├── .gitattributes ├── .gitignore ├── README.md ├── kmeans.py ├── notebook ├── .ipynb_checkpoints │ └── kmean_test-checkpoint.ipynb ├── kmean_test.ipynb └── portrait.jpeg ├── pairwise.py ├── single.png └── triple.png /.gitattributes: -------------------------------------------------------------------------------- 1 | *.py linguist-language=python 2 | *.ipynb linguist-language=python 3 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | *.pyc 2 | __pycache__ 3 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | pytorch implementation of basic kmeans algorithm(lloyd method with forgy initialization) with gpu support 2 | 3 | usage: 4 | ```python 5 | from kmeans_pytorch.kmeans import lloyd 6 | import numpy as np 7 | 8 | A = np.concatenate([np.random.randn(1000, 2), p.random.randn(1000, 2)+3, p.random.randn(1000, 2)+6], axis=0) 9 | 10 | #lloyd(X, n_clusters, device=0, tol=1e-4) 11 | clusters_index, centers = lloyd(A, 2, device=0, tol=1e-4) 12 | ``` 13 | 14 | See kmeans_test.ipynb for some test examples 15 | 16 | ![](./single.png) 17 | ![](./triple.png) -------------------------------------------------------------------------------- /kmeans.py: -------------------------------------------------------------------------------- 1 | import torch 2 | import numpy as np 3 | from kmeans_pytorch.pairwise import pairwise_distance 4 | 5 | def forgy(X, n_clusters): 6 | _len = len(X) 7 | indices = np.random.choice(_len, n_clusters) 8 | initial_state = X[indices] 9 | return initial_state 10 | 11 | 12 | def lloyd(X, n_clusters, device=0, tol=1e-4): 13 | X = torch.from_numpy(X).float().cuda(device) 14 | 15 | initial_state = forgy(X, n_clusters) 16 | 17 | 18 | while True: 19 | dis = pairwise_distance(X, initial_state) 20 | 21 | choice_cluster = torch.argmin(dis, dim=1) 22 | 23 | initial_state_pre = initial_state.clone() 24 | 25 | for index in range(n_clusters): 26 | selected = torch.nonzero(choice_cluster==index).squeeze() 27 | 28 | selected = torch.index_select(X, 0, selected) 29 | initial_state[index] = selected.mean(dim=0) 30 | 31 | 32 | center_shift = torch.sum(torch.sqrt(torch.sum((initial_state - initial_state_pre) ** 2, dim=1))) 33 | 34 | if center_shift ** 2 < tol: 35 | break 36 | 37 | return choice_cluster.cpu().numpy(), initial_state.cpu().numpy() -------------------------------------------------------------------------------- /notebook/kmean_test.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 7, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "import numpy as np\n", 10 | "from kmeans_pytorch.kmeans import lloyd\n", 11 | "import matplotlib.pyplot as plt\n", 12 | "%matplotlib inline" 13 | ] 14 | }, 15 | { 16 | "cell_type": "code", 17 | "execution_count": 8, 18 | "metadata": {}, 19 | "outputs": [ 20 | { 21 | "name": "stderr", 22 | "output_type": "stream", 23 | "text": [ 24 | "/home/polaris-nn/anaconda3/envs/NN/lib/python3.6/site-packages/matplotlib/figure.py:459: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n", 25 | " \"matplotlib is currently using a non-GUI backend, \"\n" 26 | ] 27 | }, 28 | { 29 | "data": { 30 | "image/png": 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\n", 31 | "text/plain": [ 32 | "
" 33 | ] 34 | }, 35 | "metadata": {}, 36 | "output_type": "display_data" 37 | } 38 | ], 39 | "source": [ 40 | "X = np.random.randn(1000, 2)\n", 41 | "fig, ax = plt.subplots()\n", 42 | "ax.plot(X[:, 0], X[:, 1], '.')\n", 43 | "fig.show()" 44 | ] 45 | }, 46 | { 47 | "cell_type": "code", 48 | "execution_count": 9, 49 | "metadata": {}, 50 | "outputs": [ 51 | { 52 | "name": "stderr", 53 | "output_type": "stream", 54 | "text": [ 55 | "/home/polaris-nn/anaconda3/envs/NN/lib/python3.6/site-packages/matplotlib/figure.py:459: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n", 56 | " \"matplotlib is currently using a non-GUI backend, \"\n" 57 | ] 58 | }, 59 | { 60 | "data": { 61 | "image/png": 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\n", 62 | "text/plain": [ 63 | "
