{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"68b1dd08-8021-4295-aef6-d3447c4579b6"},"outputs":[],"source":"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n%matplotlib inline\nfrom PIL import Image, ImageFilter\nimport random\nimport cv2\nimport os, glob\n\n#t = pd.read_csv('../input/train_info.csv'); t.head()\n#s = pd.read_csv('../input/submission_info.csv'); s.head()\ntrain_files = [f for f in glob.glob(\"../input/train_2/*\")]\ni_ = 0\nplt.rcParams['figure.figsize'] = (10.0, 10.0)\nplt.subplots_adjust(wspace=0, hspace=0)\nfor l in train_files[:100]:\n    im = cv2.imread(l)\n    im = cv2.resize(im, (50, 50)) \n    plt.subplot(10, 10, i_+1) #.set_title(l)\n    plt.imshow(cv2.cvtColor(im, cv2.COLOR_BGR2RGB)); plt.axis('off')\n    i_ += 1"},{"cell_type":"markdown","metadata":{"_cell_guid":"91eecdf6-e9c8-4b9e-9786-c0a0c13fd2fe"},"source":"## Artwork from Artwork - Is that Possible?"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"b9528ee8-0ebe-4bf5-821d-039b4db26983"},"outputs":[],"source":"im1 = Image.open('../input/train_2/23504.jpg')\nim2 = Image.open('../input/train_2/22873.jpg')\nw1, h1 = im1.size; w2, h2 = im2.size\np2 = im2.load() #get pixels\nfor x in range(0, w1,2):\n    if x < w2:\n        for y in range(0, h1,2):\n            if y < h2:\n                 im1.putpixel((x, y), p2[x,y])\nplt.imshow(im1); plt.axis('off')"},{"cell_type":"markdown","metadata":{"_cell_guid":"826b3b1d-1698-4d5a-b57e-74b22184a637"},"source":"## Lets test some basic filters\n\n    BLUR\n    CONTOUR\n    DETAIL\n    EDGE_ENHANCE\n    EDGE_ENHANCE_MORE\n    EMBOSS\n    FIND_EDGES\n    SMOOTH\n    SMOOTH_MORE\n    SHARPEN"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"58384bd7-cb56-4957-80b4-3fb37f914276"},"outputs":[],"source":"iFilters = [ImageFilter.BLUR, ImageFilter.CONTOUR, ImageFilter.DETAIL, \n            ImageFilter.EDGE_ENHANCE, ImageFilter.EDGE_ENHANCE_MORE, ImageFilter.EMBOSS, \n            ImageFilter.FIND_EDGES, ImageFilter.SMOOTH, ImageFilter.SMOOTH_MORE, \n            ImageFilter.SHARPEN]\nplt.rcParams['figure.figsize'] = (6.0, 20.0)\nplt.subplots_adjust(wspace=0, hspace=0)\nfor i in range(10):\n    im3 = im2\n    im3 = im3.filter(iFilters[i])\n    #im = cv2.resize(im, (300, 300)) \n    plt.subplot(5, 2, i+1) #.set_title(l)\n    plt.imshow(im3); plt.axis('off')"},{"cell_type":"markdown","metadata":{"_cell_guid":"ede6fbfe-53be-4b3f-ac39-b628218849ee"},"source":"## Lets add a third image"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"0b00f310-c927-494b-90c0-918ef1283d77"},"outputs":[],"source":"plt.rcParams['figure.figsize'] = (10.0, 10.0)\nim2 = Image.open(train_files[61])\nim2 = im2.resize((w1,h1), Image.ANTIALIAS)\nw2, h2 = im2.size\np1 = im1.load(); p2 = im2.load()\nfor x in range(0, w1,1):\n    if x < w2:\n        for y in range(0, h1,1):\n            if y < h2:\n                 im1.putpixel((x, y), (p1[x,y][0], p1[x,y][1], p2[x,y][2]))\nplt.imshow(im1); plt.axis('off')"},{"cell_type":"markdown","metadata":{"_cell_guid":"4752997d-c7fb-43e7-8fea-5171c8837884"},"source":"## Features, Features, Features"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"3d32b110-ecae-4bdf-b0f7-6575e59c1929"},"outputs":[],"source":"from PIL import ImageStat\nstats = ImageStat.Stat(im1, mask=None)\nprint(stats.extrema)\nprint(stats.count)\nprint(stats.sum)\nprint(stats.sum2)\nprint(stats.mean)\nprint(stats.median)\nprint(stats.rms)\nprint(stats.var)\nprint(stats.stddev)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"9706144a-0bc7-4d22-96dc-301c3885bb1a"},"outputs":[],"source":""}],"metadata":{"_change_revision":0,"_is_fork":false,"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":"3.5.2"}},"nbformat":4,"nbformat_minor":0}