 00:10:41,870 but this is not quite the format that we need it in order to use it inside the 154 00:10:41,870 --> 00:10:45,380 turtle. We actually have to go one step further. 155 00:10:45,830 --> 00:10:47,900 We have to create a r 156 00:10:48,110 --> 00:10:53,110 which is from the color.rgb.r 157 00:10:55,520 --> 00:10:59,180 and then we repeat this process for green 158 00:11:00,890 --> 00:11:02,090 and blue. 159 00:11:04,700 --> 00:11:09,700 And then we create our tuple by creating our new_color 160 00:11:10,850 --> 00:11:14,780 which is going to be equal to a tuple with a parentheses 161 00:11:14,810 --> 00:11:19,490 and then r, g and b. Finally, 162 00:11:19,490 --> 00:11:24,490 we're going to add to our rgb_colors by appending this new color. 163 00:11:25,910 --> 00:11:29,150 Now let's print our rgb_colors. 164 00:11:34,550 --> 00:11:35,600 And you can see 165 00:11:35,600 --> 00:11:40,600 we finally got it in the format that we need, a tuple with the r value, g value 166 00:11:41,600 --> 00:11:45,530 and b value that we can use in our project. 167 00:11:46,190 --> 00:11:50,990 Now we've managed to get the first part of the problem solved so we can go ahead 168 00:11:50,990 --> 00:11:55,990 and copy this entire list and paste it into our main.py. 169 00:11:58,270 --> 00:12:01,540 I recommend actually testing out these colors 170 00:12:01,840 --> 00:12:04,780 using the w3schools RGB tool. 171 00:12:05,050 --> 00:12:09,760 Go ahead and paste your color to replace this current tuple here. 172 00:12:10,180 --> 00:12:14,230 Make sure that you still got that word rgb there, and then hit enter 173 00:12:14,680 --> 00:12:18,190 and it will insert each of these values into the r, g and b. 174 00:12:18,640 --> 00:12:22,030 So you can see the first color we got is actually a shade of white, 175 00:12:22,030 --> 00:12:24,100 so probably one of the backgrounds. 176 00:12:24,730 --> 00:12:28,630 So we can go ahead and delete that one because we're not going to be painting 177 00:12:28,630 --> 00:12:31,090 the background in our own. It's just going to be white. 178 00:12:31,510 --> 00:12:36,310 Now let's check the next one. As you can see, the closer the numbers are to 179 00:12:36,340 --> 00:12:40,450 255, the more likely it is that it's a shade of white. 180 00:12:40,840 --> 00:12:45,280 So this one is probably one of the other background colors in this image 181 00:12:45,490 --> 00:12:48,730 so we can delete that one as well. And finally, 182 00:12:48,730 --> 00:12:52,570 this last one is probably going to be also quite white-ish, 183 00:12:53,020 --> 00:12:58,020 and we can probably delete that one too. This one because of the blue that's 184 00:12:58,810 --> 00:13:03,580 109 I'm going to be pretty sure that this is actually a real color. 185 00:13:04,270 --> 00:13:06,370 And there we go, we get this kind of sand color, 186 00:13:06,910 --> 00:13:10,690 which looks very similar to some of these colors that we see on here. 187 00:13:11,080 --> 00:13:13,060 So we can presume that the rest of these, 188 00:13:13,120 --> 00:13:17,770 because they're sampled by the frequency of occurrence, are probably going to be 189 00:13:17,770 --> 00:13:20,290 real colors that we can put into our painting. 190 00:13:20,770 --> 00:13:24,340 Let's save this list as our color_list, 191 00:13:27,070 --> 00:13:32,070 and we can comment out the rest of this code because we don't need to run this 192 00:13:32,110 --> 00:13:33,970 computation every single time. 193 00:13:34,240 --> 00:13:39,240 We just want to extract the colors and then you can delete or comment out the 194 00:13:39,490 --> 00:13:43,030 colorgram related code. In the next lesson, 195 00:13:43,060 --> 00:13:47,230 we're going to be using this color list to create our Hirst painting. 196 00:13:47,650 --> 00:13:49,210 So for all of that and more, I'll see you there.