" 64 | ] 65 | }, 66 | "metadata": {}, 67 | "output_type": "display_data" 68 | } 69 | ], 70 | "source": [ 71 | "choice_cluster, initial_state = lloyd(X, 3)\n", 72 | "\n", 73 | "fig, ax = plt.subplots()\n", 74 | "for i in range(3):\n", 75 | "\tindices = np.where(choice_cluster==i)[0]\n", 76 | "\tselected = X[indices]\n", 77 | "\tax.plot(selected[:, 0], selected[:, 1], '.', label=str(i))\n", 78 | "\n", 79 | "fig.show()" 80 | ] 81 | }, 82 | { 83 | "cell_type": "code", 84 | "execution_count": 10, 85 | "metadata": {}, 86 | "outputs": [ 87 | { 88 | "name": "stderr", 89 | "output_type": "stream", 90 | "text": [ 91 | "/home/polaris-nn/anaconda3/envs/NN/lib/python3.6/site-packages/matplotlib/figure.py:459: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n", 92 | " \"matplotlib is currently using a non-GUI backend, \"\n" 93 | ] 94 | }, 95 | { 96 | "data": { 97 | "image/png": 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\n", 98 | "text/plain": [ 99 | "
" 100 | ] 101 | }, 102 | "metadata": {}, 103 | "output_type": "display_data" 104 | } 105 | ], 106 | "source": [ 107 | "X = [np.random.randn(1000, 2), np.random.randn(1000, 2)+5, np.random.randn(1000, 2)+10]\n", 108 | "X = np.concatenate(X, axis=0)\n", 109 | "fig, ax = plt.subplots()\n", 110 | "ax.plot(X[:, 0], X[:, 1], '.')\n", 111 | "fig.show()" 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": 11, 117 | "metadata": {}, 118 | "outputs": [ 119 | { 120 | "name": "stderr", 121 | "output_type": "stream", 122 | "text": [ 123 | "/home/polaris-nn/anaconda3/envs/NN/lib/python3.6/site-packages/matplotlib/figure.py:459: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n", 124 | " \"matplotlib is currently using a non-GUI backend, \"\n" 125 | ] 126 | }, 127 | { 128 | "data": { 129 | "image/png": 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jOjrdBuoV5RU0tTR5q/2369/24v/dLGII9vLtrbg9AAb1G8Q9c+7J2mAeiie8u7KqaFc5gaMMfJF7PmPMA8ADAFVVVaW3L1SUEqCt7lxh5eCGf76/431nTWsMV02+itHHjaaivMJzdLpj3d/jVpwpx08J5ABYYnkrW7ciZmczsGwgB1sPdvpzorDEYuHGhV4nsMtPvNw7l00J9ITwT5dilILYLSKjAFI/GyLG1ANjfb+PAXIX4FAUJZK2bMVh5dDU0sQdM+6gX6yfN37epHncOv1WmlqaAmP9jt8Wu4XVe514D0GIS5y7z7q7y2vfd1WV0LAjOiYxZg6bSYvtmNBsbF785EX+fcW/861Xv5XTyesvrVGqFGMHsAi4Efhp6ufCiDF/BH7ic/xeAvygCM9WlD5JW+aGKFt0tvHhxubHxI4hbsW9mHe3dMSc0XO4Y8Yd3bK67aqSEmFH9AnHnUDtnkzhnU+sv9seM2mS9Iv1K9nEMDEmfyuLiDyJ4/AdCuzGiexZAPwBGAdsA641xuwXkSrgdmPMralrvwncnbrVj40xmX3WQlRVVZnq6p5VXElRSoFCkoncEgfPbnyWpJ1ERALZv+VWOQ9f+nBGC8hn1j9TktE7nY2bRHfuCecytP9QrzeCS21DLTe/cnO6XDQW3z3ju4F6Qp06P5EaY0xeHuhCo4Cuz3LqCxFjq4Fbfb//BvhNIc9TFKV9FGKimTl8Jos2LSJhOwLLvygUhKtPupqZw2d6imLBxgVdVt65s3GbveQcJ05T+aoRVRxqPcRzG57zit+5vRHc9129uzqgQP1+k1JDM4EVRcmaiBWTGHMnzc3a+9d/fU/cDeRbkuLG027k+1XfB+ChVQ8FzFJhc5BrVvOH1Jai+Qe0H4CiKDiZveVWuacIwk7fbL1/XQyGuMQZN7BnhG6XSVlB43/30e+8nshuOWjvXiEnvOtv+e4Z3+WRyx7xymeUIgX5ALoa9QEoStfhzx3w5wO4ws1v147CwkKQLgkN7Q7iEueRyx5h5vCZPL3uaZ7b+BzlVjkV/SoY0n8Ipx5/apt5Al1Fp/kAFEUpLYpVOTJK+PvzAx685EG+ftrXvSYwYSwsLLHaVBCdibtz6YgZ6qKxF3E0cTTQrN6P2xMYyFokTpCSjvoJowpAUXooxaoc6b+Pje11twrXtRnUb1Dk9YJwwdgL6B/vH2iS0pUYTFY/Rr7+iaPJo/z6kl97IZy2sRERz95vMF7WdLYicQaTV89l6Nqyz9lQBaAoPZS2soFz4Rc+UaWi3RLQbshj1Ygq3tj2RuS9DIa369/m1CGntvnMuMSZMWwGNQ01hX3RPMkm5AeVD8pogRnFMbFjqG2oZXLlZL40+UueQnl6/dOBVpp+J2+UEsgn6qeryz5nQxWAovRQ2lt8LKpUhF+gWVjErTjnnnAuQ/oPYd6keQA8tuaxrPe0jc2w/sPafK5tbJrt7I7kziKb8BckkPPwZt2bvLv9XWxskrZTJ+mu2XfRL9Yva1JdRXkF725/l7fq33Kqq0osr6ifjijvYqIKQFF6KG1lA7dlXogqFeEXaGv3r2XBxgUsrltMeazcaw7vd+7GiPGNqd/gsY8eI2mSxK04N0+7mfGDxvPSJy/RcLghY0VuY7Nm75rOfSl54vos/PH6BhPIb2ixW/h4/8eR79ifZ3HtlGt5et3TXrtNt5BeWwI9rLwryit4aNVDXW4OUgWgKD2YqISvXOaFbKUi3DEPrXqIhJ0IrE7Dwvz8sedz0biLePzjxz0huqFxA0+ufZKWZAsighjxSiq7FOKk7YzcAkG4aepNXrvHny77aZtJbYJkfceuUgAy2m3mcgSHdxFhh3tvqwaqKEoXkcu8kKtscdTqdCc7iVtxEnaCmMQ494Rzqd5dTcJOeH0F/IXkME4S2QVjLuDd7e96CiWMpP7L5lD1M27gOLYd3Nbh9zOo3yCvLMO729/1MnrDxCUe2fksrGDnTZoX2W4zl1nHVSwPrXqo28xBqgAUpZeRj2+grVIRUavT5mQzgnidxO5ffr/nO3Cfc/G4i1m6Y6l3H9vYTB82nZun3cx/rfwv3tsRDK8Mm2ByUX+wPq9xFpazA0EywlL976O2oZY9R/Zkvc81k6+JfEdhBWswGT6UQnwyxWgk015UAShKL6MYjUn8q9PmZHOGKSfsO3CFlhHjdfpwwyZnDp/JHTPuYOmOpQE/giv88zXzuKGeucZffuLlHFt2LE+vfzpwfNzAcfz43B97dY1u+eMtnvknaiey98jegC0/3GTHFdjzJs1j3qR5gTyKQt57V3cB86MKQFF6IcWq1181ooqYxAIraX9oqP85971/X8aK3o3AmTl8JuePPT+ruQVg9LGj2X14d2T5ZwuL8lg5U4dMzRlGuu3gNsqt8gxFUXcw3ZTw+U3PB2z/04ZO49TjT+WZ9c94SuDNujd5b8d7XgtM1+zjRkiFK4F25H13VyMZrQWkKEpWZg6fyd1n3U1c4o4Qtsq59uRrIx2VUYlYFeUV3uebp92cNVkLYEj/IUSVprl56s1894zv8uAlDzJx8MScc16zd02kkjAYqndXU9tQy0f7PwqcG9Z/mFMPKZauh+S35fvNPi12C2/WvcmiTYtyzqXU0R2Aoiht4jaHz2WimDtpLvPXz/fMPIJ4IZHutVeceEVktnBMYnzppC+xbv86Wu1WLLE4bchpfOmkL2UUU1u4cWFg9V5ulTN96HRP6Ger8BmXOBXlFd5K3s/b9W9z87SbefCSB1m0aRHPbXiOpEkSk5hn3iqPlQfMYd0Zv18sVAEoipKTfEwUM4fP5J4593hlFMpj5QGBG7eixY2FxT1n3cPkysnesZjEuPPMOzOeOXP4TB6+9GGvgU3CTpA0ST437HOs2bfGccoak6EE4hLn66d9PRip5CNhEizatIh7z74XcJSM3xTl2undfghJk+xyh21noApAUZSiEd4thE0nftyaQ3efdTfXTrnWyz9ww0qzra7DDWySJsnvPvodd591N2v3r2X+hvn4zf+fH/15Lh53sRfN5JZ1QAj4LPYd2QeQEd7qzsP9M3fS3G6v4VMsVAEoitJpVI2oCvQYBrxSE1efdLXnRK1tqGXnISfXINfqurahloUbg63HbWPT1NLEqONGBfwIcYlzx4w7PEXk73F8TOyYgFN6aP+hgOO3sMQCk1nrH7rPYdsZqAJQFKVDhLNiw1nIV590daCgWrjBvD+xKm7FuWbyNcybNC+rkK3eXU2r3Ro4JggV5RVMrpyctRuXP3Tzjhl3AE4imHvM7Xx2//L7vWJ4UWao3oQqAEVR2k04K3bupLkZWa1zJ81l0aZFgYQxt66+223Mbyb6eP/HXgG6KKJCU5Mk+emyn3LX7LuYN2keBhNQItli7R++9OHAMX9WruvE7s2oAlCUzqRuGWx5ByacB2Nnd/dsik44K1aQyDpDbdW9CZuJVu9dzS1/vCXQaN2PG5r6k6U/CSiBFruFHy/5sZeZG1YiUaab8LHuzMrtDjqcByAiU0Sk1vfngIh8LzTmAhFp8o25t6PPVZSSp24Z/HYevPFj52fdsu6eUdFxBWZMYp4Z5cFLHuQ7p38nkCswc/hMbp1+K00tTZF1b64+6erAfd1z2bh2yrU8ctkjTBs6LXA8STJwb3B2KQ+teojahtqc38dVVuH591Y6vAMwxqwDZgKISAzYDjwXMfQdY8yVHX2eovQYtrwDyRYwSefnlnd63S4gm2klm+DMtsKeO2kuCzYu8HYB+ay+Zw6fyT+c+Q/c8sdbaLVbiVkxLCwSdsLzCbSn8UpvcvLmotgmoC8Am4wxW4t8X0XpWophuplwHsTKHeEfK3d+7wWEew20JTCjxmZTGG58f9h+3xbude79NjRu8PIQ7l9+f6BSZ29I3Co2xVYA1wFPZjl3toisBHYA/8MYE9kZQkRuA24DGDduXJGnpyh54JpuXMF946L2KYGxs51re5EPoJAVdbax2RRGe1fe/uuqd1cHehm7/oC+YtMvlKIpABEpB+YBP4g4vQIYb4w5JCJXAAuAyRHjMMY8ADwAUFVVVdxuEErPpKsdqcU03Yyd3SsEv0shrQy7ou1heIcRNjH5K3X2hsStYlPMHcDlwApjzO7wCWPMAd/nl0TkP0VkqDFmbxGfr/RGOroab4/y6D8ERMCI87P/kPbP3X02RH/uYcqhkCiZfMe21b6yLbLtMArxSfR1iqkArieL+UdERgK7jTFGRGbjRB/tK+Kzld5KR1bjUcoDYOWTgIEZN2Teq24ZvHwnpMoMYCfhlbtgxGnRz82mYPzPtmI4dQcSYMWdZ9vJjpmXuolCatfnM7Y9TlqXbDuMvuTE7ShFUQAiMgD4IvBt37HbAYwxvwK+AtwhIgngCHCdiar7qihhcjlS21rhh5XHyifhg8ch2eyc/+BxuOnF4HUrn0yfB8CkFY97T/dZ2XYndctg8T9BohmwIWnjFadJJgEJ3nf3R/DxQjj1Kqi6qVhvrtMoRMDmGtsRM1Ffi9nvDIqiAIwxh4EhoWO/8n3+BfCLYjxL6WO05UjNZR4KKw9X6LokWzN3FHvWZc4hVu6YgcLPitqdQGpcSvhjgWWldxTg7AiMce5z9AD86T7n+KZUXZoeoASKRUeEeHd20uotaCawUvpkc6RmE8ArnwAERs6Amdc5n2dc75z74In0Ct+KpXcUdcuc1f/W94PPOGEWXPbT6N0ExjHp2KR3J944G8SC0ac799m+whmPBaNmOH9mXO/sFPx8vLBtBdDLMos7KsTV3NMxVAEoPZfwCr//EHj0L4OrfCyIleHZ/C+/H178fkpAx5wh7k4icZRAHWGA07+RFrRW3DHniAUf/Ldjx7diMOtGR9lseceZgzsnKwa7Vjs7DVf4YzvKYOdK55pTr0qv/AFGfi779y1WeGqJoUK8+1AFoJQOuVa34fNh89CWd1LC1o/trPirH4Xa3zs7AmNwzEEpE1BTXbTwBzjij1Vwu53bzj2MjddX5JW70oL5sp861zXVQ81v8UxBx0+A/Z8497ET8NLfwxU/g/HnwNb3nPss/TWc8peZpi53nr08s1jpWlQBKKVBrtVttvPun7pljsC1YkF7u0fK/n9oD2mpbUPDWvhoIWnhb/nOA2uec+6LgWTC+WmSqXGSivAxjpIxKWVzZB+c9/fOnD543Nk1xMrg83/nCH1/hJH/d8gU7IFoonjq+9GrMouV7kMVgFIa5Ar3bOt8WEiOPwu2LUnb4cVyPsfK4bjheFE4AKuf8U3Cd9xl1yrnjxUnoBjcz3YSmj9z7g/Oz4a18ML/C4d2p49jnFDSK37mCH13bnaSAK5fwlv116e/t41jbqoY02t8AEr3ogpA6XzycVzmCveMOh8QkqkVuG0g3i8leFNmmlnfgIqxjn1+V21KIaQEr+sLcP0BJiSQXSJ3Fanxq/4QPBb+HRxBv+UdZ2cAjrN35Ofg/V8E7z35EuenP4fA72iecb0KfqVoqAJQOpd8HZe56uaEz0O049bYqV/dYwb6VTjXPHplykEsBFb7YsEZX3dW7GtfjP4e7i6iI/Qf4ryPV+5yFNYnb8PUa2DVM3g7ig2vwXHDfDkEBqpudBSYrvqVIqMKQOlcCsnkzVU3x3/+nZ9lcdxa8OmW4KFdH0LzAV+CV+gaYztmlZEzggrg+Ikw/DTHbNRvELz3H9l3CLkwSXj5/3NW+Ikj6eeunh+0PCVbYct7BPwUOz6EzW85OQOqAJQiogpA6Vw6qyTyhPNS9XpCwjzeD06dB3/+efrYqVc5pp9sWDFndf5xsNE4+zc79zrlL53wUpN0TEWf/y4cMwhW/Dc0bvZdIDDs5OhkMnDewdqXgscyFIoNe9cHD+2ocX7++edwYAd8+UHndzd34dBuOG5EOtch2y4qyhTXy/IKlMJQBaB0LsUqiRwVAvr5/yco6IdOgTl/4yRSVZ4YLK9Q/Wj2e0++xDHLJI5mnnvv32HfhnRugUk6vx833AnLDGCyC3+PkBkp0rTURpWUVU/D7G855SNe/H5Qgaz4XcqxnAiGo/pNZuG6SL0wr0DJH1UASufT0ZLI2fwIX/z/nfOr/gAHd8O+jU4ht121TtJX1U3Ote/8LCWsI6J8XJIEkDdvAAAgAElEQVTN0eeMnY7Rd1n3StrJ3FH6Hw+HsxTFzaYcVj7hCPvw7sFuxfuOieZUtFGq5MTM66OzpjWvoE+jCkApfbL5EeqWwZL/DNX3SaaTvi77qaMQ3PBQf/SPn4M7cQRnFo40Bn9vrx8gimzCH2DIZNi/KVRHqAx2fpgZPgqOecqbWyoiyqt/ZKJNcb2wY5mSP6oAlNInmx9h5ROhsg8uxjHnLP3PtOPXboXxn4dtSzMF+PYaRzl0Bh2JHho62dnV+LFbnfk6N3fuP+4sGHaKc6j6URwzk6SLzrnlqP0mIXel38s6limFoQpAKX2y+hHCq3a/icfAnpAz9dN6+Mt/hXd/Bp9uC57raIhnNoZPhd2rKdhcdMqVcM7fwcY/ZS9TccIZjlD3O3RrnwyWpNhV6xTAq/lttJ2/l3UsUwqjk5Y9ilJkxs52kqj8wmrG9RDrl/qlDROOS9M2J0M3LPw7k92rKFj4W3FH+LuKr+rmdKKan+ZDwd/d8Rfdk7ruJid/wE5k2v4VBVUASqnjOnHrlmUe3/IOzLkjVaYBgoJWUsfDiqGTVvpFQ6BinBOVVP2oI9Sv/D8wOqJa5t518MgVzrtw3xMEFaVrPpOY2vmVDNQEpJQuXvRPs2PrvuJn6cgeNypIJOUQjVhli8CIaalVeE/BOLkFjaRt/VU3OYLbs/37sFth/q1OOQyTKoPhN/MUKwxX6ZWoAlC6h3wSkLa8k67xY2wnrHHEac5xt1RCVutKqnpnw0ed9AW6iBe/D3/+N/h0a/Yx/nOJ5mD7yv5DMh2/ipJCFYDS+YSFfb71gSacF4yise20UMtqynEdwZL6WOomnxyYZCjbGBg53UkEiwpHtax0+0pXSboRQf4dVCHZwkqvRRWA0rlECft86wONnZ0un2zbjnnDbfziKYZUz1033PH0v+543Z6iEuovkItjKuBoU9tjYuVONFM4E1hSQv7IvlR4rK8UtduABoLNa/zKt5d2HFOyowpA6VyihH0h9YGqbkqbffoP8bVd7JeK8RdHSA2b4mT/jp0Nv/9aiQh/KNjpfPRA7jHJFvjgMQL2L7d3sbvDipX7dgDuVGynPEY25VtI4T6lV1A0BSAiW4CDQBJIGGOqQucF+DfgCuAwcJMxZkWxnq+UKFHCvlDHpHveXyN/zJmpBu5Jp1RD3XJnzO6PYN3LnfqVOpc8QkZ3+Z3aKfOOv3ex//0ePZDqOZDaQZ16lfPeopRvZxXuU0oWMeFqiu29kaMAqowxkbntInIF8F0cBXAW8G/GmLPaumdVVZWprq4uyvyUbqQYduV3fgZv/DjHyj4lDLNFBfVKUmGusTK46cX8eimrD6BXIyI14QV4NrrSBHQV8JhxNM4SERksIqOMMTu7cA5Kd1CMbFN3dZotKxbwbN1WPHsHrx6N28jGNev4/AvJFqc0RjZfSr7Zv5oZ3KcoZiKYAV4VkRoRuS3i/AmAv35ufepYABG5TUSqRaR6z549RZyeUjK0ldzlHg+P8bJib8pdt+fs78Ckizpl6nlhlXXSjVPF3cBx+I6fEzqfRza0ovgo5g7gHGPMDhEZDrwmImuNMW/7zkf968xYyhljHgAeAMcEVMT5KaVAtkiTQGP3VPEyt669O8Zdma74XTq8M2O1bzndv8oGUHAETrGwWzvx5r5aR8OmQH1N+l26DWEUJU+KpgCMMTtSPxtE5DlgNuBXAPXAWN/vY4AdxXq+0kPIFmkSOO4LX0w0w+J/ggt+kB7n+a0ksyyyFXMURKcK4RLAfQWX35870asr7PrqO+iRFEUBiMixgGWMOZj6fAlwX2jYIuA7IvJ7HCdwk9r/+yDZIk38x90dQLIVsGHzYidy5cZFwXGQ6RQe9bnokgm9Dhuqfwuxx53ch2x0RWy/5g/0WIrlAxgBvCsiK4FlwIvGmFdE5HYRuT015iVgM7AReBD4myI9W+lJhCtWhkMXZ33DEWiX3w+TLkgnfPl3C+71I07LvP/xk7r06xQHcRrQ+ykfmMd1qfdS/Rt45PLotpdRO65i0xXPUDqFouwAjDGbgRkRx3/l+2yAvy3G85QeTluRJrW/T3fwmnyx41B1I3ua6pzVpnv92hdDFwvs+rDTp98pnP7X0LDW6fmLgZaDbQyOaG3pZvq6StFNmGuqS/lJ6LzYfs0f6LFoJrBSOgRWkklY+5IT3z7lctjwKtQ85igId+dw+jcyzT3hJjA9ASueFpqRbSv9Al9g0oVOQteuWueduOPtpFM4buOf0kX0sCAWh1k3Ok7iXHkA7UErjvZYVAEoxaOjgiUj1t84Qq31sPPTJB3B5jqFq26Cxk/gvX93HMPZev6WPMbJYN7uJsb7Ctr5Qz8Rp8T1yM853x1g5ExfTSCTyoI2viJ4tvPuKsYUVoivUDR/oEeiDWGU4uAKljd+7PwMx/jng78Dlr+JyalXpX5P+QM2LU4/45S/hFk3wSlX5P8csWD8OZ3XB7hQ7AS88D1Y+4IjyMWCc77nrPQD/4umBPuff+7UO6pb5iiCWd/Ai7L2BL8bdW0FzTJqr1d86A5AKQ7FKiTmriRnXJ/eTQDMvA52fgjbP8Bzfv7535wVr0k6yiLf1b8xcNIXnJ1GyUQM+Wz6xoZjBjm7nK3vZxZ1A0dZbPyTozBn3OCYxvw9EqyYkxB3zKD0O3znZ6lCemqvVxxUASjFodiOQFcRhBPEYq5TOAbrXkqveAs1/fQfEt1la+gUp9VidxIrCxbNW/xPsOlNMhy/rqI97+/T4zYvTjXQMY7wP+/vM80+l/1Um8QogJqAlGKRLbyzo/h3FnYSTr/Becbpf+1LCCsU49TEb46ouz8qI5gtO8eNaOfzcaKbpv9V6KDAKVcGi7qNne2YwNzcCBGc/20l6DweO9vZMcT6Zfb/DezOmp2S0Cr8FVQBKMVk7OxgQ/J8yFYXyCXc1HzGDc4zRs5ow4afxz/rZAsc2hO6h8D+TfnP/fC+/Mf6GToFbn4Jhp9CYK5VN8N1jwffX90yR1nZtqMEPv93TlQPkLEjGDvbWd1PPD/dGwB87zDCh6L0aVQBKN1HPo7jqJ2FKxSNGynjQySiSFoEIrDhtWBZCSvmi8TJg/ZWHN2/OR31467oY/0Ak/kO3NU7KbPOrg/T5a7tZNCJ676XzW85P8OF9CZegFcfSR3ACqoAlO4kV0SKuzuA4M7CbRbv9rsNKAFJOUNz0L8yVS8opUQGjepgH4ECKnHarU7ophv1A87Pmsfg0SudiCBXeId3QF5EVCzT1+J/n4mjsPLJ9DnXRBSPMBEpfRZ1AivdR1uO47bi1fsPCca5T/8rWPOscyzWL5UglooWysZn/lLjBg50tC5hgYoj4LS2HRMPOAlw1Y8EE97CSVZui8ywHX/CeY5fIJlSZB/8dzr5CzRhS8lAFYDSfbQlkNoKKz2yj0Cp5/2b0s3Q/fd54XsUrTOY14O4QCTlsA1HKXlN7bOQOJo9lDZb0tXY2Y6TvPpRAiaifJvBKH0OVQBK95JNILW1O5hwnhMq6Qrk7TWwazXc9EL6Xm6mrJclixN5c/Kl6dyBKMqPg5ZDmccHjoSm+tR1kn/WcVYhL3DsMN9OJFzfxzg+gtd+6PT0dXc3uSKs3JyAfMJxtYRzn0cVgFKatLU78Fa6j6SPRSWfVd3kmEtWPgFI2hzy2g+dbNowYsGgE6LzAD7dRqAZS0dLTphkWviLlS5657/v2hcJKIVkc+4Eu3zNPFrCWUEVQJ+gZmsjSzbvY87EIcwaX9nd08mftswVM26ADx5P9wXIttr1O45dmg9kjhML/vL/OJ9f+Lv08cHj4NN6svoT3F3Fvg2wx684UnH6JpnaBURU8HTHTbzAcdDu/sip6Ok5o0PjxcrPcZuPmadYmdtKj0YVQC+nZmsjX3toCS0Jm/K4xeO3zukZSiCXeWLsbCdhKry6D18XlQW74jHfjcSpJ3TO36XHn3IlHNzpOJOP7IM//WP2eYo41+7+KKg4MI5iOOEMOHrAmdPOD1Ohoz7BLhZUTnA++3csK/472NVMYo6fo1hCWks4K6gC6PUs2byPloSNbaA1YbNk8752KYAu3UXka54Ir3Td6xLNYFmOwNy1Ml1dNNkCHzwWjN8XgZO+6Ajo3R858fPuc93a+vF+kDgSPddwLL6f44Y5gtX9LmLB0JNh38b0rkAsqPkt1D6Z2fvYdeYiTjln169RDLKZitQv0KdQBdDLmTNxCOVxi9aETVncYs7EIQXfo8t3Ee01T2x5J10QzbYdB7D4TC9WHAaOCl5jbMfs4iaEGRtPWfjr7LxyV0ThOAmunv2RQlbcMVP5v4tJ+vwLqbIOdpJAYpb7PUfOdBLTbNtRQJ3R8D2bAlW/QJ9BFUA30tmravf+9145lcbDLe1+TrF2EXmTzTyRa3U64Txn5W/7CsR51hZxHMczboD1f0ybVyQlZMM2fn+dnUgsZ0Xuj7O/6YVU8pVxnuMej5VH7CBSNn7LAiPBjmeQynS2nfP+sg6difoF+hyqALqJYq2qsymRYq7ai7GLKIgo80T1o6mVui8cEoJjxs52zD4v/X2mUI+VpYXyzS+lfQcjZzjC1mtCk2JMVdAsFBbg07+SLlntzjnK+erW58nISRDne1z2U8dM9cF/pzuezbw+JYhTZqIj7aw5VCjqF+hzqALoJHKt7ouxqm5LyBdz1T5rfCWP3zqnayOJ/MK0bllKqKds98lmZ6Vd+2SmucJ1pC7+J6fomVsu4vS/DmbE+gX1iNMyTTzbljh/RNI7Cj/7N+VvLjmyj2AUUGj38PuvpaOZki3OuO4QxJop3OfosAIQkbHAY8BInP/bHjDG/FtozAXAQuCT1KFnjTH3dfTZpUo+q+9irKrbEvLFXrXPGl/ZfdFDW94JCmGx8Oz0UeYKt+7N1vfTQjSXDX3UDNhRm+7I5bVVtFJmpVBY5sCR6fG5zCUTzks5kn3OadehW/2oUxPI/91m3JD2H3S1INZM4T5FMXYACeDvjTErRGQgUCMirxljPgqNe8cYc2URnlfy5LP6Lsaqui0hn8/9e0x+QJQAHXFa2xmvBSdEuU3UcYSwxJwdh7+BytEDTjXOU69ynr/xjfxW6W3N5eOFwbGjPhdUZIrSiXRYARhjdgI7U58PisjHwAlAWAH0GfJdfXd0Ve0X8pUDylmyeZ93PNf9w7uUQh3FXao8sgnQXAK+oIQo3w7DtqHq61Axtm3lUYi5JNtcTr0KNr2R/v30b7R9H0UpIkX1AYjIBOB0YGnE6bNFZCWwA/gfxpg1xXx2KdGVNnP33oU6fP27lJZWm3sXrsY2Jq/ruyW5LJuDtaOrZNfxGXAC204YZq64+2I8333GxwsdZVDMWH9FyUHR+gGIyHHAfOB7xphwrv0KYLwxZgbwH8CCNu5zm4hUi0j1nj17sg0reWaNr+RvLzypw4KxZmsjv3xzIzVbG7OOiTI55cLdpcQELEuwjcn7+vY8r2RxdxeTLsSr6S9W10Xe1C1znnXBDxyzUlvd0RSlyBRlByAiZTjC/3FjzLPh836FYIx5SUT+U0SGGmP2Rox9AHgAoKqqqki1fEuXtkwp+a60s5mc2rp32Hx03wtr8nYYd3lYaGcT5TTuisibcMN7JO130CQspQsoRhSQAA8DHxtj/jXLmJHAbmOMEZHZODuPHrxsLA5PLN3GvQtXk7QN/crSAr5mayPPrqhn9famvEI5o0xO+SgPv49gysiBeZusuiUstLMpNASyGCUTAolXrg/CaBKW0mUUYwdwDvB1YJWI1KaO3Q2MAzDG/Ar4CnCHiCSAI8B1xphev7pviyeWbuN/LljlRBfi2OFdU8r1DzqC28US8l7ZuyzZvI/mVhuTuvf8FfVtXlOoQ7pbw0I7i3xt+sUqmeBPvArvADQJS+kCihEF9C45GqIaY34B/KKjz+ot1GxtTDld08csS5gzcQhLNu+jNRFMPDrnpKF87+KTs67sAb76wPskkoZ4THjqtrOpHFDud2nyh+o6bNu0K+JHCVGskgnhXYd7b03CUroIzQTuBpZs3kfSJ/0tgfuumuYJ47K45e0AymPiCX/3Wi96J2UWWln3KYmkc79E0vDPL3/M+VOGY4mTvyRAMmkwQHOrzf9asAoDAQXSq8w5nU2uXsaFCPHwrkMFv9KFqALoBuZMHEK/MouWVhvLEu67ahpTRg7kl29uZM7EITz5rTk8u6IeA0wbXRGI7z94pNXbOdgGKgeUs/vA0cD9l29t5OrTx3iO2ljMwrZtErYT6JjSFbQmbJ5dUc/8FfUZOwrXOaw7hQjaKqWs1TSVHoQqgE4km60+7ESFdBx/3BKurRrLNWeMYd2ugwEn8b1XTuXBdz/x7iNA4+EWvnrmOFbWr0o/2DjH/c/49VubePWj3YFry+KW4yPwOZrnr6jn2RX1nv8AnJ3Cj+Y6ZiNVCimi/AVaTVPpYagC6CSiMm3X7GjCAF8+Y0zAifrLNzemzTpJwxNLt/F0TT3JpO2t1ltabZ5avi1oOkr5DQBmT6hk+dZGMNCvLO0w3v7pEX791ib+tHZ3YH4XnzaC28+fBMCzK+q9kE7BUQh+D31Lwubu59IKxhJ6VnexrkKraSo9DFUAnUTYVv+/Uit5gGeq63jytrMzCre5q24DGY5gyxL6xYN5e7PGDQbSu4ey1O5h6ugK5q+o5w/VdZ5vIIyQziIO70bmr6jnaGuWHrgQ8D+oAvCh1TSVHoYqgDwptPaNP1lKREj4Vu6tSZMhPK85Ywx7DzazeP0eEkmf8DUQS/kJVu9oYtmWRv8pfv76ek9Yu8L+R4tW05JF8Lu8+tFunli6jRvOGpcR0nnvlVP5zZ8/YVPDocg25pD2PyghtJqm0oNQBZAH7al9E860/dHza7zInrJY2nTz05c+5oF3NmMbJ+Jn5tjBVG9t9By9rvC/4axxPLF0mxfZA7B8S7A8hA28umZXTuHv8tRyRwG43zFqrhZOZYRkaENg4fgZFEXpuagCyIP2NlcJZ9r++q1NbN5ziInDjgOcZLBfvb3ZG9+SNIEVPoBtG9bsaOLu51bxTE19IHcgij2HgkL5+AFl7D/cGjn2w+1NPLF0G1NGDvQUnBXarRjgujMdJbH3YDOL1zWQtE2nlYDoMSWqFaUXoAogDwqtfZNNiC1ev4eWhM3GPZ+xeF0Dp44alPPZ8ZjwdHUdrak4/kIoiwl/VTU2oGT8GAP/c8Eqrp89zlNwYIhZ4vkrymLCtNEVNB5u4ctnjOHb50/K+G7tEdpR13RLlVFF6cOoAsiDsDnHDZW85owxAG3W4HGzbrd/eiTg2G1JGoYPOgZoyvrc2RMqOWnEQH6/bFvBwh/gwinD2bz3szbH2AYaDjZTHk/lJYhw67kncrA5wYqtjew+2JyROPa3F57kXV+I0Pabme57YU3GNV3efF5R+jiqAPLEFUTXP/C+Z2P/Q3UdAiTsdB39+b4Y+pZWJ/rHtp0SDVbIln5seQyLQOvyAM0Jm2mjKxARZ7leIK9/tJvBx+Z21A4f2I+bzp7AA+9sJmkbHn1/C5dNHcnHuw4G59PqJI75hXK+QtuvKCxxdhhutJN7Ta+rMqooJY4qgAJYsnkfrclgNI/b6ttNonqmpt5brRscG747tn9ZjCN20rt+0codba7sy+MW972wJhD7Xwg2sP+z3I7a51bUc8SX+NXcavPKml0Z4wzwdHUd16TyGCB/85hfURjjmJmMCfoSemWVUUUpYVQBFMCciUMoi4m3AyiLiVNnJ+UUFTLj9/0caU0GfreNE00TJd4tccIsW9q4X7E4HIr5N5A1DyBpB0NY8xXalQPKPQe2AW4990QG9i+LzJLuM4K/GCWlFaUDqAKIwK3H78/afWLpNl5evZNvnnMiB5oTCDCwX5z3N+9j+KBjvKzap5bXeVE0+azbo8Sslaqtunj9HuKWtMsBXEzGHz+AnQeO0ppawb+1riEguPMR2o2HW7zdkgWe8F+yeR/rdh3se+UltG6QUgKoAghRs7UxUI//meo6vnnOiV4kzTsb9vKTL00H8JVHaOLCKcO54axxXPm5USyo3dGhObgr5UTSZuKw49jUcKhD9+soW/cfJiZphbZsSyNffeB9nvJlM7tkiwhyC+C5pqLKAeV87aElnr+kz5WX0LpBSgmgCiBEuB5/a9Lw++q6wJiXV+/kwJFgbP1Ty7exbd9nHRb+fmwDG7tZ+LuEc8sSScOzoSYzbUUEhU1F80MF5/pc5I/WDVJKAFUAIeZMHBKox2+AT0OJVJdPG8XidQ34Qzj3HWrOGm/v0r/M4tKpI1m0ckfOhK6uwh/zX9h1jkPYHwEVjgjK1oVs3a6DAWc5ZHY96/Vo3SClBFAFEGLW+Eqe/NYcfv3WJl77aHdASE0YMoDb/mISN5w1jikjB/LGugav/k79p0ejb+jjaKvNC6t2lozwByciJ18sgcEDyjhp2HFefoJtnKih+Svq+fIZvh4ElvBMTT2JZDofwo39d8NAwSlK98XTRjBj7OC+5QMArRukdDtW7iE9j5qtjfzyzY3UbG3MPTiCWeMrGTawX0D4xy3hZ38106udM2t8JU/ddjbnTR7adj9MHwayVufsLnIpoxMq+wfG7v+slQ+3NzFtdAXxlLfa4OREgFNZ9PuXTOHaqrEkkundwMurd3q7AzsVBhoTp3T1t8+fxN9eeFLfEv6KUgL0uh1AMcoJ1Gxt5Gmf3T/cstFl1vhKvnfxyby/aV+gfk5vQYCDRzLrCDW32vzm3c0MH9jP2/kkkob5K+r5yZeme/6A+b4+A5dPG8XyLfu93++9ciqrdzTlrTwVRSk+vU4BFKOcQDjhS0SYMnIgEIxyccde+blRJWXXLxYGOHA0EXl8457MEhN+YR6VHzBl5MDAu3NNQvNX1Ped6B9FKSGKogBE5DLg34AY8JAx5qeh8/2Ax4BZwD7gq8aYLcV4dphilBOYM3EIMStdFdMY48Wruy0ay+IWGOMlhQmOmWjy8OMySij0BcrjllcbCaLDQbN1QetT0T+KUkJ0WAGISAz4JfBFoB5YLiKLjDEf+YbdAjQaY04SkeuAfwa+2tFnR1GMcgKzxldy31XTuHfhamzjRLlUDijn3oWrPaUQztA1OFmyYeEfc/REr9sd+JkxpoJ7504NVPW8/sElnhJ+8luZq3ut+6Mo3U8xdgCzgY3GmM0AIvJ74CrArwCuAn6U+vwM8AsREVNICEoBFKOcgBvp4yqSJZv3YeeYbtTZAeUxDh5NRpyJxs2W7SnELOHeuVMBJzFOgD0Hmz0F2ZLILCAHWvdHUUqBYiiAEwB/plQ9cFa2McaYhIg0AUOAvUV4fqcRViTxmJWx8vfKG0j0Kr8Q4Q9Q0T/Op0cy7e7dxcwxFaza3kTSON+1akIl1Vsa00rKGNbtOhhoQ2mFPLurtzdRs7UxUgmo4FeU7qMYYaBRgRxhUZjPGGegyG0iUi0i1Xv27Onw5KJod5iobwfg/0JxS7jtvInEwpKvHZSS8AeorW/ysoAlVaBOfF/TNvDA25sCbSjDivDD+ia+9tASnli6rUPhuYqiFJdi7ADqgbG+38cA4XoI7ph6EYkDFcD+qJsZYx4AHgCoqqoqujWkPWGiNVsb+fnr6z37vwWMGzKAbfsPe+WNB/Yv41vnnpgzG7gnYxt4/ePdAQFvgK37Drd5ncExBfl9Khr1oyjdTzF2AMuBySJyooiUA9cBi0JjFgE3pj5/BXijs+z/uYgKE22LJ5Zu49pfvcc7G/Y65ZsFysssLps6EkskUMLgQHP7Vu89KRY+ysxlcL7DScOPY+SgfhnnLcHL/s313juaxKcoSv50eAeQsul/B/gjThjob4wxa0TkPqDaGLMIeBj4nYhsxFn5X9fR57aXQqJParY28j8XrAoIvYnDjuOb55zIj55fQ8J2MlrvvdJxgj5TU9+uOfUkp282DLBl76FAxzNLYN6M0UweMdBrA9nWe9eewIrStRQlD8AY8xLwUujYvb7PR4Fri/GsjlJI9IkT+RM8dmx5jDU7mjxncNI2rNnRROPhlqzNYNrZ0bHH4X59Ac9P8MqaXXz97AkZiWBR7117AitK19LrMoHzId/oE7cDmD8r+KtnjmP1jmAj99XbmxjYL551Jd8XhL+LBViWYBvjFYpzw0BzvXfNDVCUrkW6yRSfF1VVVaa6urpb51CztZFfv7WJ3QeO8tUzx3HDWeOcRCdfc3jXxt1T6wENHVjOvkMtHVZUApw7eSiXTxvFDxet9hRneUx4MqJ5TBTZGsooipIfIlJjjKnKZ2yvrAZabGaMHcy9c6cGKoE+maoE6sb/28ZkOHN7inN378HChL8AJww+JuO4wemVMGXkQGyfMmxNGn7++vq8HLuzxldqZVBF6SL6pAkoX3J1uPrexSd7FS5jMQvbGBJJgwhc5XN+vrmugVX1n7LrQHPGM04adiyb9nxWMo7gmCWYlPkmGxefNoLbz58U2AWBoxgaD7ewZPO+wPcxwLsb9rJ8y3517CpKCaE7gBD+MMRcIaOuQ/n7l0zhK7PGeKteMbDvM6fJ+ZSRA3lnw55I4V8eEy4+dUTJCP9LThvBH759Nk/f/nlmjKmIHFMeE24/fxIA44YcGzgXs4TKAeVs//QI8Vjwn5YBWlrT7zAq3FNDQBWla9EdgI/wiv/eK6fmdEq6js2arY08u6KellYbG/jzRmfFe80ZY2huzYwOEmDm2ME8+E72xLHBXVwW4khrknW7DtJ4uCXl7F4daBcpwDfPOZFnV9TzVHVdoLmNJXDruSd6JZ4lwv5lWcKciUMid1aAhoAqShejCsBHeMXfeLgl75BRdzfw89fX8+eNe7177D3YHLnCN8CyLW2vdFs60D3s2PIYn7UUVofonQ17eWeDU57JEpgyYmCguqkBHnr3E5K2yaz1IcKB5oT3/sIDhHRTnahS0ICGgCpKF6MKwEdUGGJboZr0YyIAAA3zSURBVIuumahyQDmNhx2Tj98vUBa3GDawX9ZCcbkYUB7jaGuyXdceaU1mNHwX8i82ZxsySlsLRAp/cMphCHjvTywJ7BC+/RcTPSd6tnDPuOWE3MZSOwVFUToXVQA+CkkSc80Yza22Vw3UNV3477Fu10EskZylpKOYOPRYTh9Xyeuh5vT5YBs4c/xgarY2egrE4BSbi1nC8QPK2HOoJe/7xSxh7udGsaA2Xebp1JEDWd9wCJOq73PNGWO45owxge/+8uqdXD5tlCf8Ifo912xtTGWPGSLtR4qiFB1VACHyTRJzzUWuYPabLtwwxpqtjdz3whqvCbqxDdG5wpnELPig7tNAElqh1NZ9yrwZowNCG5xV/P7PWgJlm9vaZYwc1I+LTh3hZPiSKn8NXDljtNcrIdz5y/3pF/x+wu95yeZ9JJLO+0wm1QSkKF2BRgG1E9eM4b5AAWKxoKPY71MwxlA1IbdAE2DCkAHMGlfZIeEPTvz98iwRNUnj5i/gFbnL9o+h4UAzTy7dxtPVdZTFLWKpgniVA8oLTtrKFunjvs+Yr7ieoiidi+4A2olrxnh2RT1PLd/mFEELmXkqB5R7K2vbwOAB5Tnv65ZXrtvfdonlfNneeCS/gQamj6lg+KBjEODTwy3sP9zK5j2HvO+QSBquO2ssJwzu7xV3i4rayZbNmyuvQjuEKUrXogqgA8waX+kVjHN7AvtNF42HWwImk6ED+2XUForCAP4h+TiRY5YgQsDxWgg2TuMWQxOWON3PTh05MKDTLEv48hljskbyuGavbEI+V7E37RCmKF2LmoA6SFumizkTh9CvLG0y+fIZY/j9bWcze0KlZ08n9TMm2UtHxCzh9r+YmHUOlsAZ4wZz0ZThzJ5QmdGSMReDB5RhCQF/RkvCZmV9k3fMErjolOE5v3dbyXNq5lGU0kJ3AB2kLdPFrPGV3HvlVC8Sxj13/pThVKeicyyBc04aytRRg7wYewiG0bcmnY5jt//FxIyOY5IavDyVU1Aet/jHq6ezZkcTq7c3sbI+WLk0ilGDjuFwc4JE0nFSRzWmtw289tFu3t6wx1vVR33vOROHZA3nVDOPopQWqgCKQDbThRsF1JKwWb5lP1NGDgTwSiUkk04c/OXTRnnRQpYljKw4JmC7dwXprPGVjBtyLE8t38aanQcwtkFCVUhbEzYvr97J9y4+mWvOGBOo1xOzwLYzhfvHuw5SHre47qyxTBtdwZodTfx+2TbC1iRDnuWd2wjnVDOPopQOqgA6kbA55NkV9cxfUU9zq40l8IVTR/Dt8ycFxmFMQPhbArPGDWb+Cqfb2A1npUtSu0loP1q02hPy4cJrT952NvNX1HvmpSeXbYus/JlM2pwwuL8Xtjl1dAX/a8GqSCXwdHUd16R8AWGeXVFPa0LDORWlJ6AKoBMJZ7y6K2jXyfvG2ga+ff4kx2wSs7wuY+A4ZyYOP47New6xbEsjy7Y08ofl23jq258HCJhRpowcyPwV9azZ3pRy5GbmJIDT39gSp9pnWAfEYk5Y5y/f3OgVsbtu9jgaDjYjwOsf7fZyGBIhZ7dLzdZGnq6u8+4dDouNQuv/K0r3oQqgEwnbvAH+sLzOM9nYxnir+GQyKPzjMeGTvZ8Fon8SNvzqrU28s2FPRpRNOAJHxKnM6eKao5KpPsanjxtM9ZZGT1jPGFPhmaviloAIiaTtZfj6FYYl0aUalmze5303Ab4yK3qX4J+TO19LhPuumpY1cUxRlOLTp6OAuqL8sL/Byazxldx31TTilnilIyoHlHPvwtWeqUWAcyYP5dqqsUR1a1tV/6lnLmputT3TkPuse6+ciiVODaD7XljjfTd/5nLSNhmO3pqtjWlzVdLQ6jNdCdCvzEl6i4Wigfz4o3z6paKe2sJv+krYhnsXrtZS0IrShfTZHUBb8eqdyQ1njQs0R1+yeV+gYFvMEr538ckAnr/AL6h3H0hXFzXAMzX1Xmw+OLkHdsrE05Kw+fnr67l82ih2fHrE6dWbdM6FBa1tnGJsgrNDQMRzUrs1fuavqOeZmnpe/zgYDeRSaJTPnIlDAnWS7CymJUVROocOKQAR+RdgLtACbAJuNsZ8GjFuC3AQSAKJfPtVdia5kpI6k3AkTL8yi5ZWG8sSr2Qy4AnTygHlvLx6p1dm2r96Dzta/WGYtkmXeBaCQTkGZzXv7jzK4xY/mjvVq2oKZAhyt15PW++skCgfd0d078LV2LahvExzAxSlK+noDuA14AfGmISI/DPwA+Afsoy90Bizt4PPKxp+B20sZrH90yPUbG3sltXnNWeMQVI/s2XGThk5MN1+MrRCzxCaIoTdvKkAI2IpJVCWanizekdT5LPd5/vJVsa5I4R3RLr6V5SuQ6LszO26kciXgK8YY74WcW4LUFWoAqiqqjLV1dVFmV8Ubhevp6sdx2xXd6LK1wwV1XcAMlfoAL98cyM/e3Vd1tIRl5w2ghljB+dV7jpbPR8V1opSuohITb5WlmL6AL4JPJXlnAFeFRED/NoY80ARn9tu3Fo+Cdt0iykoHzNUrgJqYcI7m/NPHsbidQ0kkoayuMW3z5+U8/vleqYKfkXpHeRUACLyOjAy4tQ9xpiFqTH3AAng8Sy3OccYs0NEhgOvichaY8zbWZ53G3AbwLhxnR8S2BlmjWI+u1BfRbZmK4Ws2rvTP6IoSteRUwEYYy5u67yI3AhcCXzBZLEnGWN2pH42iMhzwGwgUgGkdgcPgGMCyjW/jtKd9WnyeXYxFFShq/buVIqKonQdHfIBiMhlwL8C5xtj9mQZcyxgGWMOpj6/BtxnjHkl1/072wfQUyhkBV+s8Fa19StKz6QrfQC/APrhmHUAlhhjbheR0cBDxpgrgBHAc6nzceCJfIS/kqaQFbyabxRFyZcOKQBjzElZju8Arkh93gzM6Mhz+irtWYUXw3zTXUlyiqJ0LX02E7jUaa8QLoZPQ3cRitI3UAVQonRECHc0VFOdwIrSN1AFUKJ0thBuy7yknbsUpW9QtEzgzqCvRwF1ViSO2vgVpffSXZnASpHprKxbtfErigJ9vB9AX8Vft19t/IrSd9EdQB9EbfyKooAqgD6LFnVTFEVNQIqiKH0UVQCKoih9FFUAiqIofRRVAIqiKH0UVQCKoih9FFUAiqIofZSSLgUhInuArV382KFAQc3rS4ieOnedd9ei8+56unLu440xw/IZWNIKoDsQkep862iUGj117jrvrkXn3fWU6tzVBKQoitJHUQWgKIrSR1EFkMkD3T2BDtBT567z7lp03l1PSc5dfQCKoih9FN0BKIqi9FH6vAIQkX8RkbUi8qGIPCcig7OM2yIiq0SkVkS6rU2ZiFwmIutEZKOI3BVxvp+IPJU6v1REJnT9LDMRkbEi8qaIfCwia0Tk7yLGXCAiTal3XCsi93bHXMPk+rsXh39PvfMPReSM7phnaE5TfO+xVkQOiMj3QmNK5n2LyG9EpEFEVvuOHS8ir4nIhtTPyPK1InJjaswGEbmx62addd49R6YYY/r0H+ASIJ76/M/AP2cZtwUY2s1zjQGbgIlAObASOC005m+AX6U+Xwc81d3vODWXUcAZqc8DgfURc78AeKG751ro3z1wBfAyIMAcYGl3zzni380unPjwknzfwF8AZwCrfcfuB+5Kfb4r6v9N4Hhgc+pnZepzZTfPu8fIlD6/AzDGvGqMSaR+XQKM6c755GA2sNEYs9kY0wL8HrgqNOYq4Lepz88AXxAR6cI5RmKM2WmMWZH6fBD4GDihe2dVNK4CHjMOS4DBIjKquyfl4wvAJmNMVydV5o0x5m1gf+iw/9/yb4GrIy69FHjNGLPfGNMIvAZc1mkTDRE1754kU/q8AgjxTZyVXBQGeFVEakTkti6ck58TgDrf7/VkClFvTOofYRNQUj0fU2ap04GlEafPFpGVIvKyiEzt0ollJ9fffT5/L93JdcCTWc6V4vt2GWGM2QnOAgIYHjGm1N99ScuUPtERTEReB0ZGnLrHGLMwNeYeIAE8nuU25xhjdojIcOA1EVmb0v5dSdRKPhzGlc+YbkNEjgPmA98zxhwInV6BY6Y4JCJXAAuAyV09xwhy/d2X7DsXkXJgHvCDiNOl+r4LoZTffcnLlD6xAzDGXGyMmRbxxxX+NwJXAl8zKeNcxD12pH42AM/hmGO6mnpgrO/3McCObGNEJA5UkLm17hZEpAxH+D9ujHk2fN4Yc8AYcyj1+SWgTESGdvE0M8jj7z6fv5fu4nJghTFmd/hEqb5vH7tdU1rqZ0PEmJJ89z1FpvQJBdAWInIZ8A/APGPM4SxjjhWRge5nHCfP6qixncxyYLKInJha2V0HLAqNWQS4kRBfAd7I9g+wK0n5IR4GPjbG/GuWMSNdf4WIzMb597mv62YZOad8/u4XAd9IRQPNAZpc00UJcD1ZzD+l+L5D+P8t3wgsjBjzR+ASEalMRQldkjrWbfQomdKdHuhS+ANsxLEh1qb+uBE0o4GXUp8n4kTcrATW4JiOumu+V+BE0Gxy5wHch/OPDeAY4OnU91oGTOzud5ya17k4W/MPfe/6CuB24PbUmO+k3u9KHOfZ50tg3pF/96F5C/DL1N/JKqCqu+edmtcAHIFe4TtWku8bR0ntBFpxVvW34Piu/gRsSP08PjW2CnjId+03U//eNwI3l8C8e4xM0UxgRVGUPkqfNwEpiqL0VVQBKIqi9FFUASiKovRRVAEoiqL0UVQBKIqi9FFUASiKovRRVAEoiqL0UVQBKIqi9FH+L8kqXh5MAA+bAAAAAElFTkSuQmCC\n", 130 | "text/plain": [ 131 | "
" 132 | ] 133 | }, 134 | "metadata": {}, 135 | "output_type": "display_data" 136 | } 137 | ], 138 | "source": [ 139 | "choice_cluster, initial_state = lloyd(X, 3)\n", 140 | "\n", 141 | "fig, ax = plt.subplots()\n", 142 | "for i in range(3):\n", 143 | "\tindices = np.where(choice_cluster==i)[0]\n", 144 | "\tselected = X[indices]\n", 145 | "\tax.plot(selected[:, 0], selected[:, 1], '.', label=str(i))\n", 146 | "\n", 147 | "fig.show()" 148 | ] 149 | }, 150 | { 151 | "cell_type": "code", 152 | "execution_count": 21, 153 | "metadata": {}, 154 | "outputs": [ 155 | { 156 | "data": { 157 | "text/plain": [ 158 | "" 159 | ] 160 | }, 161 | "execution_count": 21, 162 | "metadata": {}, 163 | "output_type": "execute_result" 164 | }, 165 | { 166 | "data": { 167 | "image/png": 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\n", 168 | "text/plain": [ 169 | "
" 170 | ] 171 | }, 172 | "metadata": {}, 173 | "output_type": "display_data" 174 | } 175 | ], 176 | "source": [ 177 | "import cv2\n", 178 | "img = cv2.imread(\"./portrait.jpeg\")[:,:,0]\n", 179 | "plt.axis(\"off\")\n", 180 | "plt.imshow(img, cmap='gray')" 181 | ] 182 | }, 183 | { 184 | "cell_type": "code", 185 | "execution_count": 22, 186 | "metadata": {}, 187 | "outputs": [ 188 | { 189 | "data": { 190 | "text/plain": [ 191 | "" 192 | ] 193 | }, 194 | "execution_count": 22, 195 | "metadata": {}, 196 | "output_type": "execute_result" 197 | }, 198 | { 199 | "data": { 200 | "image/png": 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YxRhT4OQxWjGYWSNX7CF6hSH+JhipGJpKLjxUoxkqoxPDUF38MowpUdgsRnM3SdOvZ5Oept7H9lfBKDyDrnrLM4a/4eDF0PQ/se9X1Wnt7/vvKsOgxTCGq5mojkGLoWnGcPWcMMQLzWDFoPCoXob4ewcrhiYZomGMEevCP9LMfgocban6zcCPWqq77frHUvevuXthqveujDMcdfe89JW1Y2YH2qq77frHWvc0FCYJEUgMQgRdEcMdI6277frHWncunehAC9EFuuIZhGid1sVgZteZ2dFYRH3WwomLnv8uMzthZodTZY0s6G5m55vZo7GQ/LNmdnNT9ZvZWWb2uJk9FXV/MsovNLP9Ufd9sRoTZnZm7B+Lz1eW+e1xznWxQuyeputeCHdv7QWsA54nWV53A/AUcEnFdbyLZEHGw6myvwF2x/Zu4FOxvQP4OsmKpVcC+5eseytweWy/CfgOcEkT9cc5zo7tM4D9cc77gRui/HPAH8T2HwKfi+0bgPsq+NvfAnwR2BP7jdW9UHvbqDT1x7oKeDi1fytwaw31rGTEcBTYmjLYo7H998CNecdV1I6vAe9tun7gV4BvAe8kGehan/37Aw8DV8X2+jjOlqhzG7APuAbYE+JspO5FX22HSaUWUK+BpRZ0X4Rw/ZeRXKEbqT/ClEMkyxLvJfHCJ939tZzzn6o7Pn8V2LRo3cBtwCeAX8b+pgbrXoi2xVBqAfUGqaU9ZnY28GXg4+7+k6bqd/dfuPulJFfpK4CLZ5y/srrN7P3ACXc/mC5uou5laFsMbS2g3tiC7mZ2BokQ7nH3rzRdP4C7nwQeI+kzbDSzyTSc9PlP1R2fvwV4ZcEqrwY+YGbfA+4lCZVua6juhWlbDE8A2+MuwwaSztODDdTbyILulswjvxM44u6fbrJ+M9tiZhtj+43Ae4AjwKPA9VPqnrTpeuARjyB+Xtz9Vnff5u4rJP/TR9z9w03UvRRNd1JyOlo7SO6yPA/8eQ3n/xLwEvB/JFegnSTx6D7gu/F+ThxrwN9FW54BVpes+7dI3P3TwKF47WiifuA3gSej7sPAX0T5RcDjJIvW/zNwZpSfFfvH4vOLKvr7v5u1u0mN1j3vSyPQQgRth0lCdAaJQYhAYhAikBiECCQGIQKJQYhAYhAikBiECP4fYnX0Xt8W2eoAAAAASUVORK5CYII=\n", 201 | "text/plain": [ 202 | "
" 203 | ] 204 | }, 205 | "metadata": {}, 206 | "output_type": "display_data" 207 | } 208 | ], 209 | "source": [ 210 | "data = img.reshape(-1, 1)\n", 211 | "choice_cluster, initial_state = lloyd(data.astype(np.float32), 2)\n", 212 | "data = choice_cluster.reshape(img.shape)*255\n", 213 | "plt.imshow(data, cmap='gray')" 214 | ] 215 | } 216 | ], 217 | "metadata": { 218 | "kernelspec": { 219 | "display_name": "Python 3", 220 | "language": "python", 221 | "name": "python3" 222 | }, 223 | "language_info": { 224 | "codemirror_mode": { 225 | "name": "ipython", 226 | "version": 3 227 | }, 228 | "file_extension": ".py", 229 | "mimetype": "text/x-python", 230 | "name": "python", 231 | "nbconvert_exporter": "python", 232 | "pygments_lexer": "ipython3", 233 | "version": "3.6.5" 234 | } 235 | }, 236 | "nbformat": 4, 237 | "nbformat_minor": 2 238 | } 239 | -------------------------------------------------------------------------------- /notebook/portrait.jpeg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/overshiki/kmeans_pytorch/3cd8540094b6b2765ed27799091f2cb36cdc5455/notebook/portrait.jpeg -------------------------------------------------------------------------------- /pairwise.py: -------------------------------------------------------------------------------- 1 | r''' 2 | calculation of pairwise distance, and return condensed result, i.e. we omit the diagonal and duplicate entries and store everything in a one-dimensional array 3 | ''' 4 | import torch 5 | 6 | def pairwise_distance(data1, data2=None, device=-1): 7 | r''' 8 | using broadcast mechanism to calculate pairwise ecludian distance of data 9 | the input data is N*M matrix, where M is the dimension 10 | we first expand the N*M matrix into N*1*M matrix A and 1*N*M matrix B 11 | then a simple elementwise operation of A and B will handle the pairwise operation of points represented by data 12 | ''' 13 | if data2 is None: 14 | data2 = data1 15 | 16 | if device!=-1: 17 | data1, data2 = data1.cuda(device), data2.cuda(device) 18 | 19 | #N*1*M 20 | A = data1.unsqueeze(dim=1) 21 | 22 | #1*N*M 23 | B = data2.unsqueeze(dim=0) 24 | 25 | dis = (A-B)**2.0 26 | #return N*N matrix for pairwise distance 27 | dis = dis.sum(dim=-1).squeeze() 28 | return dis 29 | 30 | def group_pairwise(X, groups, device=0, fun=lambda r,c: pairwise_distance(r, c).cpu()): 31 | group_dict = {} 32 | for group_index_r, group_r in enumerate(groups): 33 | for group_index_c, group_c in enumerate(groups): 34 | R, C = X[group_r], X[group_c] 35 | if device!=-1: 36 | R = R.cuda(device) 37 | C = C.cuda(device) 38 | group_dict[(group_index_r, group_index_c)] = fun(R, C) 39 | return group_dict 40 | 41 | -------------------------------------------------------------------------------- /single.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/overshiki/kmeans_pytorch/3cd8540094b6b2765ed27799091f2cb36cdc5455/single.png -------------------------------------------------------------------------------- /triple.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/overshiki/kmeans_pytorch/3cd8540094b6b2765ed27799091f2cb36cdc5455/triple.png --------------------------------------------------------------------------------