Spaces:
Runtime error
Runtime error
Antoine Macia
commited on
Commit
•
478e20a
1
Parent(s):
65fa3e8
Add code
Browse files- .DS_Store +0 -0
- .ipynb_checkpoints/02_production-checkpoint.ipynb +0 -0
- .ipynb_checkpoints/app-checkpoint.ipynb +43 -0
- .ipynb_checkpoints/door-windows-detection-checkpoint.ipynb +0 -0
- app.ipynb +343 -0
- app.py +28 -0
- door-windows-detection.ipynb +0 -0
.DS_Store
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Binary file (6.15 kB). View file
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.ipynb_checkpoints/02_production-checkpoint.ipynb
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.ipynb_checkpoints/app-checkpoint.ipynb
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@@ -0,0 +1,43 @@
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{
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"cells": [
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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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"outputs": [],
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"source": [
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"#|default_exp app"
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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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"outputs": [],
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"source": [
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"#|export\n"
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]
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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 (ipykernel)",
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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": "3.10.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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.ipynb_checkpoints/door-windows-detection-checkpoint.ipynb
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The diff for this file is too large to render.
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app.ipynb
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@@ -0,0 +1,343 @@
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{
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"cells": [
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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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"outputs": [],
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"source": [
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"#|default_exp app"
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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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"#|export\n",
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"from fastai.vision.all import *\n",
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"import gradio as gr\n",
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"\n",
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"def is_door(x): return x[0].isupper()"
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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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{
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"data": {
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"image/png": 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hkv7qG25VDeo6g9KHYmvUYDMDmtJVqH5g+VI5ZmimluWahAiiYAsVofifgOuVy1EWYxlLLr814CUa2015GUEUmlVev+oHyv8AMjuZDEUuP5keYWkVrfT4I0Viyh/Uk71p+xg/MSPRIxealL5587TlvigjDjfjEtR8uTNgOXJ3LwRQl1r/AJyuqepqHpUrURLGta/7E5HiyFPDFQN35nkQI+qzEDwkK/8AEQMbmeqaj3OWfzCiFRqk9GNT+9ckn59cTx96+nuaF55kDfDqtx4GsjH/AIkDj6+9PDHuVU1fzdFuuqyMB0VuDf8AEkx4siOGKJj82ecYiazpLXryijP/ABHhh8bIEcESmL/mX5lb0/rNnbyiOoHESR7H5F/DD+Yl1CnEO9EWv5nItBd6ayCvImKUE+PR1TH8z3hj4SbQ/mL5WlLGV5bZyBx9WMkdP5k5jqcsGeJRwEJhbato1+UWyu4bgAdI2Unw6dctEgWJR6sohBZI3DGgDKPHrUZJFNJ9WWUqIAXIHQClPHfpigq6xJN/dQcu37NKj5HpiqFktZoo6vEeIH7JXsN98FJtpY6ur/VwQjA0JWhpvjSkobVLgLykktgCTQU4kdPDFIYZ5gkNxR1hA4gg1I33wJTLRlItYtqfCu30Zkw5OOX/0Ol3AJGZFNbGPMLMsBZTxIIIP05CSQpaZdzuVBm6d6L26dsqLcyWzuWi5OtxSRgBuV/pkVpHxXsrKqSz7Ag7caVp40xtaRKXBpQTgjcgfDTc18MbVRub2CGA3k89I4FMkxIBolPiNFFduuJNbqGK3f5kRKksemWDTLISRNcn016UqEALnxH2cxzn7m3w2O6h5i8z6oFFzeNHEBQJDWBfp4fG3+ybKZGZZCICUPa2kNZZ5QrHdnYgE/NjucRj72RlSFbW9Ai2DCVh/KC/49MkMYDAzZdaeTfO13pw1Cy0ORoGXnHykhRmUioIXkTjGQIJHIMiADRLELzXNStbiS2ns/QuIm4yRSluSkdiKDJRIkLDE2EM3mHUT0Ea/wCxJ/WcNIWHXNTP+7QvyVf6HCrX6X1E/wDHw1fag/hirv0pqJP+9L/fgpWxquoD/j4b6aH+GFNrhrWpL/u/l81X+mBC4eYdRHeNvmv9CMaSqr5nvBTlCjfIsv8AXGgtst07y95yv7IXa6BOYGHINziBIPcK7I2Y51GIdQz4CEjuL/S4bmS1vENrcxMVkilUoVYeJG345ZGMZCwpJGy9LWzmpJBKrDqrKQ1PkRuMgcXcvECmdnrXmSx4rbXjSRL9mKX98tPk/wAY/wBi2S4pxQYgshs/zDVLdxqNmyzPt6tt8Q32qUb4xQfy8ssGoHIsDiPRk+iapa3yC8sriltx4Bh8NWJ3FHH7NMvjIEbNchSLkupZIvjuCajp8Pcb9BkkBDrdzM6h5iIyRypQUH0DFkQpX6Wjx0muCRUmnIeGKN2Ha4tspIjnJjA3Nf7MBZJtoyj6vGOxUfqzJDjv/9HptwPhNPozIamN6u/Eh+HMhvs1pXIyZRRmk6kZaRR2w2FR8VNtvbKiWfVOltbqYq4jWmwpyHap8PfIFmCiBFMiMCoHA7/FWvfwxTaZWGoGOBYxDyK9TX9W2KEJr+o28mjXoaArzgZWNR3xPJQ8N1PVV00tH6bSECsSrtUe5OYoiG4sfuNc8w3e0Pp20fYIeTf8ER/DJ7BTZQJ03U525yn1H/md6n8ceII4SiItG1DqEX78BkFESyHTdS872Vsbay1K4gt+npR3DqgHsK0GVmMWdFCyaRrFxK0sx9WVzV5HfkxJ7knCCAKCCCWv8P6p/Iv/AAQw8QXhXf4f1X/fa/8ABjHiC8LY8varT+7X/g1x4gvCW/8AD+qj/da/8GMeILwtfoHVf99L/wAEuPEF4WjoOqf77H/BDHiC8JW/oHU/99j/AIJceILwtHQtT6+mv/BDHiC8JTWLU/PcFr9Vi1O6S3pQRLcMBTwG+U+Fj7k7pJPo+qSuXkXk7GrMzAkn3JOXCQHJBiUMdH1SJuUalHH7SuAfvBwiYQYlF22q+ZrQ0kQXEY/ZkI5U/wBYfxx2K7p7p+uR3oVDEYp2NPTeh+kMMrlEJBexeUrWVdEiSNBwDNxJNNq99jmXjFCmiR3TX6jNKqMONJARTkar1G/w5OkIS6tpoVYMFAXbqfGnhgZApLetIqtsDStPp+jIlkxbVS6qUoK0rSpwKnmj19GMH+UfqzKDjv8A/9Lpc5JQnMhqY5rRpCTUjcVI65GTILNJkhRgyu4J2anLp92UtrJrK5PRp5NqcNm+ntvgIVGxSLIz85HO+5+IHbbwyKURALZU3kcbfEPiGSpCF1+O0/Ql7xkJb0jxrXuffAQl4X5phrdinZd/nXMeXNvjyQNrbmgyFskRepJFYyyIeLqKq3hvkQd0UkS+Y7mJzG85DDtQf0yzhY2UTF5nfvcH7h/TI8Kd0QnmlxQ/WD939mAxXdVHmub/AJaP+FH9MHCF3XHzXORT6zt8h/zTjwruuHmyYD/ekfcP6Y8K7uHm6UbfWR9IX+mPAiy2fNcp/wCPkfKg/pjwLZbPmyX/AJaFp8l/pg4U7u/xbIP93ofmq48K7rf8WSf7+T7hjwsrK1vNj/79T7hh4EcRUn82yHYTJXsKDEY14ymej3dxerK8tPhIC0FKVGQOyQbV7iHrthBVbosB/ScAUVbnsPoycNyiXJ7l5Ya2/Q8Xqu/NWfkFL8evYLtmWDTjJm4tFStu0gHE8f73rTbDsVQMoiMZE3qmhFSfUNclsqWajaLQrFFICepo/T6ciaSxHVrZwo5xuOQqpKncYGQKd6UOMEYA2AGZIccv/9PpM/2cyGpINURpaRqQCx2J6bb9sBSERo9hfIC6yRkFdxRunXxyqtm22Q2pvART0jxp05d8ilMre3vFfiPTJclv2u5740qtBFeTxt/dqSCtPiriqX+ZUuYdHuyyoV9OjBajuPHBaXjXmG0V5qoKigIHhXMbLzb4oS1sjTplDJV1KyP6Nmp4D9YwBkSKed31sV1CQU7D+OZHFUVxRsr4I41JDMAQd65RMlyYgI1VtqbyAH5jMYyn3N3pVAkVP7wH6cgZS7k0FwWHu4++uRufctBRu4omAVGBY9stxGQ3IYyiChGtnHbw/WMyPFazBXgjCyfEKCnfbKpysbNkABzVyISNyo/HKvUz9LfpwfzKcTKR6IoLWWEjYr92IlLqEEBRlEQB3Xptl0eJgaQHoEyKabch+vMoS2cecNiXoPli3/0ecU7r+o5jyLVEI+5t2B/hgtm1pERXUI2O1G6/RluI+oMMnJ6noV9N+jxGFAjR2Ar/ALeZzikJo97dxRhUVGqKkmop38cUIgxzzREGSMVANeJr4/zYa2VLNTuruBAAysVPH7J7/wCyyNJYtrWo3FwqMTGvpqVXip6V9z7YVqky0tqRJXpQZkBpL//U6TNQrmQ1JBqhVaFgSoO/GtafRviUhW0oRkg+nP6ZBoB6tAaimVNiewNZpTaUMaVBElfbIlkEShAlZh6oWvwfbyJVFJGxQNCJumxX1AN8K2gvMUTnRrskS8lTct6lBuOtdsBCQ81vYmmk3UVoKnx3yjIN26K+2sfbKOFlatqNj/uOm27D9Yx4VeaanY/7lJQB+yuV5Z05WmjaDfTPUueJWuxpUZGOUiLYce679CioHADtWmSGQlTiCMHlxChPpj50GDjKeAK8PluIpVox9wwGUu9RAOj0SGO9iVUA5VrQU6HITkSKZRiAbTCfRVQD4dtj/wAOMoEd2ZKEvtFX1IldQVY98MSYpMQVCfQolcBYwB22wDPKtyjwwV8Xl6NwS0SnbaoyEtRPoyGMIefRIo1oIlDd9hhjnne5YnHFAtpdDUKBQjtmQM/Rh4a5bJg67d1/XhjlBNMJwqJekeWbE+hPt3X9Ry0xcIFG3VjsT3wcKeJQsbYxXKvQEhtq/I5biG7GR2egeXRE+n1KAsZG5MQN60OZrQU0D2ioBIilhsdganFDU0cToRDB8Tj4SAoNT9OBUmu4ZOVDETQEUov9cVYvqtrIwosPUkEfCOv04VtkOmrSBO1AMyQ0F//V6O5qpzIakg1hnWPklOQO1dxiUqml6hPHxj4xlab1DeP+tlTYn0b3Mjcyy1oABxOwH05Alkm9paXM1p65kQKGKU4mtR/ssaVHwrdRW9A6FY1NCyntv/NhtFIHWr66bQb1CIiZI/iNGBpt03wFIDzWOIO77dO3hlMw2hMrS19shTK1XU7dRpc238v/ABIY8KkvOLmzD6xMKV2X9WYWqG4c7R/SUHNbXUF2ZY7cyxjwO9Nu2VRMaq3JINugmgkfjujkH4HFD9Hj9GXRjs18SblESIEjYg0+jHqqhJqNrEDGtXk/32gLN9NOmJCLb06K7uL2KV7YxxKTxZiK779B/XIEjozAPVObyJaLtuAK/wDBrlchuEoLWLSdo4XtoTKwNWVTvTDQUlLpJhyUSI8JGxEgpv8AMVGQ4QSnkm2mRCQtUdBkOBkZIO9jtYqvM6olaAnbCIXyRaVSsJyVtbaR46isvHiBT574DCuZCLPcuks+IXb9oV+8ZLFH1hjl+kvRPLFqPQm2/l/jm1MQ6kFH3FopJ2wUm0sntuKkgdCMlCO6ksu8vRJDpnGRyXDkkACgqB45eC0o2SGF4y4b33I2xtWriURRLwm3pQfZI8MVSu8uJGB/fAfLj0GKsY1K5lPICTbcE0A/hgVkOnn9wg9hmWGh/9bo8o2zIakg1TsOHPf7G2/30GJSFbTBZP8AC9kRJ1pxSn68ppsT2KxJbklkOJFBsopQfPIEJBRVvFHbxMJrchgx2IHX5A4UqtC1rzWBgQKsw402613xVD64bb9CXP7ngQgo4Cjeo8DiUhilvbhByFWSVuKPQ8eVK8eVONdspkRdNoBq02t4e9MACt6vEBpktP8AJ/4kMkAgvOZFpqtzX/J/VmBqxuHP0f0lAzXWoR3zrbxLNFQMUJ4tX2J2zGEAXL4pWrxDStUBhmQw3QFTFJ8Lj3H83zw0Y7rYls1+g9V9QWzXFbKlRMN3of2a5Z4nXq1nGuvbvRPL6BGdDLSojXdyfH+04cWCeY+kW15tTjwi5GkJ5a8zyavrT26R+nBCnPc1JqaZkanRnCASeIycbS9oDUEiI4RH+cye5pzUEdeI/wCHGYh5hzkD5j1OTTLKK5jiEgDcWQ7VHTY5dhwHLPhBpx9VqhghxEcQ/wCKQ2m+ZNH1ROE6+g7fDxlApX2bHPopwFyHp/nBhpu0cWXaJ9X82X1K8lpd2Ls+nBXWSilGqVAP7Qp4f8D/AKuY8Y1z5OZdoebTrOzha81CYSS/78cilT2QD9S4kkpFBA3F3qM0XqWtq0VmCB60x41BNPhj6/fiYRH1c0+KTyVpo9kHclSfwyeL6g1ZvpPuej+V4a28/jVf1HNoQ6iKZz2+24wUzSq5t+YkHFisYDysqkhFrQMzAUUbd8FgEKeTI/K3EWjnhyQSnjU0rsPH+OXBpIR91d86qsAFCRuw2pt2GFQEK9w0VuKwhioFSGHbvuMFqll1cNUEw0HIbhhWnttgSkOq6kkYKmAN23bp+GG0Umung+kh9hmSGl//1+jybKaZkNSQ6oRXZ+FP29tvvwFIRWmgMVc3IUEUP2N+++2VtiepeOspjiuBwoPtKnf3yJKr+TP9qetTU7rWpwMkzs7SF7QcroioowHDuN+uICEF5jsoF0W7C3HL4BSpXfcbbYlItKtJsxJ5MW43qL+mzbbR0+zmHkB8QHpu3xJqkVBDRem2XBSo62lNLl2HVf8AiQyQYl5jc/Dqtx4/DT/gcwNX9Tn6L6D71GFa37FT+wD+JzFiacwBq5t0vrmK2UBRE3Jphs3L+VT/AMSyQlTGQTBdXsTfnRRKPrIj5DentSv82TGMkcVbMfEjfDfqef8AnPRH0y/9ckyQXB2cnkVfrxJPj+zm50GoBjw9Yuj7Q05EuLpJFflwy/pi4YU/ulr/AMFlfaZsR97PsqNSl7noUwLSqfAg0/2QGaY8w7pLPNcTT6ekYFSWG345m6A1lHuLru1Y3gPviklp5eaS1SJVoZW3J328c3mpzRx4zIvK6bTSyZgI82TSG30W2ghuZaRuyxxl2qeTdq5zX1Wae4iBEAE/0Uv1ezMF5HqEn72MjjuQwj/y0HT54BNnVovU6foQkf5G/wDshlEvqZBByoPg+a/rGX4vqDVn+g+56T5UQehP41X9RzbF08eSbzR/CcDML7K3RtG1/ejfVo6DkQNmfsMrMRxX3JJQvllgLOQSSGocjkNqUAy8NRTFzZV/vTU7seR6nrhQo/7j2h/eyP8AEBy+Jvp6YKCpZqP1QrSKRuROxJelMBSxzWI7Sp+ItTpQtXpgVPdNr6SewGZYaH//0OjSj4cyGpjmt1+ryUXkfA7V3xKVDSkmJ5ekvEgCnIePyyotjKtOinbkohX4TSoYeFfDIUyTRLG6jTkY0oxJX4hX7qYoBd6dxKtFiAL/AGfiHcfLFlaE8xRSJotyOCqQF3qCa8h4DEraD0i9VfLEdgTxm+veo0XHonp/aJ/1sxJiRyAfw03Q5WmUNOAy0KUNro/3GS/Nf+JDJ0wLyq+31mcDsV/VmFrBu52iPp+Kl6whuZX7pGPvqaDMB2EVSSWPT9Ma5kPJwpdj3JP9TkscTKVd7DLIRiSejzRZ9Rk1UXkJLXpk9Rfc1+z8u2dJ4ceDg6PNeLIT4y9S1GyTzF5VfkvpyyrXiR9iVP6MM0ImcOT+q7yQGXH/AFmMeRtGvNP1Kc3C8ecYUfMNvmdr8glGNd7h9nxqUvczg1MyitAONf8Aghmtk7QobXUeSOJF6ltsyNHKsg9xcPXxvER7kxSCNIYVAoI415n/ACuuW9oZuOXD0h/unG7M03BEy/in/uXlHnTVX1HVnRG/0e2JjiA/mBozfeKZl6PHwxs85f7lp1uQzlQ5R/3TM/J97LqWiNBer/pKDg1Ruyjo30jNXq8QhOv4XZ6XNxwv+IfUqyu40Wa2k+3ausZHfiGHH8MxJc3LAWuKMg91p94zJw/WPe0aj6D7np3lMD0Ljx+D9RzcEOmgdk5lHwnI0ztAPeeha6tCSQLu1WOMACjMrNtyPscqnH1AshyKr5YM8llIsYRFSSlGJ7qPDMhpKOawuG9Ry6UFWOzeOKLUVsrmaI/EiAjoKk7jwxpNoC/srkbFl3I3APfI0ljupaXNE5b1AaqduJ/rhpBKcadX01HsMyWl/9Ho0tQvtTMkNTH9Z4GNuZ4oerVpTGSQ7QDYVl9aZiFVTHR6VJJB6DKWxldl9QT7NyVeoIo/9mKopLwnkHmYjkQK0NQCQO3hkSUgKZlRIeMMjGn2QGr/AAwJKF8wPG2jTgykj4Tuf8oe2JUJFpErOpdqdRuO+RI3Zg7Mggf4cQEkqeuH/cXL81/4kMlTCReV3S11i5Pun6s1+tPq+DsdCPR8UBK6HUDATUsVqO+xJ/jmvI2LnxKK8yWF1d2bQW6FwlDIF9th+OZWirjvucTXSqFd5YamlXNpqUaSqY5AwPgc23iupMLD0byszfVJrVzy+LkCfBuuajW0Z33ux0N+HXcgoP8AjsSAt9haU9weuSlK8cWzFHhyyCYhm9cg/wCQK/7IZRLo5S+/TlLCK92/VlmCVSBcfVC4O1G4aDRJLqu/pu496DbIg8Uv6xZgcMPcHkZt2aldzXc+ObjjdNw2zryxzhmgY1oy8GHzzB1xBALlaAGMyETq7JFcXaEhfWVGFe5V81sg7a9l7sCsYpQhkp771zIwf3g97RqD6D7npnlL+6n/ANh/HN2Q6OB2Tqf7OAswker1Fu7A8SBWvhTBSbRHl1Q1o5jSR/3m7jlQniPowsSU6giVUP1iCUsSwqQ5qK7d8WKlcC0eBjbxSk8DQIrj4qbUrSmKoC8itY0USxSAmlHKuflTFILGNYjh9SoifgKncHw22ripTew/u1+WZDU//9LocjEr9GZIakg1gsEbiKnagJp+O+MlBV9L1GVUI9JRQAfa23/2OVXs2UmdvdkszcBXYnfwFPDIFmmUEryQ+qAKEHbken3YFVYbgmINwXiq9SxHQfLFUL5jL/oW4YhQKA7HsGHtilI9JkSSDmi8BXpt/DFU+tjhpCnrp/3Fye7L+vDTGReYXP8Ax1p/mv6s1evPq+DtdB9Hxd9Z0j1zC0ZN4zCjcWpUAftfZzFA2czkU30m9ht79lkAMc4VeJ9t6ZHHk4LLj6qPEAxvzxJAvmSMKKdOmXR1F7uN4VJx5blVnlP7IA3965jyycRcrBCgrXFzpgkk4Rn1lZiWCnt13O2WA3s3qHrhJ2LKRwCMw67Fgf4ZKUeQYRyAi0TdahpkNZr4GKONgjMwPVun2T3xMDE0UDIJC1DzG8TeX5Gi/uGiJRelFrXp8shE1Ie9cg9JDzfl4bZknMXCEGX6NICsFNyStMpzZeIU2aeFTtMNSudNhdhfU5vVUNGOw6jb54IRc0kKDhWkjYHYlKD7slg/vB72rUfQfc9O8pUMc/sE/jm8dFFrzJ5qttIuI7eS1lnMiepyjKAAVpT4iPDK5zAbIi1M3i3ulx3iIVWeMSIjUqOQqAaVwjcWhNvLQu1s3o6fb5FeLEdB/lDFBRkmo33qPHyiHBiDRTv97Y2hCm6vYIyVljYItQCm2w6bNimkuu9QuriNWaRAKqQvEjp23bBaQx3Urm6llCNMiKxIrxGxAJ8fbCgp5p2yrXwzJDS//9Pocn2TQfLMkNJSLVBCdpiVir8ZUkGntTGSx5rdNXTmarSOrEU+05NO2VNqbQJEJCF5FK0/aO1PHIFmExgMKxqgZgv8g5bYFXwiARjmWFRvXn174qhPMXAaLcBS5qFFDy7sPHFUh0S4jWEqW3DUFdjTbxwhLJLZg1CuSYkqeuuf0Y4P8y0+/DTEvMblv9y05r3X/iOajtH6h7nb9n/R8VN6cnen2GRvxoTmvifU5x5O1z1vq8dxDIYXjZWLAVpTb+OW48JyyEB/E0ZsghHiPRg/mbUruTWUeS6LEBd+PTb55n4+yZwFHhcCWvhI7B6D5JicaK1zKxf1SXDtt8Pb8BmvyYzjkQf4XYYZiUQR1S+1vRcXN0VYmik0IoB16b5kZNFPERKX8bVi1MMnEI3cUxuz+/nB6GNB+OCf1R96MP0lJPP06jyzdyRSVBuLcBweXenX6MyPCM8oj5OOcgjiJ/pJzYypqvlWN0avrQFW8QeND+OYU4GEuE/wudAicb73kr3V3GzRtcEMhKsCvQqaHNkNFI77Ot/MxBos78iGS4m9RpTJHAq7cafEx/oDmBqdMcZ3/iczTZoz5Dkm2u7s9d+CVPzkb/mlRlV8ve5IHNeoAEPc/Aa5PTy/ej+swzj92fc9O8pf3dxXsE/jm/p58Jb500PUr69intLdZ1VERiZFSgDkuKHvxPwnKskLLbCVL4gbTQYLWT4JoYFjZAwJBC0pUdcmBQYpx5YWP6jIXtmYep8TUUk1G3U4QpR8stiSyJaDnUAkolRT3rjshLZo41i/3m+MblgF/rkWShcWfILJ9XpQg8fg6Vr440tpLq72UaENZ1qeNaR9fvw8mKcacRxXwpmQGov/1OgyV4EfdmU0SSDWpDHEzgAlegPTrgkmPNDWdxOaH4BsBSpPQn5eOUtzKdJW5ngMp4qoPEVDbkd8FLabWmlTSByZo041O4beu+PCm1NTNLGN0AYeB2r9ORTaB8xxTDSJ3ZlqCpFAafaHvii3murX8lpe+i0EktEU84wOJr2+JgclH3KbZ95beU6ZAZQQ5FaN1APQHJ0hE68f9xjf6y/rwoLzC6P+5Wb5r+rNL2j9fwdx2f8A3fxdCeU0qMNmUAj6TmtvdzwiLcpf2RgK8pF5RSj3A2P+yGZIuJEh/WaZRBBBeaahoeqXvm2PS0jZncijAH+7HVv4f62dLPVxOPj/ABxOgjpJeJwdP539F6T5j1GPQ/L31RPgmkHpxL0+EAAn5UzTaHTHPmAPIeuf4/pO01mcYcRI/qxYf5SvJJZ9R5NXjEpU/MkZsu2f4f6xdd2QbM/6v/FJ3DcP6dyWap4pQnr2zVZ/qi7HAfQUm85zkeU7n1DX/Sbfb6TmZpv8YH9WTi5v7g/1gqflbr8UqS6Q5o28kAPcH7QGR7TwVITH+c2dm5rBgeYSr8wvLd1Yav8AWLeJmhvGFAo3Ep2p/sv+JZboM/FHhPOLVrcBE+Icpf7pm3lHTP0VpSiYcWK85n7ciBXf2AoM12qnxzt2Gmx8Ea6rdSZ2tLiZxR5mDU8F2Cr/ALFQMw+K5Byq2bEn9yp7cN8u04/eA/0mrUf3Z9z1LykfhuPkn/G2dCQ89EppeljE/HZuJ4nwNMSGTzQ6jL9c9FrSbnz4tMeBUGtOX2q0yBVn3ll+dlKGuQDzp+wNgPfEJKYvDCH5C7qW3f8AuxQ9PDGkKYtrWZVD3nVT6grGBttQbY0m0PfelDESt10KitY22rQ9seSGN6tBDMtXutgfhFUH0kUwc1TTT6BF+WZAaZP/1egyH4cymgsa8wqTayChNaCg6nf2wSTHm1otvbBSZ424krwHGSpHfKqbmX2L6WkJRYZAxOxpIAD3wKmEL6eIk5xylqH1CyyHud/uxVfPFYPAfq9u52FCqMBSvbEhUu8xi0XSJawPw5IACrd2FNsgQrzxfLr3erJeNyS3Wg9Pm25Hig+HJgKWd2C8UAHRRsMmxC3X9tLb/XX9eKkvL7sj9JTH/KX9WaXtH6/g7js/+7+K2OQfWX+Q/Wc14G7ngqVrePFqfO0UyknhcIv2aA7EnpzXtmWOVFqJZRHDbRytfelW9ZOKqKcqHfbem+DpXRjW7yLzvqOpz6rJ+kI2t2+zbqfs8f8AJPQ++dR2bDHDF6TxSl9bznaEpyyeocMY/St/L0Si61JSeRaFAoH+s2YPa4NQ/rFy+yhvL3D9LMbe3uTDch4yrsECL3NG7ZqM0wZxLs8OMiJBY95+juY/KU3rxmJjcwUB8OX9mZ2kyA5gR/NLi54GOGj3vPdGu9Sg1K3fTgzXqODCiAszHwoOoPfNrkEZRIl9LroExkDH6n0JbXj6npttJqNn6VzRWeIkFlYDejLUZzko8JIBd9HcbhC6neyfW47ecGG0SjFmpxduwJ7KPfK5nbZsjz3QWqNWzl7g0I+/MWP1Nx5LFZS0Pj8H8MydP/eD+s0aj+7PueqeUSaXH+qn8c6J5wJ3MtVP6sWdsJ1zy20l+l9AaemQ0qc2UEKa9F2P05XIbpCf6BNW3k/cAsCtQCKdPcZFU1S5EcZRbUVLFq1WlCBt09sIKuBmmibjbqAQerL32ySoS/ldY1aS2A4gA0K0NNq9MBKsb1aGdoxIIEpyruwB77CgyNKmth/dg17DMkBoJf/Wn8pPHMpx2Pa48iQsyULAild++Aso81TRri6lHAlB6dP2T33/AJsgW1kltFOpqjovI1PwmnTt8WRSj7druSFf3qAsCP7s+NOpbAqJLX8NszrIh9MDYoe1B/NiqS+ary6Oiy8mjA5JuFp+17k4CqSaOQ9ojc+ZJNWFOv0ZZFBT60/hhKFHzAf9xTeHNP14EF5Zd/8AHTm+a7fRmj7T+v4O57O/u/iui0lLhmuJ5WWIkgICQpAPelMx8fLZy5c151bTbBfRsYxLKNqINh826DLeHqwsIOPUtWjuDfep6gbZ4eiEeC+FMmOHkWMgeaZm40XW4za3caM7bNBOAG+itQ30YRxR3BUiMhRS6z8oabod3JdWRKJPRHjLEgUqRTlX9eHUameSIEv4WGDTRxyJj/Ej0YNOdtwU/wCJZhSPJy7W+YvL1v5gtFsLhmEPNZX4GjfAdhWhy/SZTjlxBpz4hMUeTWneXfLflu2rFFFAx2LGplcj3PJ3P05fPPPId2qOKMBsF1zeX1zT6sTaRKeSsQDIxB2qP2V/4bKZSA97eASuXWopl9DUo1jc7eof7tvev7JyPD3JtCXui1hJs5ysTCpQGqnv70+jEVe4Qp8eMsPUUKA/hkdMbyD+sxz/AN2fc9V8o7m4H+Sn6znRvOhPZt1OKUsv1Jtpu9UP6sBSED5fosUyl3QgrUGoI2P82VHZmUyPEsSZ22NAK9qD2w0hYbwRoUjumUGtKEfxBwJpBXV00kIEtyzKwBYEj+mK0x7Ur1i3A3LiKtDTem3ywgqeTIdPNYFPagzJcZ//15/Kw4ZlOOxrX052rinLkRtSvfBJMeaE0WDjKf3DMoFKFR/XKt2+2V2ltRAXtWpUkbL0PTviVRluiNER9XY1B4kqv9ciElM5ZNPoojsiKKOZ4pSvTpXJMQlnmyBW0V1gtQnJ0HOkYod/A5EpSDQ+QsV5gBgzCg3GxyyPJBT62OwOSQoeYWP6KP8AxkX+OKC8su2/3KTfMZoe0/7z4O57P/u/ilk0YmvZRIz+mKcY+R4Gtd+PTKcWQiLlSjZRqxxRxBQgUdgMeK0gK9uKxnlTboB2yEjuypVktLe4hZXQE9q4RkIYGILS23oqOMkjJSvpsxZQa0qK1pglmMpUmMAF9qWMzbj9itP9bBk6Mgi9TLsY0jleEM4VmjbixBB2rkMeQxLIxsKUdlaQMXVOUp2Mrku//BNU5M5ZHqxEAGuY45BmQhSVccSASdqH3ydsaQtzZpBEJLd3hPJQVRiFIJofh6YfGI2YmA5qhkLywV3oV3w6T+8HvYaj+7PuereUDU3H+qn8c6R5wJ/KBxIxSl12f3MvspIP0YEoHQry4Rp/hVqhSDuB0IG2+RZJol5PIWoiAKd6MfCv8uNql9zFPRqhaMSaAnua+GQSCgpPXMLCi0ZQK1JpX6MU2kGpPPXhxWpOxqQB+GKCyXTSRAlewH6synGf/9CeSt8JHgNsyw46QawGMZCtxJIoaV6nwwFIX6ZayCrLccaAH7I6gU7k5WW1OYry8VQBMPhYinAfsnauRtkird5vR5/WACgJVeK4FTaOzaRam9oaghQE6DfwyVKUq84GSLSG/wBJ29RegSvfpQZEqkOhsDp0ZFaEnrWteR8cnHkgp5bMMkhR8xmmmU8ZF/jixk8pvHpqc591/HND2n9fwd32f/d/FLp5nS8f4HYUFCFYjqe4BynFjNOTOQtVa7PCqrIDXp6b/wBMmMXex41W2u2VaenKzHr+7f8A5pxOJlxo62v1UNySX/kVJ/zTlc8ZXiC0XQlBAVloAPiVl7/5QGVyxESBLMSB2C+0cJKwJ7x/8SxyHkoRWqSKnouakeopNASdgewyqMSTQZ3QUW1CDf7ft8D/APNOXDEWHiBQN7GF6NU9uD/0yRxFPihSNygYGjbf5D/0x8Mo4496je3YeFVUP9tTXg1Ote4yPgm7XjCrH/eQH/Uw6b+9H9Zr1H92fc9W8nsec/8AqL+s501POBkUhBGBKX3tPQl9kJp9GNbJS3y+9gTMzKUqFIUcl8an4dsrIZJlz0sElZW/yhWSv040qkx01kJZn3ZuNWkPw12/DGlQV2LP0qRF6U+Ghkpg2VItVWwoxaoG+9X227YhKd6f/cpTwH6syXGf/9Gcy/YOZYcdj+ukGAgryUkfCAD398iWUearpUcXq+p9QqpoCOKbUUCv2vEZAthZDam2ZUP1MlR4LGKkfM5DmkJha/VreA+pYH4BViREaU698IpSF8tzBLullQgihpGOhB7HAoCT+abwJYR8IArmUUrxA+yetKnFKU6SxFjH0Jqfb9o5YOTEp1buKDCi1DzEx/Rg8TIv6jiiXJ5VdOP0lMT1qo/DNF2j/efB3XZ/938UZblVqONRyPKlfnleP6Q5EuaNjMR7EfMZOkK0fpk0AP8ArDbEhUQrRg9PvyNKCgdWdPSXYA8tiOvQ4JR2ZA7pZbNW43O1UNfpynKNg2QO5TxSpZeShqDbBgG5RkOyuVWhPAgj55khpUWK+BqO2+KaU3Ydl+nEpAQt04ETbAjeowUlLQyBoPElR+OU6YfvR/WRn/uz7nqnk8/vLj/UX9ZzpnnQyKQ4CyQFwQY5P9Ug/KmPRQl2h2TyGUwSqy0ULyBP4jKiE2mbaPdVZ2lj+L/JPYU8clS2pGzuSvxMgUEhSQTWm3SuAhKEu7e4ihLckIQeDV2HzyNKkWr2UrxNSRfi6kqdvnvjSpxYbQJ7AZkuO//SnEh+DMsOOx3X2IhJU0NRQ9uuCaY81XRbmSVAXmRWDUBAUHoMrbSye1iURDleH4QSuy/PvkSFtS/SFyUIM6kOKHZe4wMkVGRRW9cbsA269/oxVA+aYLUWERaX1P3mygqSTxP8u+KpNp5MVrFGwowG6+FScsHJiU3tpBtvthYofzJOn6PRa7mQUH0HFS88Gky3F3LKXVEYjjUiuw8CRmv1Oj8SV25+m1Yxxqkyt9KKr/fR16kkqP8AjbIDRkCrbTrhfJFLYgdZIyPYr/zVj+UPev50dyulhuGV46/Mf1x/KHvR+dHcq/UZKgkoaf5Q/rh/JHvR+dHch73SJLiNUEioAak1B7fMYPyR70jXAdECPLU6To4mRlqOVSBSm/jvgloSerIa8dyZppzoasyMAKUBH9cEdBXVJ1wPRe0LkUHp/wDBD+uS/JnvY/nfJRNu1KAoB7MP64/kz3r+dHcsNmOQNUr3BK7/AI4/kz3r+eA6KNxYeopAKA9viH9cfyR70fnx3JXPo10jREFCEZS1GHQH54MOh4J8RK5NcJRIp6F5PuE9W4UbngpH0E5sgXWBkUsjda7eGEskDNJUOAabHB0UJbpcUqXEwKseVCTHWh+dMglOLYxrzFwk5oRxJ9SlKdqe+NoLUkmjgUCsGB+IBZK1rvhVAGbS1irMrj4fiJEh6Dc4E7pJrsFu0dIYZabVChxUdT1piqaWB/cJTYUH6svaH//Tm8m6HMsOOx7Wni9P94pdKrVQAT198ZJDtLvbcqFjttwaGqr1B+eUtrItNnghT4oOXKpNAu3XFNJpJE93aH0YFQ0puVG5P05FSVFoZYKc41JNBsR1OKUm8yKRbROqhOLliSajZT2xVgGp61czTehBKVijIq6/aZhvWvYVw2qvaapqn7VzLT55HjK0qTXV9cBQ8zuqbqGNaVFK4LKaCiHvieIdqDpuciZFREL1e+Xb1H+Vd8BkWRiFVZb6lWd/vIwcZTwhFR3MyJUmQj/WJw8aOANnUbon4HIp1Na4RNfDDY1C9O3qN9GHjQYBetxeNsXan+sRjaOEL2luabSn5cjjbMRC1prwf7tNPmcV4Q4TXoFVmNfDHdhwhTM2oyNtKfvpkSSyoLgNR7yt71wjiQQFGU3wYgs1PwxJPVRGKpayXULF45HRyKFlYg064Y2xICIfWNXj2NzIy/5RyQJRSy116/t5wWcypNRGViT12+jrkrWmU6DLcRtKobdaBlapIAJpTfAVTdLi6eR+LJ8FKDgW+0P9bFaUmtJWLP6yjmeVeJpU/TiqTXayyxtV1UCo2B/rilJ9S1m4RSq+nQ0BND3IHjjakJ/p5rAjew/Vl7jv/9SbS/ZzLDjsV81SvFZl0NGDLQ/7IeOMuTKPNL9Iv7tY1Ik3+10HU09sqberIrG8uPQC89jWuw7nftigptHqN7HHRJSoFABt45AFVVry6mp6khbj9muLJJ/NckjafECxoWav3YqwSFFLtUdWNcVTO2jTYU2wRVDXxMchCfCK5EpCGWR1kHFiK5EsxyZCigxBiN+INfoxQpB22FdsrJZo2JFIAIFCN8tjyYdVN0QNQKBXrsMSE2700I3UYCFtWRErTiO2GIYq3pRlT8IwkLai8MQegUAZAhkOS8RR8fsjoe2NMVNEXY0GSiqMCgUAG2WBBWSqvDp164ShShRTWoGQCtyRp8S02pWmEqlvpR+ovw9GH68YqzCxAaYswBPEb4UBF2sUTXMgZAaHbYYQpWywxLJIoQUDEDbtQYlIQF3DEIJCEXZTTYeGBVmsWFksQIgjHw1+yPAYaYojTf7hB2oMuaX/1f/Za1nEowAAmI1JREFUeJyM/VmTZNtyHoh9Pqy1944hM2s6dcaLA1zgNkGCFE0kxTY1Jcp6MD3ora3/gH6VfkK/tclMJpPpoVstkS02mwRJgACIO5w7nLHmqsyY9l5rubseVkRWXQA0U5hVWVZlZGTEXr59+Pzzz+n/+d//z+5ORGZWSqm1uru7t1JOx9vb29dWlwRm5pxzznmz2axWKwAiLMIpK+DMvFqtdrvder2epsnMaq3WQkRbcwA552VZllo0Z1W1cEQICwLeqtkiwhGRcyai1hozi0h/V6p6Op2IyMw/+uSLYRhU9Te/+c2gOuTB3TyW64fXQWpLnfenpEmTHg9HEclDblFPp9OTxx/lPJyWspSaUia3uuxT1lorEe0PByOU48nc8jBGNFB79eolQRCYD/PNzfVmM+3LfpmrqqYkrRkTTdNVuBDTMAwppSTaSpE0sozhPp8O43btRrXURw8fPHzwcFmWr7/5OglUqLnNpaxXKwC11jwQiwTicLtbTWv3YNBxfxhXq2ZeWi21CktKY0qJWc1sKQd3a625u5kNwzCOo7szMzObGQAA1povNWdl5ohw94jo33J3Dz8s89WjB9fr7el4PN7trbXWGgARaa09f/789evXZnZcZl6tnnz25Thsh7wWEVVVAETUX46ZU0qllABAICIRUR6mlJOmnIfW6jiO2+12v9+7e7ehbnDDMESEqm63WzNzj5xGEdnvD6VUVR3ycJiPT54+Xa1XAbh7mRcA8/6gGiDsdrvVatU/ZCnF3XF5TOMkKsfjCUD/8NM0RTMiSkmXUk7HRTNA1Air9ZRSqohaK7JyW1hstZHb29f73d1hv0t5OO33t69fppzd2+3u5W++/s3hcBCDt6aqgJd6bK2aByzIabPeishsJ/NgZkSYG5GJ5HBVTaTiEavNKg95s75eDzc5Z8nD6uYqpWEaV/5gOBwhyqJV8hhEaCbiLO7uQAsfWVKLUBlzGszNSsspCwuxNDdNqpIQJCLDqMOwErlZlmVZFiLa7/c3NzfdOETEzLoBeYQw79/epqT9huzPGceRiCLCw5H0oycfTXmopW43m1qrmUXEsizMvNls7u7umDmHcU5ExHT+C4CeX8XdzFprEUFE4R6AM0FolIHBEOEkaBUAq6RxFIox56UUZs1J51MtxTbra2sgEma0QGsGEDO31lar1dJ/nLi0aq0BSKqe1d3cLee0uzswc7NaaxlX07iaNOXD7rBarSOCqXhZhtXKm63HcbefSdOYE0A5axoHmJ18Od6+LmU5zrvffPsbM3/74vt2OuUsu91da3Otc61VJTjMGlgopFmzIWU3Yws2mcZxUkeiAIBElABH2EojwgMeIPdoZkRLGiKiHuYZhOM7ugt75ZAQMwcxMRtJysM0Xa1Wq/V6RTpM64cPHz7JWYdhzCRDyqp53GwixG3OKamKkJya6zAGhXuL8KSJiC389vB2tAEHMCsABq1Xq5RStw8R6b68Hz8RLbUQsw7p7u5uzMM0TZLUI8IdHhQ0MLXW9qWaWVYVkWVZ9vt9RDDz/W3cbaMbpZkRgfs7IKL+vH7SF59EAFpr73b7LKpD9nCv9XA4jOsVi3ir725v+1sUWe93+1LL4XDYbrfjOEaEjhMzWynWTFVba4FoZrfv3tWlNGs6DKeINp9EJGU+nU6txTCMV9fX796+mfIgTjkPd7aLiIgQUTPLKRn7g5ubVp6Pqd3tXv3w7Fe3dy+WeTne7W6fvTwcj61VUA1v1pqqjKJNJazlQViawgdlifDsTCK8xkggMHNAiZgAAZEImII4SDzA8EQWLQACIS4hgBDN7HoYAI9AgMMbk7l7ODNzIIDqy+tlfjW/8kNpNYhZIpxZc15trzZXNw+3H33+8Oajh1fXacxBg4o6TJWY1QoRICreQkGSZDUM7nE6LhEh4/Du3bse6Hv0BzCOY2uttUbMp2Wu86l5EdWGOJ0Ovj87p+5Nm9mxLFZqq00D/dyXZWmtlVKOx2OtdZ7nw3waUxIRAN16AKhFBEJFmNhg9zECQARFkHsUq05Q1VUezOztq9eswqCU0sOHD929tTZOqzwMwRxEu/1BWDAvZr5ZryPieDzu9zvR9Pr5M/NKARbxXbRazdp2u5XCpdYxr1arlQgxo9aGxBauKkNKxg6px8PLFy/233z31evnL158+63Hab97VZYK96ysKiKYskEjHELKMgAsxAQexglZSZhIhUSYRAUQwgQiIfYozEpMjQSsIABE54tBhHA3BwjExSJADCIiakAAAQKFh5lFsyiBsOZkFd7cDYC5wThnBDkQ7k5MQaf5tFtOz5998xfCCh9rytfXN08ePxqnm48/+fH2auNBwUYcQeyFxjyIJ3JDs5ySgngcd/u9mzlie71V0de3b9artYgw8+OHj/yq50ltLiWx7He77WZbWxXVpMmssSgGWuYTeyul7Ha71lqttdYqItvtNqVEKpxzRDCRiPTUWYmJQP3DdFfUk4+IiACzbDbbQbV6m6bpar3pdpdSmqaptXZ9fT1N0+FwcPfNdlPMlmWpp1lV3XyzWW+vrt69e2fmRCBi98KCS97XFopafbUaiTgiWm055VKP4zgubV6tBxLTMV68/vr122c/++mf7V78ELF4FPFI1D0XhlE82CMAR2OhRHkSHnNOqkqkKhpBUDFJFszUP100IgI4GBFuDlaA4OQEooAHcPY0RBTnr3sS6ggwyCPgQUwgDg+AwSmInBQIzm1gB8j7jehBRu7FYzEzMw9YaydFhnumheBNT1SXu+/fvPv253Mxp6vVZri5efDws8+ffPYHjx89dWopXwFh1s6Za8B6Ep1zGrOo7A97STqMeZBBRHLO8zz3omS/3xORNRPVlDMzg2gYBjNXyUwk0QBckmOoSim1Z7dJlVR7pCI6W4sScWvNzcIDABETSIjtPrMWnqbVzWoIj/6Tw5BzzgBqbbvdXkRyHkpZylLymMlTPS3MEoGlVD3NF3fNqlqrg/zu7m6z2YikadKyVAvejGsEvStHj1htNytM33z1F199/dMfvvv23asXb16+8FiIYjVlEQQRgObmpIQ1heacVCRUTXXIWUjcwHG2gBIgonA0qyCcixMQEAAhmHocJ2VnBII8wnqm363HLxUNAGbh6HcYIQJIcHIOJweCe3QLI4CCa4sgJgKHCksLgyhhzMzEbN4Q7gEzQ1tKPSJ2mSiRRshqJLMZvty9evfy+Vd/9m/++XZ7/ejJ5z/+/b//5KNHKQ2SBCQtYpmLAMMwSMqHw205HsbV6t2bd0nSp59+amYppe4aRAREopKHQVV6StpqC0LAQSCS2qw2i+YeINKI0oN1BABhlmZtIDon0eERHgEKOl/TYGqBni/VWg9v98t0Wl+tcx4Od3c555yTCAeCme7uAGqlVDfLeRjHsZRyOh1X67Uw73a7Wk8RIaoIuHspRYRba8tp2a5vaikjZyutapvWA0m8evGbaqdf/PzPv/vLn5f9Gx0WVb6+SmYUYI8BJCoaSXKaVFbMShTOZAS4S8AaDAh3oZ6u9HB8divh0YuGVquZB6K2dl8JR4M7mpeAX65aENGHJSETJTnnjkTEnAECh2ZVZRFOmhBQVWUVEaJgJicHAIkI8mB3wD1IiJSYlaEyjtMa+JgtrFmttfkptTetuqQ2sTrc2tsX37395ps/H/LN40cff/Ll73/89PMHDx5SaZvNykUsMB9P62GAcYQ8f/W8F0m9quoZWauttormERGIVtqpLJxViVtrIMynuSKsNWut1lrKcjweal3mYlNehydi6agBAO2wgdXaL1ZEgAgEp+i3mZnVsuxuW87DmPMwDOYt51GUmYkF+/1dKQWARzudjilpHjSileokWMpJhL0aglqrqokYq9XqsDttBx7SmK+5eRUpX/3iF19/9R9++Ys/9zqH1avNsHmcwgdvCCRNSVOCbFiEIZTIxd3hAWJBhAYoFBA3s2bN7GSltVbbUkqxdsZLWmvmfsZC+oe9lBERATCzMAc+eNzDHP3Rwpv3ZBFEiJgB6v4buEAs4SDyoJ6FMLEmIqasaciDqmpKQx6GIUOJoqdb0mMjgqGSdMi0olh7xTzP5kemRZkyYR0mUW9/+MXX3/5lUPrk48+++PJvffnjv7252gorgchUZdodj8Mw9Fhxe3s7DEOtNbPkpELUSu2npqp5yDcPH9SlmDuLjKtyFSEe7bTM8/zu3VsgWss6VB0mggLS77ecs/aL0qskBwJgD4qz9+5XMqWckoxDBkhEhoFFkZICyDk3s2malmWJiJQ150REwzDc51I94XJ3cqw3Uy81l9Msaak2f/3Nr7/6yz97+/rF/vhOqW1Wo662blFsdnBKm/Vmy5RZKAIe4h7Ng+0MEJi3+Vi8tHp3bKUUeJ3n03JaOIEk3CMuNx8zURATX6rOS0ji/j57gL6kPe8f3Sbo4rQvTq3XqSAmAMH9mXwpQRgAR0SYtWaIUiQi3E4R4REdSRHlQYlVV9PqapzGcRyGgVSYYGZEBJoo8ZBG0ASYR7RSbF485jzyRzIg0t2Lb//98xe/+su/+Ox3f3x183DK69V1CirLcrh+ct3NtyN8zJxVa6nEASCldPmAzsIs0s2dAnNdEEgp1Vr7pVPNhhZBgfuLSecy/sNL2U8aPRlisFLKil6AeIgwEB7kwUSsLPDgAAtvVmt3t1obEREpCwsHwtz6azFTa8tufxARVaw3qz/+4//hlz//szdvXq/HcUr545uNkZsJ0aSZxyQsCjARucHdiNjEHDYXO9zeHvbHZVnmZS7z8elm/ff+1u/+7u//b7c3D0/7wy9++id//vOfHRb2RB4aARZmYvNC5Pce5b7e/P/z8Tc+/z/2n/36nu0ARB0ZYATg4QhO0b64mr74/PH6yU2r88vnr55/+83LY03j9Wa1Xq/Xw2oYpkGkuzelSEGhw2rI0aK0NrMd3LDdjiMAvPv+p//zv3v1VtP17/zkD370oy/H9aPt9eduZn5O4IiolMrMQeYRTHSOORFWmhAxkZmFG8xrKeQoZSllUdVaWmuNUxDO6fN7IPH+9rqA3+QW5BQeFm1ZFrZIOYPKNE1LaUaUScwWbpaEezXbXSURNVsA2Fwau6gEA5QSDeTRDFaDamN2Yf+zf/8nq3b3xZNHSKtAhAcFpzQMeQAiEG79TmWClcUOh7vX+/3t7e3xeCylMCWRRBwT4f/wT37yX/+f/3Ns/gvgIYB/an/yy//p//rf/rf/8qtXC4lQEBEH0NGuv9E4+nX40Bru7eyvf+s/9uP9i55j3X/dPZxHBXp2AApbKf2X/9kX/6f/6o/0d64x/BjY4+0vf/2/fPN/+e/+9Dc/7N+82TlBlVLG9fXV9fWD7Wo9aGKRCLgF0zCmkaYp3JpZtMZomzSOwxM/4td/8a9fPvvun/4f/5u7w61bI+dWvbeDamsEVLdwE4f0K+Jx++KVpoQIs7qUYmbH43FZFjPrfx8Ox9v9uyt9yPL+Arq7ftg0+e0rIuEyDdvrTx5MKa9vrjfbLSKAUAkRHod0eHurTBGmqt379WZWz9hnXx4+fLTarlkGCRWWaq3UOi9zSjnQPvnR7779+meUJpcMIgYogp3NLMKdpUFaqbu7t2/evLm9vT0eT0HExKKqMjGzCDOLhPyP/9Nffrc7/a/+wasnH3/Okg/v/uLXf/nrXV2CtAM07n/1+M/h6D9uEu/hsIiLhfyV579/zQ+z7B7xALgH8/2PdCtkgIK4YPn65Zt/85c/XM/7PErZnb7/5V/++b/79m6HnBQcDoTHfKz73Yvvvn0lItM0PXz44NHN9mq1JqIIRGNmSUos4aHmIPLh+u7p9uNPf/S/efzRH4LnCI9WV1OKsFKWlBIRltqM20qzCPfmRjNzM3MXVTEjotVq1VojIlUtpUSQU0s59Y8Xl7/1wxurh7DuoEoUIgjpuFpvptVqs2VRIpoSAdaTgmDSlFoLFjF3EWERa83dRVUxqoyKcUgjUz8PTzKOQ65urcX2+uHtuGkBgN3Ro6OEMaG29vru7vtXb+7evSun5YKVq7AwM53v5HB3ApzT7sT/y7/41Z/+8c9XScCy2NJqIp4U6hyXmvKvmdDZtfR/tg++oX/dtiLeu5nLRTMgupu5v4QAn3FFoFtP/2b/0bjUKbPrv/uzw5//+38TKxNVWdqpNvh1qBM8kBH9ILJCIuAe726Pr9/sfqO4Xg8PHz16/Ojxaj0i2DyIKelawxHRWuQsMq4RcGMCMwRAwDqIzMyYW9KBk4Y3EJEK/BzZ+52gqr0TEhGtNTMLQiLB+RzPISsizh7o3AKL+CAHAjGBwMLEdDrdrdZrTVqtqaQI9DyqWjNyURLOEHEhC3KiapUg7p4ytza7m4gEIudMDq+eV8OQN1ebh7v9axgTkqoWi8Pt3bMfXrx9d3tcFmdWFiG6z9r6bfzh6Tb0NNnAMttQHQFyBevAvc6KwN9kQOej/OA/7s3qrz+/P/k+j47wixkF0cW4/pqJ9qfd29/9QwIaRIzmyZaBCgIJaGC7BEIDjIgQQXBCUHBAiaXBX7zdPX9zl3/z3fXN9PTp048eP1bSWhvCHF5qevzgcw9UPw557E0rIrIqCIqIIE5pcDeDl1YRAY844xrW+5L9ce6QWnN3t2ZucnE89xdE7xthPZDdwwYMSiy3u8PbV683mxWxaUpJNaU0pDwMQ1YJM1FiJrPjuZsmPOShGyJR2+1vj6ddr5lV1d175s/CZaleQ8eV794e7+6m1fbly2e//vV3d++OALOIZlWhCIDDaWFJzHyBg4mYLudJFAYXEBwVHCBCJRYDOXA+Egp+DxxGnC0xeh3lAPrFBRKxgCxggAM4NzS6/3AHKCIu4FLPBgRgUDgqUIkY0X/V+0zoA6M6f+3dS7FxgIkD4XD3Gt7Bydbh8n4DhMNB3oMxgpTCY7Hy7Nnp++9erTfTjz59+unHH+Wcl9qQsg6DtbbMcy1m1pio1nq9vWLmUyle6jQM8DjOOyICs1vtsHtrrRetvRfWK4BallqXUtppOa7NPryduNNKPnTC53udKVpYs2HIoEBHC1JS1adPn6roOAwCrFcTKNxrSllVO0zescR2RufMrI3j2FkinWzUf1Ep9Xg8mlnKud7dPf/1r0+nIxGePPlIlFNiIiTtEcFBTaSnWe9hG2FhYSIWIPG5wyfKzNxPTeTsUTrg18+R3jthJhIg3Fs3pp4niQgTxTkMxb1n6k3UTqfplkCQ/o24f+FoH3q1+CBduAAHZwfWX+2MbhDQqTnnf16KI5CHW3M3bwEHBeID1+Dm0czmuX777Xfzcf/48eNhzFfbq9rK44dPHzx46I5pGs3szZs3H3/8NDx2x0Nt7ebqqs5lOCrIAlRO83I49ns73MytY9YiEuGtrdw5SR2G0DQEemNb+mdU/LYzP8OJHo4IDlJOSOTBoHBXlmkYe9cspX6iEM29giOi3nC5f50OP3T3c99lExEglmUpdQnHeli/ttduLaekokSmHEnAzKosLETCIiIKkLBQ/7cKEYQ5yIVAzAiIclKh3plA6ne2qLMQ+/kIeyQ1BBzaXS/SxZ5AHkQEpviAvRCXCERE1BtkBBC5BxEClSg4Ujh5uH8IIwUBYHh4kHAHoRH3KVTHxC/PDzH3cCdmhHuYEwBq1syaB4I03JpVb9QJFcW9mZVaw1bM8ebti6vrh1esJDkNK1Le5MmsZeFB5bDfM3MWTpK91WHMpWqziEBZmhmYSSVXXrw2V9aUCL1rGa32Jr/SBTA7BxkRvb9X7kMYnXMOIiEQRBOZAW7NiKhn5iEx5RQR87ykrJ0L131MtxVmdrf+a3LOH77+fQRVFbDUxYQkE3u4A0wkTMKsqqrKLEQgdu4+BqSiwr0CIxYGjLkHlRBhUJgZiIXUwoXFo1GQS4C9t1sBMBEExizMAoSHmSOImIGQc9CxgAN8Zj3AAojewwi4m0NwcVrOADOFU1xAl0uIdJhTcAgFA0YUv52L+yWydvsNZo8wjnCGhVFPb8OIKklwEJjp3Hsy6TgtMdiZRZOO45hyNndr7fZ0SwC5Hfb7VmvOiYj7AZnZvJyI3CyOx6MttTvTox+J2b3VWsK8mbkbCEtZ5tOs63JPFu2h/OyBeoras+kzzO8gSG3teHc7apIkOafldHr94iUnjYi7nPRct0OUe8LIzJ1MGBFMUry15qU0YYkI4nNXUlWJpFmQKEliRhI1eEMTpn6szEwIIrCAOFRBxPtDefXD9yllFmbGOd72UjnO+X7SRExE0b/ZWmEiUSUwCEzvk5qejQtLIMyau2tSVQ0PRLAogUornSqkkiICvbBqFh4Bv0RHJqZAIMAsdAGriZyZQE6MaOzmSkKBOBeRuNxMBArIEnEOguFwP0PtSzUED2NmJnfrN7aHB0L672QgvOPrBGcmYjnsD8fj0aqLyJTyen0VEYC0Volot7s7Ho/juAbCAzJMkkZidje2VGo9lghwjRYUKaVam7unnDpYI8wUAeH3Iez+mt7nfb0RyaJX282Ysg5JVQfRYRjSOAQRuxPi4cOHHa4nCWvGzMMw9AA5n+o0TSklJvIIVb2PlTnn27tbc4cHqzIzmMIRiCCwQBQdgSfqBXAQgZkMsT8eNNXuIUXkXKEhmNGbA3NpRETc+sF69PSoEfG58v/teonOvVJiJqJCRAEDdWgzEgt625F6tgsCWvTGNQEU4QDxmR56X6zdBz5CJABClc6f776/e87ovfuguKC47uZwD49GBGstqf7ul19GgEhEwsFhzowIsBAH4dKgUU5w3e1PP/ri6RdffDEfFzcfNKum1lqtZZ4Pw5BLnTfbbU6TsIKpWOv5Vi3LKsbdblfUZTj7ZVCklMysd/HOztPPYVjf01g/MCN04z/DGORu7h2zk3MCRaQ5hYcHmHgYBo9m7QwH9BSMWYZhtHCI8jlsAAFmdsBB42pdj+5mLImIiVxFRakTykRC5YwmEDNTMEcmH7I2j1qcBe4hosFwcg2ChTlUlJjhQRFEERQ4d6wuqV70C965gr3YAQjWAIKIUCdqRABo8F6mA0C0fu6WtKc6AkM4Efzi0MI9QBwMQgSYKehk7u4dgwYAxrn2DyIHW0QPogQKIncCcQDm5NHIsJ5S79cRwSyIgrnHDcQZberdIhFJc8M4pPCYjweARbojdE0AcSCpKHMSIXNzxJCmFOHRhMjCa1sCpgJPIi1ZQ0iwioiwBXG3b2MVCljzD2kJZxTxHu3o92UtlYOqW0SENmYu1tKQVbTT1ZKoR2MOM+uhMKXUWpvnBpAO2VGYGEDPy7wzdmsNkGiqpxNIu3/yINVQFebEHCxBRMJMEj3ryexJ2EGleJsXYlJlInKOYJeg5MzSDwgMIuIQB+KS3J9v/c6IutTov+WPehy4d05GYdx5iIJwkDMxt256ItG68fzWSwTI38OSjQIENgBn+MCIgkAICzKIBAJRqYa7BMGlM5LCHeSrfC4S6NzoJQdF/y0ARYhwhCO8c97G9Xa1WrXSbt++5swAbCluPk4TIua5jMNmmWuENzcDeL/3ujSbx2Eya8fTqZTiZixynGczb9bm3cFqXWpL22Dm/os5Ls3UnlTfZz/Rb8mzQ/alFHLirPMCIYxp9H7UgiHnZV5MWspChNPpNE2Tu5eyMIumVFqbW2URJiqldE6Zmamm0+k0z3PuqRiFirg5BXpmI9JLPWIWVhEiUSZQgMNBxBF2e3dIoqwQgoQHWiJBEBhEwkEszBzWwbMO9nB3R0EX+wDo3iOcT78jIaTec+BAeD94DycW6vU4AQFWeGe9Ehigi0tzRovojQsHFARCOxsQUcSZfNWC2jkhgkVzCwAtOAIePozp4fUGgV54RkeCGAJhJiZydyZq1YS5+9WU8jSt3FFqiQir1lpDRC9uRCTnqVabVhMLldp6LnY6NjK6upla9dV6XUoh5lILM19fX+8P++9/860Ap1JFtPMNmbing4oLhPhh/OoRjpmJeLVarQbhNBDR9YMHNzc3ZpWZN9Mqq9bWVHW9nmpbIvj66kpTEmEiNjCLtlp70tNRovuZAVHJabTlwKI5p1khHuzEHEzWyQXnbhdFInR770ime4gQgxM0ITJI4QZk4lGDxZk8gYNM1Fn8zEe8JDQdSLo4CHcqzD29AcBu7vC5yfEkCEZwOBtAGR5EjVlajqYOERrUmS48EAqPaB3Jp0QgUPWoZ/STE3oAoCgE62YbCA8ODtDs0YyKy4ndENUj4MoQIVXOytZ7tAEgGAQnciCIWawfmrDm1Eoj5tU0bdbbMjf3hbIGNaakkolhbEZBwplSVNeU3Eosp2Y1pSlnaa1RUqHY3lyvN5tiDcLKMqo2Zlxawp3V8T6x/Ss2dAlhQUCtlpiYeZntdCrjKOfK/BLy3OEmTDmlKc4kfe3sqvv6rtZ6fX3NzK3WViuDxnFdzY7zzIycxI2MXCRESRQiECHm0ICGM1RFAo3V2cDsiZHAK6/M1rPdUZOiETxJy/1OtwoMACiEwAxCOJETWiA6Xkwwigs/KKBMBhgjgc6Jm4Z5ULRmUEnKwRECEtg6L0yVSAgJIcEwDwuq3m9ScVSG03k2wzqEmEI63EOI8I5tu5AvBjKJIIezVQaLBkuAnSkEHASnsE6MCuczddvJYeJENeDLUqb1ZO611mZNhMybtRqqHqbEOfNhLmHORJIEFCLqHtYa3Jjj3N1qnsfBmUg4hCqiuJ+TOBAAFWHm87QiLtDffUQDwERmPh+PAsNch2EwR4uqgqS6GkYVAZBS6lyOeZ5fvz6PRYpIi+jkoz7CWGt9+/Yti3hrSnw8zeZ1GAdbhpkopaG1ICssZwxUOqjMwkwCEqLOYmOWRCRqoMgkWRrgxAEipZbIRJCYB4mOSLN3LMcBC7YgZ1LAiZqQABEcHYxxd2Iwc22WSIWi86cbwhVEzuTdryAIkUAkMgrx2RbdESER4eiYgTKIe5IVzZezg2tApLBgcEDhfKZowYPE2UGuHkQSpEqJJc5llpMzODzYPYI4EEHRhxKJiDTDIgZNKed5nl++fIELAd7MrMz9a3efT4VJQgJCAoqqc6m1NqsLkS9lOS5zlEZE5l5KWY6n0+k4l3bz5HNiMncSptaoTyvit8kul0KU3GMYhtXDR0qh4yrnrJI1E5OnlAZNZVk6/m3mOeebmwfuBiIRFtH97W3KKaU0jiMTYbXqOVAti5d6Oh1Ph0NerVLOechWZ1UFuairiIiKdBMXZVaSjkGrJhUJsKqzQwUSxMQiCEAZmUkTGDPDkpBIJDYi6tB6cyJSoEXUgEnvmzKhY6dEoEpETZwlWSE4+5nCH0ThGswhAmIVqKCFm1EATBSiTBHEkTgghZm8VXgCOxDSQyS5M8KlCZl7b4FFhAfMnUiFWUCJYW7GzEyirKoiygx2is76gvfcg5iExC2CIMxJlQhlKV7L6XTqtOXeD+jJQx9SFk4fffRU8xDESQRNWR8u5VgW1LYXlcPpqCJWG1pjIOecUpLTrKKX9Jg8IKD3Iax7oHsauZlVc5Lp6mZFVsZhyMM4jqtpUvPa58ryMmxWKwCqecjTtJqW5WRmUJrGMSKGnIfVNIxjFq2lgMi92ii11tN8l8LmQ9NBg8CqrC1LEjl7LBESPfMmg8g75XKow5DYUxFIEpIqjI5Mz5WMlLQ2NCYWJQ/2CiPrGbIIn4us6CxB6XkxuUYgmAxncKe5zpaCLKkTkQSLNfU4ch4oEUlFdUKiALOIWGsEqtECYIAcSkEkcAXAhPDwEIDMAnBwEVLR7ILiDc7WGDqgIZFrCIMXRrAz10SixMS91gIxwAS2aAFhWLi7gIS4jztaaWGmwnzh5/Qg0POTzWbT+5JElGXsgH+oeXjSqdXjuR7vwFcAgLJI0jIv5N12nEk54OGt1XMZf2ZAX6gd6LRLgLqZWwON3X8wczNvraWUm7ULMkQsblbMLBBJU6dzE8DMtdbE0mcljdwdIjoMWUWYU1mOAGnSIQa37r3OzS5JTDgjhf2hKqoa1p8Voj3NDCKjFscSxwZmIHSgCdQivJ6ZJM5CIyJ1199NivvHsXvkotdHzbVVWvFunBDuSjpIKJzc2Rdh20RpgxyqHo+SJbsZETlREDh6wmXmETSAgFD3CK8ARBJgAQuXCDGmGm4tRSNFY6kpu7uTqYSHiGiv+roFvWe1xXsGN84QHhErdyhuyKO1Mgzjh2fav+j8dADN2rIcPTylLAKPGhGg1okczMzg43zqxjQvc6d4XCLVGWgHoOeuGFHvc92nz/1/SquvX+/R5t1uv91ub2/fMTOxqbKmZHOB9ZSF3RuIjUJYEul+mu7u7lJK47KY2S5nESGCuy11abC3b98BlJJ4JFCkxABbG5hFlVhIBCwkIp1EFggRSUlyVqqaFTliIsoMJoQEJdSZl6UDALGHAwwISNDgIcIhbowg4g6BgqCCM6rB9P4CRSTwZqtrCVMDKjEHhVVLLpJdI9XwI+xwywcEABU0oAFMUKIEdncj9wjvWa8bIrMQxCksLOAU7CYOo3DoUCAULNGqEEhNWFWSCjRpSonDu0eJCAYkzsAbh4II5ATVJJvNhlVOtViplLX7ni698kGfH8ty3O9v7/swyzKDGkC1nDUVWmlEdDqdDLEsc2vtcJzz1voou/fuAZHeN1c/TJ/pwpoOj5RSHtTduxDEo0ePmElTYvbV1Zg0EREz5TTuDnsXJsDJDscyjhMR1Vr7iLW7p6QibBFGJJyPx5PqNAx5yENbgolIXVWJQ4TknEH3P9IhAJWSdEIgqaZMcq6ijRgDE6VYURlGpk746i7YiIAQjIk77EYstZk7gjgpZenkBAqc/fxsUU86DbwavSUOlrAWqKaSQ0ldTMltG7a69ikvIsFMxWKpAeqZAYmKW2GinCki5sVAhYU8tDSvzQAvFkY5LGr1nM49EGYhao5snFPSlDipctIIQwDuYIIZCBDy1sAAMUiRhjxNKlLdxmG4vrmmrG4OoNY6TdMwDN1HnGFb9z6qMM9zKSWlVWtNxDQlEgYrABeKQFfF6C2B3my5ILHQbij3vocuswTnr4W361WW6NONRPTo0aOuqTOMSeCC/oEp59wslrqsx4EIqso0dFigW32tNaXETKKpIcphHobpNB9yVqIsYoTwMBEQs0rqiRAuIayDaURZZABMVJR5EBrZWIiEzNyTV2BMzt6JRAbANLsTcU05ZxqEICItezFDRFIe0/0kL5sZKHKhpdB6jOGaBt4GpVar+0k0M1hUoxJbM7fi9WqjItUahpbUw2AgJ9KgRtzGxMNAtQa7iZgK1YbbBk8C4+QAiqiSa2YGgchoNHHyFguTSGYV0SyaPIAICiZhNAITOQfgbgQiSqxDkOz3ewfGKUvSZu8HI++n2fEBI6yPtqWUOusG6FMZTgAJO8KBbmm11SllSeroVWHvy5C+756+n8rA/e+IQG21nuZhHHs20z1KSolZBpVWFkC6jbtHEuX7rhOdaUC11nvHRsTobfFeYYJOx5M3F2ISUJBqEItKVj17nY4oAhDRcRz7a+akWXmSWPcSXzkCKKGmm4HCDKDOF7OgCNWEYcjC2jlp1V3CKJBTSoL+muHeWU1Mc6mLakpZiVbE2tiaKRdh5pQNaq210ooZxnGlqdVSW6WeirBaOIFJeJySa2oLW7tMoBowDZydHd4kNCoTFMoS55SGAQ6lcOWUs2pSHVVHQu48MqZgchertYWLk1mQqpKmpdbaas4DMZdSg9CTVADLsuScPIKJ3f08CejeqX+llP60s6qQeyfnxKW0aq1FC48g6ZXNeVRL7x3PfZ4V97YDtFp/ePs6kfWZty491E90GIdR2b26Y8gpaZrnJWet7dRfUNKKoAFXlUC429yqMHuAhOdy9GjEpHkojYVFWGtUUhLiXop1JFovJEMWJmVOQgFVyswTmWoQkwobh3Ez1SlxGihCHBFOxRXEOWvOKaVBRCMiuTUCOZJqPlPvIs6yNxThwidNU85b5sycKhubIYggObEMZmbzslOWnAZR7SQLNhdRVkRUUWZgSCsRTuRFLdAsKptPnMzIxDs2RRQVVRggam4kHk4B85RTypyS5FHSQGFkDrKIIAfMEhp1Tim7sBDrJGkcRiec5tNut7u6eWDmIpzTMM9Lh4tKmVurxOghpc+nrtfr1lrXYOin3Icx+j0/DisWtRYMJhCTIKQDoHpfw//W+Ddzz4dEdbPZrDKvV6vNdttxhQvOp8e7tzkPBqjINE6b9YaFms3dFk/FHz18SErDmDv5LqU0z3NrvtmsN6v0zc9+ZhEsKqqSKAKKUVSVWPmcPUuvB841mLDMmkb3mnRIyoOaJuFgYc2JXaXOaRjSKlNrXKpzGhKJuaWsOaVO9xHmxVpxE4iKDCpd0qvff2aWUk7KKQ05b3tvWNWp3ApL+DiOyhTW2jieailOwpI4URIjGAurKkVKqsJgGlWlmbFjLns0HgZujVXIwpqZAqo49RkMopHVwliNrZWMUCUVUVZN5MnJ2d3jnLsYda/ORI1IEMzdeFsbxjSNkzUnYjfpc6HL0qnGljILS29c5pzdfbvdHo/H7iO6AfVLXmt1g3AqZQlWpBznkYtz/1Tvexf8fowS90GNmfM0clS64Ms9lOZh2KzX82GnSRKL9sJbEzNYcgcsMrDebphhbtwJIDlHxDjKzc01fFmt17v9Hr1LLx2EY2FVFj1Hrk74ARH1eXLRvWo2Z9JBhdPIk2jX1ajUqEbKeRiGIYdHaCSVsVIMnAMkknJOvY8jIolZzmJBwpdSpX/wnJKIiKSkAzGGMWNu4kzEcM15EFClJSdpFhGKSEnJonjqzpKHPDBzOIZhm1OurVmdxZ05t2oibM0FmsIjmmayVs5umymHhnojF1HRQTsRSwZmdNtxN6NGHbdCo3u+S6i1OB530MGcOCXqYg5E4XSetA4A0VoTOUuKzfM8TdN+v+9p7rIs3Ql1AAmAeeucvqXsVVcfIs8dlsVf4VjdF3s9+YozAzr1H0spqapH7Hf7ZjZKPut1RRAhoidrqLU1R60t5e6tuAsWdSxrHMeeGY/jsBQPD8lJSeKCemlPoTWJgOCd9ZKSqDILQEzKKiopsiYRBIk0CAPOAhZ2MJ3Rs4CKdqGqc/BmjvAIT5wuEznnj9+1PplZU1JVTcoCFTZNauKQIFHJygRqwtqcRlIYS2QKVKsIIhZ49PwNUOKUko4sEdJaIWrukQdmZqvNvLEiZzJrzBKIQXKjmkkzT5lXKgmkzFnBTh7srRlCiYK0MlpDJRgzCGm2M27gjrnUQVlE3JuHXfLIIEJtS631dDr5Rdqwm0FvWQK4vb3tNtBaW5a5tdpafX37+kl+dD8qGRHSRePuq/f73PnepMqyvHn59mo1zPOiqinl9XpKKp0Z7mGlnoRFmARgTqpKbHkYzM1CXr16oSoBd7PaKhMJ8Wp9C8K7Ny/n0xJEAWcR4USdIc/CIhAGX+hkLETEIsSJOLHkYGeWzj5NOUlip8GPxMQRHi4WJOSe1CihVWJIUBK+ZOUMo3BSFg8PcgqiAHO0Gsdy9kNJtJsWkQiDRd1JhFlYRIMG4rGUI10POTNQW6QgEDuIg7hjStM4cFIiioN3GpfqaHAmZzfjtNTKRKockXJSUAhHmJAFxkSSwCmnSXRkBM4gUAtiuBMYrDC11lEtAVeCNjdQ5KTr9cpa8+AU0lojJoQ2a1KgSXtVT0TLspxOp+5++tF3tKkPOEfE6XgCYUgDCH0KIC4j22cPdA8C3afP3QOJSJfV7UhJa27WFLaephDuElcRoUJJ0Ip8+unnkmKulS7MjU6cGYbheDzOh2NSZSYHxrxCcGsmSsqZSJk4OEQVDAiFSIiEalzas9BEPDCPLYwgKknEkyYepEEQXku7PR1e7Wy1Gtc3WK3hcBgm0vAmvW4QqXVRTXWOUCO2kMXcqsVu8Rd3h3eHnSynp2uhB8HMhEAoIVRSq62DsE5MPBrS7a7ezc8f3WzXUyaFSYBUmGswU2PiIl0Eg4Yh7oMCRWWCZNnv6+ud3h7e2NKebq91SizmEeyaIkgZWVkSa2YVoFFQh+bdnJ0DDKNoaAF0upBErb6+vrnarrebFXOPVlRKTVk7XsOBPOQeSbqyoqr2TKgreNRaU05MXErp9enxeIygROlMCf/ASPQeQsQHXI57wJsvvfReBwmTaqI+JKvKIgT0aS13T1mvrq9Yot3dxmUmJqmKqHQxLJF+hnlIVmseBpvnpZxAllJ6Hz60F196PyRE9zRtAjG44+RCDFLmxEqtPbrOmykeXmE+tv3x9OJZOJWHV9ubq425BFFDzgJhrh6ttmqteVME8/hid/ju1Vuz44Mx/94a20dbTtfDNCbVzpwPOPqAZ0Qf/yCRIQ+fffrxYof58LwcIkRFN9O0zUIpFXdXUm/O42Buy1KYenBFlPHuWL99/vbt7qiZk6ZpNTC3YdxGGBFCKMKYmIE+PpC0n0iYeYfEvDMhz1eM+mAks6vyer0Ske48/Jw02Xq97qmIqM6nUz/oZVn6EF9PTty967lM46rjMj269TGHFsagPjDJF1XW9/IufV6NPkgIekIUHmatpw6l1lIShEqrDAIHsyOEScPRvLi3APcUrGNTWTRaa+HzPHtraZCyLNXaMs/dS7EzwphChCLAHMwXXSbmi2UzcyKSPnzOEWBW0UmdxqSaOJBWEtOQVCyW07EcD/Wuxovd62/3766vrq5ubkYMRAsRwmEII7fWnu3m2/1R1D9/Mn40rDVNMk7X08Zk8D6NcebSmxOzjtHI4tyNunmwefJ0E2H19Oj49vXRyt1yXA5H1zFvVqJE0JVuc55ObZE0lmVPkJdv33373dtwX4/Df/LJdLPR1UpI5mLaXGsZmKPFAihIiTNrIlFh7Ul0h/HNrE/mR3RP3xUKmcUErKLufjgcVutNwM3DPU7znFOuEaWUOs+lFNVUa+0yZObetRC7crk1mFktHcAT5lRLnVsbHeGXcbkI7+oc9wnQfRp0npGMMDNzi8C8HLrTO827IlK8jsNg+5kZOWeGeAMT//SnPyWi6jWljN4DDPTUo7QK97qUIHLC/vb2sD9IEgA5Z03pHA1V77U++NJGvhSAypQZGRJAIuKUkrAAENXDfp9VWZIg5+thtaarWh+tdreneLa7fXO4+/SRf/wkM4MTV8Pbw+nVq7cbpZ98vFqv8/U0rsZhdjXWwNLaHdIGqvAaHT8BRNVoZB0UEnDDqpwWiAyrR+Nqe13Ko+UwtzeHw+7u9sAYt9shNhJhzGQit3v59sUzL/PTK7qartab7WpMwqW0ZstI5sR85oiSO5NLdk7G2Tk5Z3EGBQncncm7kjDCER7couNDAIDD8YCwjz/9TMe1Atuc74PMfJoRqsh1WXJa5UxM1FoTkXmeW6uBuixLWWwcx1rNzRv54XQopR6XIyftrYX7yv08MHrp69I9nSMi3Czn/PD601Xu2ppTn8vIo3Sd8+Pt3Wa10aS11v3pJMybzaorvBDzfre7urqKiFLKsiyZZdpu15vNeSqzNQ/32tWUkzDTxYDuEYT+rpj5Xl4BAAkhQCQQ9PLbSQBqgdKWMNvSiBBSySltpmldY3Vd397Nb55/U07Tk6ePDPTd8zfLYfnx0+3TB6rjNORBWYwItWo5Wa1uvmzzRKkrj8EjJV0aDZI1qQ/qZnbaDxqSyHloPCrs0fS42JMpv7rZlHfv7u7e/rCexnH70CN/9atXr19+9/TBw8dPrlYDqyQiqYZlUXJyk91SZRVC7hzMY8TSZ++pA/pnLiCJKLOb1Yge8J26cFgIIkSEDH3Gu8PQRDxN56ZkRKymaWFezIl4mEYHUUTPVnvEMG/TNLV6NDMnuDCchmGd1YTHxX+rE+Lu75up94jih4W+ux8PR1TuEXTIQx7Yo1nzaieQ1XYMKEg6otX3aXSj6TERwD2ETUTnySnmIedxHPOQD/M+0Fik87LumSt8oUV3A7qHGJjYLtOfwgxJxolJDPrT3zzHuP7iUftoPW116vjUlPlmo0/Wy3ejfv/m+LNfPnO29YC/86NH16s0bCcVrdbcHa366fTqaN++bRXl745bFmvh2QVkbt5aDOP5nbDI892L3e2rpzcPN9ePx3ENwilc9Gq9uV6WN9eieXX77NWv39yVF69n1cPf/t1P1+v1alizt1pnVbZWTh7Pd/7tqx1h+f0vPhkSVyp0yUR7FkhEogJzv4zqf9j2Njgzd3pxygNnzavVXGbVpKrp4tr7qExrtSu+11atzzNfYk7EWQfH3SN8HNctUGo9LUf3Lrg5Q9b47cdfHSzkD1Tu+reO89EKSq0PiIR5KU4E1aQpzfVYrIgwQcKTB06nU8/Caq2llP1+3xu/XehqGIblcCzWxtWqmdVax9XqenNjtICmEONofT6OWIgEIUw972YCRZCLGLMTwMLODTQaCG4wRqzz+Po4/Gx3+A2/e3Jz9cWnjx5u1zEKRbvRKa/ztL797ru7caAfff54u7kaVxsAqLPZ/rDUr5+3v9iv/t1p9f1+918+jH88EFkVPzOnCYSl6mDsUmvNOYtM//f9p/Xl8pPh13/nJn/58Grz6Ao5hcuYtq4D/Orxo91XX725utp88snj7WarmpvVaA3gw1x/+cOrX73d7Q+YJP3+J0nURVJxgKN3clw1I3MISFnFzQJBjYkE7EAjCncPAacsrZ68iAyJ+fZ42t/eqY51Kc1smec+z9Xmubcpwv3u9h2AsizzPJuZiJa6iKCUUpZS6lyKLUs5zYd5Pi5zbV4ef/qTD7uTZwO6b4R1VODedLrl1lrJonM5hmHYbrc553Ekdx7HKxZTFTiFk7XWUSl3n+e5T/DcG2hEnE4nZgZRxyEjgsJUs92+jjaX7dPtZt3rVBFhVkRX0qAIIqYzIqmCvm/gg6wNaMRtu7LHN6tp/OTN8fa7N/sX/+HXXzx99KPPntxshoS4ntLNzWdXw7X78cF2Oww5SQTRbt7/8tnxX75K/xZPn/OD6qdojWgWrRcdFxChT//hoihFiInizebJdzz9srz+Z2+Pf/9N+tu3L37ydPfxdmu8Buvq+jEd0yef8mYzPXq0QUCE0oDd4fTV1y+/+u5YI336+JPP/ta6zW/baZ+pEA39I51v6XvaBEDUh637bIcT+b0WsQq9292Oh+cUwPpHt6WNOW83myHn7nuY6Pbubr1aIWdcUpR+4jmllFLvY+SmIM85L2lxd2HOKSHGssznCc/fHqI7tzL8IqdKHzz4wob85ONPYEtPTUTk5uZGVVerlYhcXW3NKxAqsl6tnj97NuWhWTvMc8LAzHmatttN71++evWy4w3nkVjVWutud8i5/YOffNbuvvlnX/3w8MEfcjhRMLlKZ53iHNTO06UgkDIziFm6/jsHHMGsQ9LMth3GhzfDp4+vXt8efvPi7ofXv/mj3/n0ycNBuOTQp0+37pu5WKtL1Pbrt+VffPP2X7+5fkOf1LzPfpdaa0TKmSUT0MUVupZ2XDo8CQqgCU/wVaIlXb3V638+Xf2c7fe++ul/On37xY8+v57WZjZM28++yEzSalNhN/rhh7s/+/lvDrM9efr0x19+/NFaU/Jvf/NmR0o0dZSA0GdqzxNr1Ofj+jQr02UslTnYzUiEnfavvv+7/+jz1erpf///+Xm+3kzTJoIEZO4qHV47JxBEZOHBffwXDuRV3p/2xDGOudl5WYqIAL6UubbCF1U4/kDDjjsf9j5g3Rfw9xGNLyN00zSJyLIs6/W69x07v2SeF03Sdfbu7u5aa8iDNXN3UQ0AhFKb+HnwN94veiFHNAqBRzltVp8//Ih/+uwHMqfePdQ+qyrnCqhvF7q4zT6YI2e5skte0DkxMlIKZs1Cnzy++fjJ41999+pPfv79R4+vvvzR1cOMgYKZxjQedm//7NvyPz5rz8rmSOOAF9ySBMGjkGTpQ+8gBqwRG6xpp9gSscJiSRJZeajO4YEcm+Ewrv+S27NXv/r7X736zz5tjz5ahUs0wJF02u/uvvn+2a+/e75+9OgP//ZnV0zDxDa2wVVlMD+am7AyC8iZL4rEZ74/EYKlc4YudD9Yh/Io8OnNzZc/+XJ/GIZhkzQzS7jXZWGRvovprFUVaK0GExEvrXRtpNqah0V47WIurQHoBI8O3/S0qd+999e6/633LufeKd1/u3c1Xr58uc5yfXNTSnn27NnV1VXf6jXPc0qiqbfxYLXOp5OVGhG1NXcPhXk5LQcmZtZ5KVwtWxA7EzdrLZrqkA0uu3fLy1JOlLJwJBYBM6iTFO/fobAoiJnCwigIQR7OYCJ4JxQwgFpPzEOv6taj/O4nj463r6stx4Uf3STvsoqtzDMOxu/mRKITh8d2iBLkLsEtCI1MAyRwowaYeetSvRHGiOomFBPzauTSlIdRhvVAsMS3N7//8vTs3d2bYRg3q4GZmsVS24tXb797+fLx0y9+/OUndd4vsJHGwZ3ZnBpAwtrxfwonDqZOz72ofiFAcJx3nZhZX6sVZqES7VSWJrxeSV1OeDef1lcbzWO0Nt/e9su3tEoBb24U9dSCAuxJU6s2pIGIS6nutixLrXVZljNNKmKaRoDmau5OHyQPEfFbOtH37Ov7JJpZemndqSG9FgOQc2bi5y++H8bETCoppzTkc28lpwSi2eo0baZpUlVrtN0KM5kVkAF0OOxT1mpljXH72SerB7L62a9dwMzk4J7jENNlM8oZib4XJyBCJ6dRlz6gnHPEic8bdHrAxtLq17/5+uH1+OjxzcObB1Y9yFU1SNarB3/v83fB9f/xDRWZRltaAOF8kVVEY+8zfB6gYOIgiYhwixYuXUQDmkXGQcf1uF57o7tx/rQ+/yefyqNhwxjrUtKQUuLFl08+fRJiz5+/nPfbpH0wj0ABMvMW0W8OJkR/8/eb3ZhZmBF+nqCmcwrYlYJCqFHkB4+Ghz9pp2vzvzjOO12laT0N00hE03pFRCC4uYDcrLS21LLZbs0t5Qxzal2ragFqKeXly5fMPE1TL5/NUkrDaAOLXBRFvBf/7wWmzrnhByBjz7/GBw8GiZyHPuHVE6D1ek0cu8NqvZ5AUBYEmEiR+xYqFklYf/TkqYiknMM7eBOt1VJPQfHo0aPNantYjtFaAdFySFbHSAqTCwnonLUROd5Ps3frAIHIzzO2Ed2pI4KJkmrXIGTFDz/8kKU9ePjo4dX1mKM1ev3iLak8ePxRJB7TzR99fvj2cPjjl6+DQZRxXhbmHBTewi9zow7V1OkG0XcTOAfFMGgK5pTTME55qpgfpfa/u3n1n0zhw3WbmUP2d++GaVPNRePpo6tYXj//9ttPvvhckjisU4zjrPVCxCC6v0NAlxwIRBRnTYUu88BEYHQdEQ54PcViHKbZr8erBrRm52qRuc+NwKPUIiJ5yPvjoVZjSd7IDZkzWvFGjmbWiKjP1XRDIaJlKaWUNF0kE/rell6FfZhB30+HnfuxrWk643udg6GqoDgcdo5W62ItjzmrJjOTntue17AB0cpyzGkcczosx3P1R0iiLJiDNQTNVHUzfjZerTer16mTtJmZBcx+SX1IiAJ+KYmE9TKLB1iIpr7IS4XYWxIXIffY3x1P+9ubxzd5sxrHNaju590/+9X3K0n/+cPN8PgBzWPO9k++LD99fdw3IZ3DlZnZq4ABIwRFIjIiAxJRu+CZLMRKshmi8tA452k1DCt4+x3f/aOpba4fsd7Ust8t8198/cPvffzgk88+MYDHVOsnh+N3L16++PSzL8gXb5SyqCpwAllPlu3C7bvHfAkEYoqzjkMH06id81lHjNM1Dw+4yrRZHYu3WnpPCXHmAeWUain9ZFtZlmXJ+RRxJNBclqzJayt1qfXYS+mOG3U8r5SyzMtSlzWdTaUXVehjPfSBOBBdyED9GE+1vnv9bjXIsszjOHVWRR445xQep9OsxG1eWJhEEBHmnfJHRIZG5Il13o+GqK31/QruliW9+P4ZzKlrk9Ysda2d00LnxsVf1YES7qk34l4IjN3MAyIECrfGiMQuYRLkzd88e/3o4cpYWnj1Frb87IcX//zlaiR88YvXf/sPtpyWCnmySf/F76X/7k8PlAfwEkFmztSRp4jgoD6xk8K7QB31ZDJaTIk951PoarOmadjUw9/dvBywJdk0dx1Wf/6r7/5vXy3/+/Lq4dZ186mTar5+8NHd99+9Kaenes3agbfw6POykbzf45cWMs7pap/S7p3dCGIKgoO8j87a/vh6v/9mkmv3Uj2KmyMiorXaanX312/Oo83RN7pEHPc7ITQ3R+xuT3y21/PC2r6rsDOj7+7uRDIFdf2QD437vdC4Xx5xeTAzImqrhQzAfFqmaT1MGkuY25CGq+02nwe+zuLAw2piZgEJc0qbWquF7w4HNKulpJR1zIYgx2meS2vUp0KYGAw3YjkLV+DixHFWtCTvcneiJA0OkBv3eYSOmQsj4F1qjjmfTseUY5wG1mvWvDvtd8fdv/q17fF4x/v/1zdvPrrafvKjFcVwteJ//Dv6Z18ff/a2clcbqo0gROQeDiNCBLF03T8jyYRQo6CAMwqt1usnN49C2x/as4/L7qgPyrvj8dTe7Pb/75++fIlH/+ybd19cvfvi41F03GxGksfL4fD2xQ8ff/KZhcPvKV0R7ObW9VHOIbyrc+I9whIeHACoF6jBxB7eZNIFcnzx6q0M66vt9mq7XY9rXNrk9kHLgdyzZGUO80Rwt6i2Wo8940kpLcvczGprpdZlngEM4wBvZ1zqAwY938evD7+4v/mJKKc8jmPOmZhENanmnHPKOadhGPiihplyDsRZRTqdrarj6Em1K9SJSgBDHsdxSEmaNU3KImT7Mr8wb3070IeF4UWU/r5I7Alun9phdwl8WBacB2qt4e3bt6uNJt2sUtYgjvKnP9z94u5Gc5lQ//I2/viHF81iQxHBq0H/0y9EaKEg8bOW2lknGt4r2LLUeZ67BnCHFcPdawmrq5yuN1ef+PGL+BXrtSYBhMP/1dcvv23jhuuLuPoffmXzYSeKlHG1vnpwtTW7PewPiCDH+SbqqedZnhUAAhznj/9b7vj+dIiZCKAJddi/en5691I0T9OGmfuGKwAsZ02F9/DxWcCU+6inu52r9MsvaeZhAXM938bkAdb0IdDT38B79V1c+iB4L2p8JlJ0RMTMzJqHIIi7chnLOAx0EezsQAHc2yWjOns5USiX6kOWlCYCL8sJ1OZ6THlaqtXDfxB8/fZUHrNlll52XZo+ncLRx9uJggEOqMdAAhNjZgR6htQRSyLaH98RL8OwnsZ1WFsqdqfTv341LKuUw4zXjcZ/86t3f+fTux//6MaVIen3n05f/mr+eonE7EYQIlSQB2oEu3ME55wjHFHDuIYJY+VWqIwpptw+fvNrXtinq4TW6PTs9uWfvvCmKyEf2X/6Tv7s27f/aLuOQcxidf1ofHP75tnrm/WPIpzdk1MCR0AC0nWoiBtWzgArs0RchvWY/ayNjqBwokr2rrayK9eZOOWQFIjd3S4CZ1XdiON8Orf87jdctSrdZ0csy+xurdVOHpqLsTmaUwDOpdHp7s6CP7qJLmNyn1y/T6Ljt3dB9C+ttWfPnm2mNE0TMwNiVpIid8H5/X6z2aSknXXm7vv9PoHPcGcP2O6qGkxlKUc+EFcOEmm1VQDejGKM1STDE5IcIRdUEPgbb7oPHj1VP2MkwQE2qxEjM+92+/V6Mw5bUSvVBPwnb6rVvJXqjgjoyC935V//6vnHHz26ulYT3j64+gdfzodvASJpQ0p06S2eKVSiSlBi8nCO851GzJusG5XHbfd0//XI2WREO7Ry+hdfzw06oniQMk5Cf/zd8ne/fHO1eox8yp6vNo/evH5ZShmnzBcPQUk9EPDzp7+s/esSn3/zhYgAfMojt03Zp1La4u9as+3Vdc55GIc+nDqOY79owzCUUt7d3k7DSohyzqr6+BEvyzLPc6A0M+wO22njgWa2WZbtciqtHk6FfzsvJboMFjKLe3icW1cdnY4ITfr4yeNRabVaDcPQ6a2D4Gq7PZ6OwzA8ePCAiFhFcuqbeGsp5XgCcLvfT9PUdVaVOKmS8FJdiMdMu93bNCahVKw+//pbO7604wMiGKBd0QtdqsDBjGAiDw/ui12ZevV7v7uJSFo5mhWA53luZpNiGMYI99Dd4c3P78h1lFp6kZynlB7/wXft7tkPr65vrqgN46B/8On4A66OiGZpGu+ib98DqlsLDAoKMQRfVqy6RSadBlmllG6/obLH6qFE4Vi+fjv/5i00JbZWmzHT9TjuMH31av5oek1XaxHZbLdv376+vbtdb550UdhL1ozubBACKgjxqED0VgTOQwB0kUmFwZiCgn75y19+/HSbFa6ZqKWUuhYHM59Op05+F5Fpml68eDFN09XqapVXKaXa6rIs6/VqGuv++DojSjOXRJwyUYnbKPOQ8jJXuhAB7kGf82jzudkQDKSer4nArNG5LXKWWTnPwAKzBWTgPDnnIWdNiYiGPBCktWpMdBnE6fq3Fr7ZrEot4gSLZVncA6HXN0/c569+cbpeP7r++ElpNmpqLNSFD8EUJC4IATMRGsGFvJ1Zld2S+l3YGZ9MfDjeBR1Vrzt6Uc2+3c3H08Mp5sZEFiGgYfjid7/g1l4ffyp8A8BpeDDxH30+PvNxabSeZ69zjBBqGYTIEnt24yZJFYRAC7ErZhPZSrne/Uolg7PXxerys+fHJSRTM/IQAdHmerW+Wf2adj9ZXj+MlIZEm9Vqmu5ubx8/ue495j6mA6rWakS6fDImZHOGSEjfzRBghDu89GOrrT755ItS73726javr+A4hitzAtfjTKnzidntPJBqZkxkaHfL3YhBVCK5ISwaQpjFY5eYBYYIRoiI1dolmuJC2eg8C22tdWgHOJ8G91IoBGBz71t5z/hBa72b38wJMPPOXr0ehpxza7Ysy2qdD4faWtvtdmZ2fX0NwMzv9ruIkCBFJspLOSKCoETqnmqsXFumgSAexAGKAHV51DivzCXud55TOILBbkEaeL90ggN8mueUZZpyhBGp0fzDHdQtuq4pBwjsTNY46Y6H49Km1Ziaq+p1xC309GbfBeQchOg4C6gLg7sTsQdz1CAds1flXO9kvlVWGHuLu2N9/vqQhgcZzS1EolLkMV1dr4rh1e7Vg8fGlKA8TNPdu11rLcIdZhZD+JAFQMwEnDtfTlSBfE5gifhS5QMAlBgkDSWg1cdOc/VSj7v982fPAGhOi7WIWOZZU0op9YGeWksEdgQz7/QgJq5zMbdSyg4nWGulLm63u7tWFnN+Om3pA3qFmZ09ULjTJQWi92xAdvfTfGqzpfmUUn748CGAnHOfBBaRw+EQEYfDoXu2nNPbd36fo3RZOwCl1VLKOI5jyokGYgp3d6u1qnYNZ6cIQudrIrxn6v0i9Xbph5NrfVeD9XY9LjX/Pc1qHMe+0pWBea4vbT2kZE5MLeAMcDN/96ZM4xuS/eG42myFWVSH/TsdptPxVKnwVsy9eoVEa8FmxOcJFvMQZglOgHsbjm+HOIlel2rW7M3+9G4OHZxZUE2jqoq6WzPW/Po0/c7+ND1aE/k4jndALeUC5LKKgl2VOuDUO6nnLiiAiyq0u7s5fbiXAyAER9zd3XromDTn3Kl8Yd5aI+anH3+M85oA6gc0z3P35c+fP5/GiUA3V9cdOTQzmB/3eyzzUIbVOH64Rq3XW9pfy93Pwr7xHozundRhGD799FOJyixm9nu/93s3Nzf300M9oolIsxre7na71SpzAEzMvB1XEUHCHmHhu91ue3Ul0YUEeL2+ScPuzd2rnOThZhxIGRQRDS5nQXimUAABNqEAnFC5a82FgMhj0MusBCEYHlFL0fAsGgAzvNXXhXy6TlG5mJCHBBOYl0EiKR193B9vH9fm4TpOA81pOUGCIUEkFIRojQKNhWoxHQBqcsYLQlGNS/aDu8gwmjnCnu9a1axUEOAUvSxPUTWcJB2G69KO7k6MlBNDT4eFuyq2cIkIcxYwW8ADYn2DVWckfVBCB+CkRhRhF1WjACc33Dy4yqrDOFLSHlYShVnNWd3Rk2h3703x0+k0jmNvM6ymqffeASzLklRbyckt5xxuDmKRe6znbNAXb9H1p87EoHsf1dkUfVN2B7Y7QBmXBmdKqWMRtRXzWmvpG4cBWGuIaM1aa8fj8dLxQQfKiKSvCAhENQ/w5Rp0UUKKgHt0GgIxByEI5uJ+oQfBmSqRE3EXSbTwUyvBIeCUUi8HjrHdjDwOtlrJMLImZw3NnhJtEmsed03r6chMrDoIcT2lpDkPxEQIYUaQe+tXRVWIIedtfCTKg7CXyjwEMVMTpreHOg0ysGe2rJETjcoj+0A+ojXJu7nUUvrQpKrWekqJAG5upTZz6xfAw5q7n3X03xfI7w8IFKBG1JhMxJQhmvPYVySXWqq15mYRRFRKWZa51lJKpTM6E31+ISKWZck5g7m2Vls7V23RBYn8dDoRc3P7cIUeADM7MxJZBGA36it27t1URNRWBRHufTb59vZ2nueI6IbcUc7NZsXMrVl4zKcZRN5aEm2t+Xn3FoC+whnC0lp1C+4LE5lVMkg8zmhzgM+rdSiI4IgIP2OvXXevN164q+MmYGbWWr15MiIKDhYRqrU0r9c31x/5zbssY07H3f7u7s6apYSsdUilRRSL+XTSaVTmLBBbEgS9Jx5nTXKWfnH8DFCdqQKRyAmIVsbtlFlqq8d2t19Ccd5GAARTCHnSyOKqNFlqtbXWkg6siXJefG5WHAQ4iTaz+9krZkb0dQ1kXSKa7uHUC/DL5yeA+2JhWkrZHfYQ5px6rCAIIb17dwg3CyfgXve9qyl08ka3pFrr6XhU0VYbIg6nYwB3t7fHUx1XNx9iiWcciIj4rJyP+6kMAN2bvXn5chSsN2uAvv/++z6P0b1ca22cJmG+vXsrClWdl1kuNrqrVVUhDCIW7rxJJhKiJHo8nE6HI4iG1SSSAA7A+z3lIEYg+LzUBh594WCP9NRz6qSJuXc3C4jdYpntuOw/fjgQT32rNeCffvHZavzkzdtXm2F69+rNV199ddgflNrAdaLWiHxpRGOzlogHgi+1+XFxtEmTRLBfdOWVqHlEn+4zQqtBGwMOWE4jb5SZIpaYZ7NEoEuGIlmYZUiaWQbRgTxp8mbOrklJ8qtXJ4ghxIP6+EAppbUPkLnz2qizJ4r47c3THzYPCPPpBJE8jZ99/vmTpx/1kXvhsR9rbaeO0vzwww9XV1eds0FEXVNhGIb9fn93d3cn2llHrbW8GretnQ6H1dT6Nb1kY3zGgZg54sK16UT/C5dZVR8+fHi9Htebq2EYxiGP49j92PFwSInX68GaD2MW4fNoaZAyt9aY+fr6ei6lfzDpE/Xu4THknIcsOed0WWRJIJCdE+YAIPxewZCC42JMnVTlwPla16pJmRjEq8325sHIdrQWdTEDmlmaVh89uFkrhiHlmF8/V1siwtR8ghtF6plUMCEtsn2ob2/UybyCBIZehp6rPIiciTpeWwtd3Z1iP7daC8HmpYUvzQKe5bxakckJThTiLYXnACVuhaMLKLqzyGa7yfnB3d2BWYmiVg93kUwkHRADnQtIRFCQMrmfh6zvwxku1c/NgweSUrUm2ucPOZy6mHDHVgAvpeacx3G8nyY9z2zUSh753OZgTSncVbTD2SxCIDd3dmaJYGY5a+WZnRdg3DehLryO3lUV5mxG962ZWouoSBizOznCCWzNABBzXEi1vcyjy4wOADcLjujqGIhxtUrMktS7lHbvpzD3rneEqzD18gLuFh1uc0IQAmHNSAUhRPTk409A+Wq1qsed1TlpWgq15tSWdSpXj69qO5WNj0MVWiJYrGiIkBkWkoFE0Pzq5kZkSkmB2B8OEdYjJl1YVF28PGdF8ONHj3Ne5ayBR+anaotHtOpJOcIC8HCNBsDNFSnxLPBecVI4LFqrDx4+VmF3324eg2aLU9cfJihB49y/IQ9SUjAxOmr3gbLsuXmPD65ziEhvpItIztraIpLc3K10jZSylLu7O1UtS9Gk6/XazPb7fTstZrYcT+M4WuOllMPxsJRyOuznxW/GTcJ5soAgFB9UYe8rNLwPHL1cLLXgeEwpsZC5WS3ElJOUWlQ1gtzc0LovaWadz1JbS11wjy682ktDmIg6S7cP1b9nKdxzEfuOkzNAG9y5ke9rkJ5bAADJmVM/DDlP20Fz1JNQJgbgrGzz3XH3Yry6GZKxn5Rm5QXBygud23/FfGY2FYURiJImC2PuW3PAcCEGPJpzJ9M6gZQ1uohRkJixn7cykkhEO/agw315bxjFlLBQVAYDzdyLldYMiTQPfT1YqTN6f0bkfgv5PVTacQoCoq/vJO2tSu9Da26EYOKllP1hD+accz3v8vI+D9b3lRFAzLXW291d3Muw1JqSWmviXGudT4fTKbeI4+F4mE+H05HCA3QVH13sJLpPUj+/xLn1012hEwwewm729u2b5ZRS2ueUNtuVqCahrOmIPmZwoDM1N1JK42rVMYtSiwHF2oXakfrCGFzm5dzMa7t9+66vyzy3i3u51d01GOAIcSYgEGcyZc+iQR4wFoBCuHHo6XgiZo1lLhZWnRurGLjt3saKD3JcDxOXA9qJYm7VEGO0Jh4SlW3NZkTqZi2shIWbFzvUemSqBizzwwwCXh0opoHmw0pMlGgKTWmeFwjrlMpyFJDacanH82UBEE0IHFVsFiKGdGdKjKAcUalKp/VYCxFKClCW4L4Kg3vcZ3rf6hb52V/86a9//XNrANWc13/3f/0PhaWPr8215HHcbrdPnz5dbzfn8iXi2fPvxnHgSD1KdJFDO1ffsdvtwkPHqVtGO43ufjzOabNNORH5erNO4wqc6LK1GIC73TdT3b1nFWEEY/ilD/rRR08TmxCb2fVmxdzhtNbPudeB5t68TeOw2WwowMDxeNwdD2kcBbQaR1Hd7XZ9GKgbQVftnOcZF30ZAAhGCEIREt6vHgfYiLzDwed3TwSKDlN7VXPA3r16+9NffH3w9PBq+r1PtnCQC0LL6Y3tlmu9ybr15Q51qcdbFkLNUpMgRojGEM2blcO8fPvs+xMgFR+tr19W8JOPKfDmzbsHWwa1Z7eVx5vTjE/s1c3k/+6bX7Hl9aB/8IdfEitr5mhcdoK+vx4UYHAgyE5hIpXFOVoj2qQ8tIVvj6dfPv9WyNDazfW03kbP5yKCAtJVUjsQz+zWIoKE3rz7Yf/qZ0ZTabNB/94/+IdByciC2jStUlLR80L3XmepJpWBKatqR+M7/deba69xLN69e3f94Ia1A/rhHiy8tJKE1jlZsXE1But9J87d0VcdAABFSoO16MKuRMRMdta9C2s2rAYwNyN4I/IuFUHmdD7UmE/zer2uteplcZK5u/s0TmbmEb1WXK1WRNRlsEopItJHss+uhd3d2cPJ7wHx3su4fKpuagwwnDycBWSpiAfXSSoTR5nD1qR9ZbOU47HZ7okWH44ac9QTGYgCfnJrQEO6Iabm3CqWxYjKlJ3SyBEiSTQDflEgJIC2qxWZ1bev0jT+269+OUD+wY9/t54aSbgXYYGIuQtTdDSCQSCrS7QclR0C5pS0sqGCVF7v78zn7H51ndij1dZgHgqCUS+8HOg7ic8BPHNaTSvjzbDosc+jdEAVwiS9s3M8HTdX21Krm5VS+vhpR2uzaO89gGDuhlisUVJzs6W6tWUphLQ0m2uxspyOy3Epd6f6+OkXeTiDtz3r6nZK0dHxuKQ/l0dPrK5WudR2d3dnhvV6EI4QTix9TSs5959ptYHQzvhhE+Za69G9w2V9urkPPveIJnIe+4rAh/KMf+1xxjzutVQv1ViPaB1nqnmKj5XXos+O1OtHMyOQRnv7+sW8act4KoeDnfZRvNWy7DA6ISo97GAKPMJRwbaUuzFHxAqRcM4Z4R6wVmvZHw+37bSKUODOlzrPfx+fL6d9SAaQ86Aithw59WBBgDczmms7UQ7xxnm6SSmd3B3kaE9usBZ6eTuEw82pL4L67UenvZ4vh0dZSgTMHASz99sRCZjnuZZjNWfmPAxm5uYgTONUau1X3sxOx2NfPw/uu/gwTSvrtlOWUus0KjGllDiCVoCk3al2Xen+i0SV6bLuiYkKhQlZj2E4Ewt6mecepdTrmwdJ1YMpkCQbgGhsTUUGTeODh+5+2B96w5OZo1nSdD/OOAzDRUQ3uhafu7vbbn+73d6cKaRdQZb6tseuTdR65sQ9RQ0msFugOsGTEypKKrBhYGnsbUhcq593KBEIvvj87d13u+P8+MGrN/vvv719sY9BiE4Www5qv/P4EwyJlSFe2zIf97bMw80Dz2x1ZnKnemZbUEtZaiyjOQtZnOrJ9ne8P53cT6pCZsYyur15vmeWAKlaGNxjtdLJ7zi1lMb0449IkhYc6dRK0bApKiO1UPbm7CoidqZCd9/cE8eziHM4i/AwZSg1m1s4q3TqS6CZsepmyh999PTm5vH9Nm0zMPN6Pd3d3ZVSGl4+XI8KKVZPy1JrHYYhIuZ5SLXS8bC5uo7zb6dWUU5lvN1RXJiNRJ0bpOcTdWMZrE8DXKw/ENM0/c4Xn9XTfl7qarVS1fV6TXAROZ6O0U5jSiIpD0MLzzn3CSYlBtBa22zOSZxcZNI7yCTnbYQyjkNtBR3fDVxIrPQBdn+un4Fg0c75/PC+JOfzvu3OOWdmQm0WIT0DGCQdoz3bCXx/mOd3+/lYkgmGJIPrFmm1WnFHHERsfzfWuS5HOR5YngAFVP4Ks201jaWFn7wS0ZKW+fT67hjEKWmzs4roqX3PqGrNIltEIFbmC4en9ujh9TCtiTncRLkea9IkvBAbYKLRLhjPf+wRAcrTZ7/z43/5//3XP/nyC07mcV4Fd2nKEjP1EWF373K+vQp+9+5dl4qvrboPrH0H2ntISYQjNHVSsjCAVs2sifA4CQRxCVO9e6/u7mbBaN7M3g/09HPr+crd3U7HtYFVBcoKqbVYa0NXlDEzMzCdlfAiQNT1VvtLyWXTRbekc0fMrNtC/x8zIwJYI5xS3EuB0mVTQgSYqFOROyOTAPdQIiLuVkXEosIsdamnY12vN8ycU3rw+R/dpU3JXI4HqbdyuxDmuLpumYcrH4ZBBNHC7PAyVq/Gvxf5oDiN5AZRD6Ke0IHcKDwMjaxpEMai23mafthFmet6DYhqxCdXm0c3D+58k6IC1HVZfLtdrpKk8ujhdRKCh7lxRmmyWnE91h5uRSI8yCFufauch7nTPX5BIEnD3enwx//2jw9vT39x+Pm03f5RUGmNwlsnrUazoP3ublptmXm320VUFvbqZfHWGuAB7PaHIx+bWUeM5nlmoqxK5rWW169f53Fw9+PxVEqZj8fa/Mmnv3Omw3ZD6q0MFvFuh/y+RAuAmL36s2fPvJwmd1hpS14Ox2kchiHPy+w1hJDzWFttF55sdPQ/YlkWfCC3eG9DAHokbme43mtrybwrLfbFpKrKkohSD20qvYiliGDiM3RGphIgCzSP8CgIU6NB+bTs3bdmzsyKfPRPf1p+7xtevZ1f/1C+q/VOsX95eqB1/fHjQxZmyqSYD3e/Onz0r8qXeTn80wc/f6SBSswKiEATIoKhuTRyZw92xOvy+E27+sXb29e39dGNK7GDVuvVST79TVkP71uPkZYhlQcPyv7v/agJIyKEiEXL3enxYz2GS+CDMWEjcgKHC4kCet/2DqA1+4f/8B//4R/8oVVEm1swGjhaeHhpy7yweIB6T3S/33dc5e7uNqXcS3glGVnBWOrSWWZdemW1WkewmT9IU6ldF+ZIoGWZ3717m4eVWesocH8zjaE9oAiLRdcCvOQ/ABGdTqf5cBgTwtvbN7vt9mocRu8Tj5qGgdN5RTfdjwUREVhSTl2qLC70x84H8guuKCIdSjeLu7t3Zd4zQYf1tLlhUSUwC5MCFA5ido8wB4RI3YshiKKisbUEpQ4VhSNiTOlwPGjS6H38kT8qr//kzcdFttUCrbR2atEwzw9W8xePkPMjJg23N8fDi+XLAWpiITAKdTKX8ExOHG2xukT95utvboa0lTC3YoYoL4v+7MXhR09nHUZR3YzDx1ebn96elt4BjrM+pvPdenu6HjYcGmBmzKdjRgyajuj4ZHReVLA5uu4qd/3abkDuHW2JMW/yw7WZtVZLqbu7u3I6RvhSqw6y3W5zHm8ePnzw4ME4jqUUUa+1iGhSJaLMCofBUk73KPZqvc451wbx8GaacqnFzAO4unlwvLuFcJwnrrqNB8LPMr+qfZXhuZy+B2Zyzom3iW27vVJN5/keopxzTqoaLCSsIkKtdeWi+65F11j/cIFLzrnP2HtfL3p53N3ell0C4LL//xX2Zj+yZOl92LeccyIit6q6VXfr29M9PeRwKJKgKIGSLfDJL4af/Kw/0y+GDfjB8ibBFkyKAjUgZ8iZbvZ211pziTjnW/TwReatbtJyotGou1VlRpz41t9SlodPPv206z8evlMl5Ee2XezOYN5yGniMr8kdzS2XPnGurfVdp6ap+PnwcIlvbw6XXlttzQxdSGj83Sd4VlaLfgGE1uzXd/13+nzS12qjibs6qLx5+1A1raFN1iJJ5K5zF1BTA1Ag18nol+/tX+72m8SElAj/yXP6919v99oTojuZuaoN9eZ3r9bozqVvtfV9/+b1vhuQE2TuzUEDjYAoburHsbu7WTg2B1PXAMzURMVUReS77765vb0DNHMl5NWqn3GMqtvtDsDNNKY3KaXAkBChmaaUxAwBamtTnRarpaiCMxM5GROTUtd15n6/GxEcOOxbj9obCAiQAt0nYkCBE5hvFZ46ZzA4apgvl8tTnnKE8A+YEW4KDo6MAKDmgAbcGQAQuof4KioC5SQigFDNkMnMKKUGZU8JkTJa3R7u7x82m/VpRxivABvMhdEpmitCimDp4OSg5pYRhqHbbu8vnlwUz66lJf29s4d/8/ChqapoPewRYbHkP3pZlqkYM5jd3X749fWTd9PODluwpucGIGOzB5sOY6U6KmZ32m7vdLl4ODxM3STSITEC5H74Zmzfv785OxsMu0Uun1+MP39x/uffVGMFFXAXx09W+MVlQUBGUqLqcn27e3G5BFf3DCDmDSHUJDQGiYBgENBQCD4uzHxZjWnd7e3t7e0DcwZ2RneHaRKz7ZRq4jwM63n8Q344jNM0uZ32IUGH9WPFizc3N0wEUADg5Jihqvv97mF3X0V1t/XL9qPyPsUbMrUATzxe7YL74XDYPdwtCpnpfn/Ao7JQuLDmlLu+5Mwx5Yti2gESs0NrU4tvFF5f0zRN0tydmBOzgd8+PJhKyZ1AcQAkVycGd7UZwvHoDEX8MTM90WvNwNHiL5s2UTWpraU0LTJcX8th76vBpWo3DD87tF+2h//wMByqWRb1/Hk/vSg9LtfiXnD37fvdr7Y/m/Rep4PVsakBqBqEZ7ybSVUwZ0ZXATAVcS1mrqVLjvdT+evv9ecv9totHXLpD3/2afrV9w83jdGFFBYmf/TsqlNlWpoYE71+tweUvkxgSTXaKNWWVFBcYyuAAI7oSHakF/ocmYLugMf+lAmLG5lX050ZHKryFRNRNOdm9vRqEBVpFsuDh4ftZrPq+nJ7e5dTV0o2Fzertaac3719lzL1QznsD+vNsh+KnZ/v942QHz/XiJjcEYAISQHN5DRIjCI6qjAcCgAGDzU8ghBxGuvlJ0+XqwURATgRx//Pzs6Xq+5he/3d19+vVqu5eycahgGOEBFm/jB86ErZbK7qVH/zy1+aKzMjlPXy/Nnzp6aABIZ2onP/4NjP03MI7ZxHw0VABFVJCRL2b95s+58sRJoCr3r509X7X71J74RxWjyFm3/x4unTizOpKjIdDq//nzef3ejS9K4pms/Sk0ToCEwGAUtUE1UFSUesgas9yJQFE9Cff5/+2afy0892yv15Lj99Kn/y+fC//vUOU3Ftr15sXlwkomzO4qBN7t6/f3bWo7mjmWnsOUW9NRBQAHaAcHc7fngyc1M4QjtMVHLO2932/vtvQFRF1erv/OyLxercGVerZVSZADEBWtZaHx52YYI0TW2zuXDX1dJXq42bHsa9u5u3rmNOMJQBCd2bGXddt73fLpYdcj4Nmt1cwVJwMJFYTGPNe7pbsTxfr9frPudSTkcnJM2Jcbkauq7EZClSTM5ls7nImdyN6A3NtD8MrZZTGmJmQgrUd6314f5adWIm8361WK9WGzc08DgbHyMiHA/3rK9w5GmHcsy8Z0UHFPN+6H/7+vrp0yE7MSzTEi/2+k+f2re3E7fpn/1O94svnnK/qiKg41991f794eLOkYQ49eYAfmdmACzupEdQMoC5dylpm8y8SavSxNAAJPV/t5f//bfp5VXtzpcKq8WA//Wn9v794f+9Tk8X/C9/drFkSd3CvDWnu9uxY1gNGbwBQtCakdBd3YhS0jYjXuYxjaM7uZmHbqSTOwHgMAyLYfntN3/vMMbKRcEFPM28uVkg0N232+0RjhLCPXw47EIwxV0cPKUk0vphGA8jET48PHRdl3NJiXe7mkuZRDym1nOIcf7ITDVDBqRwxon8MOu81Fobz5X3SQ0/yNURVODYokett90+gMM4bVW1tZpyeDVa9HcxVgYAUYm/wEQ//fyfBGAUyF+9+izn4uCn8/GD2PPDXwXmhhBhJhuRzx8Pia1w/u7b659/8Sl3Q16szm3/z+32qze1ifzZH3/xe3/wk+1oC9e7N//h//zNy2ssMH1orTlMLlXV4hsRoKO6QW0HEzPLoQ8H4NJARd3UCEn2mfTffod//Pf+p5sL3Dwdlmef+Hf/6uf25j/e/IvfffU7G3ny5InnRYJpHMf3729eXi0AxxCDPn2gEAUJxnL8xrzJgSAyo+O8u0FEQkbkp1cvap0okQOhAzPvdvfE6d379zADBlFEHILzjwAYxc3p2kZzk3MWaarV3Hfb7WHcx7TFTKdR9oeDOlw9//Tx9TezI8NjrnQpMNHuHqu7JnJ3d+e1lK4rpSwWi5yDp+0i8t1330XECsZqoBDd38bXUxMcKzVxh/ALyjmXYyTb7Xa11vfvP8hUv/3+t25USv/i5Yv1ZomM874uAozHcpd0RkRHPeSO6DATtaPQ8hO5xBPx+PRs9fWb683l7vKScMpnm+w1/9nnC/ik/P7PPj0cRp0a7j/8X38Nf9Gem23lcKN1FBnBRdQcHREL0pQdDzgscDIkKBMoG3Aht4ROPDVjEOLEeCOH/+lX7Wcv9q+Wk3S4uXz2i6n/742fnJer51fDMLh7rfb991+tlqVk1ubuykwUcCiHIKBKDSiBhZYUuCu6Uag6UBwuRCQqiWG5XC4Ww1df//VuOwLAL37/9y8vr5hoWPRdz+6ECNRsu929fPkSPKnGam9m+cUVvb+/H4ah6863262IJO42ZxuROk2t1slsD/vW98vH7OrYFcwHiBDhEa85ooqZEeJyudysh67rmfn58+dxYPu+DyLzer2OOebd3d2zZ8/6vg8Ds7id4SDkDiKHd+/fPH/+AsMwhvD5s+cJqdZ6d3tn6mq1o3R5ddn1QxxKM/VHZyJSlx3Bb6cP4R5omeO4eo6nSki5oydP1l/99pvN+g8LOyBebc4+v/LLq2d9oWmUsU1/8+XNv3nz010Zyv1rHfdad6itqdUGZm5iXiB+JCETgrkSIxwV092MLLRUvWEPoH/xnf/Pf/HuX58P+dkSqbx4ddbs0BdEsKlOKvr6zZtp//Dqs0vXyedHARAZQI7BE5mVUDzYFfyotznWejHodzMmGobh6urq5m4d3XTi3JWSOAXpPVLYYrEU0fPz8/EgImaqmEIUcPYO77oSGmKxo+z73oEPB0Ns8X0O+33Xd6egZe7oxnQsSoJ6aTIzb6KNj2OeOM1rJiR37Pu+77u+74io7/vlcplS2u12i8VivV6f8o6ZpZSZ8zBwa1UUu27our7Wqe97MzGTRNTcOaeL8ysAuHr69PL8klOB+ZwfdzTgEBk9bhvEjBaOW+FIcx7AGZ+lHRiQHWG1GFptX/7t3//u735GyCPQZ589y0NXlVzr19+++R9/u3krm0K3BESOZk3VwJwc0BWMa5u8giF4UzVgLm3fSFSSGSiAEDA7iGmyuwYDgf4vf7199rz/V93LRG6qF0/OUkrjKOh+c3333bff/uLV08I+SnMHB4lqhpBn9D4SJ0XRsJqauRgYKcMTkoIQswUs2J2ZV6vNyxefq3zdWnO3aZzSghkpVHjpqNgcz2Br02lYE+vF2qYm1cxLySmn1Fi0Bq2KCKeptdZqFe6mZAiATuREDAYniTsIvbhHFYYfg5CoAPaEhSktFgufaQnC3NVaP3z4EJPDmDVH8mIOvHwR0dYmVVUBUzIlaeimQDrVOqrs6jTVulouF/3w8unznMvHKp5JGA2MExOixHiEUegHvT0hEmHIwop5czMANFRgRGHO/VC+/fabUvjpsydnF+elLMG0jdO71+//3d88/HL/hdOUx+oGKSWHhWIIsj6YLCeQtr/HWrzz3FETSzvzu3tH7zMRkrmbNwQHdbJGyFDwrfP/8G9/e9XBz794gcz7qRIJQr6/v/vy735zdrHu16MogSeYFWSqQ4P5roK7q6h7DPzoeOPdZ2g2OKIzmZkaKCMYlZKfPX2G6Hd39wBwd3e3fXhorQHhaXLr7r/+9a8DiQXmIkKcU+qYUS3sm+vN7VtENLWptqh+AGarExF5/+7dJ4vnShmA+ln14DiJRqZYaAN9lBuPk3s4HLYMXad93799+7a11nXz8DA8ePu+D/7HdrvFo3YVHZ0uTmd/HMevv/6aiIgxJf1w/e7mepdzXi7XL158nlN2N6SCBsBgiI4fySsWmfyYsMRNj81toLARCBEI2RSBBMGTpsNBvr+/3+3un796VnpaLPq+FGuiZpMcKNMf/PTlN9/s/uPrvRs65QxlSCmB7OWg7YDEa8aXnXnWZE6UEx3WaZufJtbUd11FATBHUAR0UGaCZDY9W/Cf/O4XqSymhmQSQwBmQ2vLVbfbPnz5pry6OsvQFByRAQzAAV3VRVwEjEAU1RBQ3cMgBxAxKKjzkDcmagCCihPl3L969fmLZ3p9/d6shb3RYrEIVZcTzabvOkYiht1+7Moy5bJYLGJjPU2HcRqJYBwPZarb7bbvV0TEnMaDTNP0sH9AJHVnIHCOsUk6ldN0VJqi46uqllJevnix7PP5+ZMIM1FHLxbDdru9vLycV2kcNgQz3jGlFOzVs7OzYBsFhfZ4ttBh3Hy3sdZzYiJKPEBKAE6c4xshPR4iHoMN0Q9+HZU+mqkRkUhTdRVMKanSN7d3768/rNbl57+46rvVZrEehuQu+4exqZZFefr06eWyfrqu/1tn/+6rt9/ek/M5Z3QT9ITQudvL9eYT4ob1YZr0MMHUffH8ohsUnaYDvxsnwAqQAVCQzJfLpH/wavPf/ulnP9mU0mdAMpOSmJhLx8/y+TDk29u7u5u7X//d6/X54nzddbYHmiWIYqJr9pFi9aPXjIf5SDM6YRYop97BKUel4UQU6kYxOsEj0yZgweZKSF3X8yzo7iqa0uKsWzbZmVlrAgBxT5lSJZdm6AWRTwcmWuTU0DERxGTqkT5rVNAppYRLJiIu/TCoVGLKmf0IUQ0x2JMRQiTd45ZUT66Dqtb3i1onmsHhPUJx3CGyqhlTTgncIVHkpAjXj7swmMscj42puas380omlJnQnW10lEkOt3b3cJ8X9Omr87P1YrPZDMMy88oNb7bTV99+/8nzi+WQmwEOy6vc/Xfd/Z++vPpPX9/+H19+9809HBAdlw2I1VuZFti5WlEDAEcltwxE5JKbTyTaqRaEKSf7py/zf/XHr1497Z4sYFkGR2UbU+5uHqbVAH1JDX2zLn1/vhj47rZc327fvd+fr9LFeW7o6gaALfWualb90R7wWOR9fJD8uLJ0d8JkiVwU3Z2aqU6H0R3iXnwsanGGBzJRVCaHabsua/MaHw0JahMzDZBxVNOtteaiUh3aKIfel+m4fIV5Eg3HN+Snp9pmvhmRmWmTnLtpql3XQ1hb5n7o+8PhcFqz+xFvGkHicDjsdjtmDs8eACilV5nCNznc7QHpsN/et4fSLVYXVzDDyWZi4T8yff4HL3M1lYh6ZjqNfntLo9xdnA+ff7Hqu+VQluv1mqmLzfPDw/1vfvPtV9f7b+/aH/3sk+dnBUEdfLXZdL1fnuU//p3zX36//8vv7r98ew3aEa4bunrAOIkTUzJidAAxIGYg6dx/sil/8JPzP/np2asXF13hMnTZAEVTBirLt29v//Kvf/Vks/jDX3y2Xi+ZsCvp8knflaGUPI317mH7za9vEFJOC3CAvMeaVczxI2ri/++FENrjGJN5crNxHAFht9udjLYCgR49V5ytqdbt9h6RovxIaebwhcyvql5fX0/TNI21TtN+HAXweb/ufjiZS3BMkKdz+hGu5b7f728/3Cy7vnvoPnz4sFx2OefDftt1JYab0QcG9D9E6U+hNbqzORvWaZrGru8RnDkh8ru3bw/jSJAX3cCnmU+cawdyJ/6xopvPtGs6rYKIyGN9DVQlv3hytlqX0hN1fZ8vGcEMmqq53V6//ebb7wHSs6vLD3v/y7/56g+/ePHq4gxp2k8GQMNiPfRt2fEfPhtuH1R1bAQMrKCz6iWYBzQZyFQpcRH/1//NFy+Xq9WCStGy8sIMiMBIGavyl3/71fv3Hz559vR+e/dXf/U3P/38s/OzTWJStb7vr64uDoeahmVe1d12lBGJOKeqSWgeYGjUO3bUS4nro0d/e3/0svmpQ+I8LJaYqJQyDIuuC3uutN/v8ZGNHwA8Dk4xfwkf51prLmVJWFuDsFlxBKKyWJVSguMQpQs8Fhp//AXGjA4AiVJKi2FIXSaizWbTdV3mXLqu61LO83HJOd/d3Z2dncXCJRTO42dEFtvu7m9uPqzXGwAPsm0/DNvdfUldTukomXREZM6brv/v1/xuEREdrUlL0Pfcnz971i9LyQXVTRwwmend9v2bt28ebnbD8knuSvK2uihvD/znv/nN2yern37yyWa5BAdXZS7nm3690icX7e5h5/UGIalbM1G3ozWbAwAnFoTC+Y9/dtEn9JydfUiEBq21CdLNh913X37pTp99+sma68US31/f/epXf3f59MnTp1eLYUgMCNqvCg/9cjHVdXd3UwtPrMDgxhkk5t3Hgnne9P1A0fuU4okolhSO5gDuSJ4ROWdoYm4som7UD0N8J3c5cW1PRzMIYnMIUNOmoMZBnXLrui53RTWUVeb8BSeh8bgvpzoaZnVdY6ZSSsrJzR2MKRMyUe7KgOCqFrYEUQOp6jiORBS7jlJKiA4DQN8NTBnmAOvElEI3D7BNE7qhM7iHodO8Ppzf1cdJtAfexDwWjTEHSU5onvBwsV7nPqlZa80RJm2H6+ntzcP17Q0Dnm0uOZeENiRPqFDSUK4+3O1ev/vq02dnn3/y9GLdJQITB0MqZbWWwwduTZDBCZvrJDVEnzyM1ZuvhkUuqVGjpBmYASH5/Xb/N19+2D8cPj/vnq4X5nuA1id/crnphv7u9u79zf3z5y+urtZ9l/ucinmy1GfOxDLtrYmLu/fayE/34pH21wneSY+8SuGjsC6pwf3DtnQD0rA/7IJ0g8itCZEwk5mrmbsmxli/M1GrFc3ZQZqgutTq5iJNahNprdW6Fz9sz572cJRViJOXTsf5BHoHgOPw190UYv0SWOCmTAlBttttKR0nE3EiCju64IW5W6hRRQ2kql0X6neNORyECJEOh8Nhf9jphCvAEOVAmmeGCBSi9ObEp6Y18NAOgOABgjYHM0AiVAXwoesuWtvu94fr27sPd/vr+0PXdavVapkSEdS674e0WPWtWSctkV5crR4m/XB79/rdu6vzzU9fPj3fbJiSglczFTSSEP9rJk5zVnUn8aYVc5+HxbozZcbdfvftw/1vv353ey9XF2e/92lZZER3dEGKJr0NQ1p2lw+78f2Hm9dvr1er4erJ8mLVJ0yGTuwpcSm9QdUJGfOPwm7csxPW70dp6BgScLlaD12urdU6Jh5aa2ICjjl3IeTr7iX39w+72vaE4Gp5Vsv3nW6j+zGzw34v4OM0EVFKPNap1obwkZYat3K2vAzksh9d7MzMzQJ+++HDh93t7WJYckq11YuLiwg5ALZYdsEaiTR0/eEDMRMxIrZWu75PKcV+nIgWi0V8yFjEIvpytTSFbhjUnRE+FmfueLJxDdPnGUV1/HOA4P24mRIQl8nw/r7+7dsvt4ebw7gnpGHonp53myElLt4MXPs+5YLmowEsBiaUZrYq+dWw2Mny3b3833/1d30/rJbD5nx53iO4MYM7mikCJM4qMpeIjs40jnI/XV8f6u3d7e3Ngwo9u1z+85+vexTRPVNv5kDibu6Y3RIiMpwt83Jddvt2e7P92+s7Knmx6Ffr5QC1T/MDPNVJjf/Rg/Kxxji+fvTXIiM4QC55tTyP+bI0V5PgIzRpiTtA2+6s74qpSW3TOIZSSiwYYrDX5dQPg4i0Vh0wQ8j8fvyheFJpPb2bmSzh7oBumHM5O1t3DIkzcVouh7OzFTPnXA7jw9XVZUw2+76r04QIuct9t0op3d3dvnj1WTcMTaXux0JgrtHquzuA5cJNWuLkdMJqfLwKH69UkMMRgGaizylnm6qR5/DfyFr1w5vXlfvFer1eLfsltdITIibC5ubmCICWdbS+T4AuCl2ilEgErnJaLH1zWDTp68Svv77Bxf3mydIBXQYANsUmAgZmDckSElq62377n/7mWsrLJ+fw808Wl+ueM6g3aBOLsVYFIjQFN8MgJxJhRmezNPBFf3Goelvbu4fp67f3nyzbq+cbzeruXd+Phx8Qm044lseXCk+wpEfHyNws2AoO01S7rnMHJDfROBbg89iPiNTCBcEoJzcPGZcAIjMzEgcziJBKzm2a4EjYOXXcH4vo03RhfpePCquudOaGKACiVnPpHGZJc8QwokbiWWW3tZF5QcTicLFcbw97YHFQaRKr+HEcax1jtLrf7xh7QPDHEeg42IxcqkHlcTzC9iM6Rop1MiAxAM8k52tdP+lScoJDIUswgCEliqnBNE02yXLRoRkknnO1Wy7OCTu3S+E0WL4002q1Nly40VSru5upNGNzJENC9CSt9qyfPS9PnneLzqFVpSqeOMiRqGjOEEYMCA6mgR9FRARXUiCGs4VerOvLy/6bbxuhi02mKM1EZV5/HY8OHqlbj7/4wZDsGJmmcby9fkfERBRt8n6/h9MQUhUAShn2+912+xB2qiqqImBOhKYWggWRwsI7UFTqJNtxO2zkR/ia9KN3QEeX15DOpOCuA4hoKQwAIm2/U04pxBKZOWevdQ+uTDhOmpd5v98fDvvd3fuM7ebubpymwikRq2pMJsZxv9/tW1PRqgBO6IQxbGf4eL0wtqcIAMDHMIk4q3/FmzYDdHP22hwNe0ZwScRNwUCJUCYFAG2iqiknLgBQwYtFfQ4zRJjRPeWMkLFBqRUnq+zAOZODNZWcgYwQMqKrioEaNiJZgJJxg6QGgBIQMEMAV0BTQDIKrIa5RUuhhshIxOjs7kPSTWmNRKGJZnBWaTT78UQ1Oj/2pxNzqoT8UW8frUwuZb1etyattf1+LyLhFh6Ox8MwMPFud++um83aHWudoiEfx7Fw9iMrfFgsJmmAOE5TExmnsXSxqfwB+SJFjIn3dBpDz6ppAKY6TZWM3H2aat8Pu/1Ycu45rdcbAJQmYVB/OGyXiwUB2ThxSn3f73a7/W4fkewwNjM9Pz9395xzzpvFcrlYrrbbG/CEM8pJ4in5wcriv/BC5JTCdFcV3CVRgsbEbui55JwyANSpIhITpy4lUveKDIANkBDIzVrzUlLKYCrNkJlCMQKcgBoQgaXZs/SY5dHEwYgTAChVI6ro6EgKaoYOKiGUiYCoasfn4uNOKuesppCQUMPrCVAQcywziBDU/wsf/R+7GAhB+kJS0ZwzEXZ915VynBtB13Wl6473X4MTykdPppgGyVRT4taaiIY8oZqKpq7rFuv+xOw7Hd90miydztAcjRDVLOd8+eSq48yZ3f3i6pKYA4q6Wq0SYkYWVSJ//+H1er3p+/7UdZ8oYPHDgheWUgpAWd+tajsQUmhDmunjyQ8edzdzRHTgQJwQIhN62DWbmadEhuZKmyW1USscwLFwdo9prqP5DHUCCO7tsCpmrqqAllIOw3IuTKlqRdLOTBOxkk7gVQjN2YhU1NQM3NEETc0tmYmqZMpZTZ0V0N3AGSDHlp4MHVx9cgNCejyzdXd0YRSpQbJK2gowADZHdlZ3ALQTI+x0MR9373DkYM1TZuZxGqdpXOY1MYHXcLc2M9GRxNKj3i6KlpSTqoZ8TlOhkjAlVTFGEsxIlWYeuuoPGsAoYH7gmfr45rl7FO3S1NBcHBFbax1/fJhKLrE+yzkzzzT7kGuMs3Iqz1trKXHs7WLJEh3pfn/ocnGfV+9zeno02PzBK4LnSXvP3M0iWkbQnBEyFr7qdjgccs5UwD0efYdGzEUbAid0BMBWPRXklBCBOTUXVTMVYjMzBVUljtEzocgcqt0sJNTs+F/cSJ9V26MJgcc3O4T+gkMyk7wITWdLTTX1eR4fhVKCf9Be/aiBf3y/iMKYPCBmzCnd3NzkzE3WPkKUPqp6OBxaqwEoNdOI+qoaj5OIADgRjeMYes7QFMxaq7HQ0EPr1i/x+H7gyMpwni2AkYhOUFkHc4JJdNzuaLFIudvv95ywjbvUDbmUNo57nPXqur7s97vYs8QUMTZlsQgDAFEpuUxTjVMvou/ev7u/fw+A600PDuxgx0gfHzjahOPJAUE3OnWQYWTqobYJ7iYytqk6MQIhoLlnBOdm3sRNiaCz6ZBRu9yruJk65SjFTcENDRUAGJI71KqpNHOdR3gedsQhRaoOQkwo6F4BSMWY56KeZ3JjFMAEoO5GWEIT0yOkmCASIrl4eNy4q6o08k4ms2RGhjOKzIDcDcjiSXw8iX78jCGiuyGpa3TvqycXl/vDdrFYBhE0xDfiQOejosF2u12vN/FIhIZzrKQApOs6M3vy5PLu5pa60g1Dq/X67t79B6AxIpr9wgIF9rjCdw9zbt1rLVp0gpzTDMKRCciu39+F7AMi8p6YeRzHE4xyv99v1k/6ruScU8ri6oiZ0bRFM5lzWq3WIe7p/sh351GLEccoftfd9fEj6D5D0MXIDSmWemDam1sCcDdgMFHEQaqLOVnOgypNTlmMTT1BiImrsyOjqkozpuw6gFc3NwiLNUEydxJt5hN4IRYgVZ/ca+hAiLgZU0oz96caEjFnUwFG9Oyg7qamiOgGIubu6pIYm7MCs0oK9lcI0HlIrZs5uYDpR52Jx/fPj+sIAD569iISqqk7LhdnQSe33lUk+GRuFigOhA/r1RpmJziNuZqIjuOhtdYaiEMauoz5ME4E+cnFwKn7cRE9t3azdDUe9wiAQABc+uXzoWyGvusWhLjsc9/3KlVVmfDJkyfR8sWrlLJczkf+7u5utV72fb8Y1kR8aKMhghuagDZ370pp7VCnEJhyAUfGI/D340zhlOx/PDpDNHBXV2uMCNg7sCtCq+AgQNmdFBb9oEaKExMQAzjXCQlBreVMgAyIEINBdVBWM1EXZfROAVCJWZGxMciMngjz1JSY2CcFaGRAoOhOYADuYA4tJl5EBlC1eYz8zSO2qzcyQcwmoMZkhJK993k4Qyinm2EINmtwQRRYj2ccx3IYgECBHAmh7sf7h7vVap1SIuJpqsyMSCllRBJphmBqu3HX2kkrGMKQVcRUIXHngXDWlks5HCYVMw+8DxzBtRYEm3TKZye12OMjDu4goo4yjgemzIndc2JWiafhaMY5L7zmG2zHD8xMQShhhq7rq8os/u0aqPv9/vBwf1gsN7EC01mx2h/DeOcI91GbDMA9ZD0iUyh4QwPIzbv7ST/UkQiZOWeQZimpA6gZqCNCooJAidFdkBTRHRAzExtic+c2JaSWAT7h1LsnQ0rUTNWsqYqE3pcQEJI7dA8PdN8sZY0kQNTmfhuY0M0EUEKeOAG5WeTEY2Qd3T0UE+4f9Dwvs0kDUzzWP+4Aof6Gx+h8ZPk8Qm7BUa8t/kkUMa0Jc3r//n1gs0IYLkqLOHwiEmrxrbW4b+4CiK2GrYWqTQ58OIwitVaTJtv9/uxZGWBuuaLmSbPGyqP57+kRBzCTA6pX9Vpvh2Fws+1hZPSu5Frl/v4+nF91am5eK4lWdUyEU62cEzPPhtwpla4zM1NBt8M43t3dd2WhCyTMDhzbtlNqP2EjHx/K04ghsBwQJ54QoJgfcr589UkhBkppbMIECYGIFJyIyJ2ZQTzEICgDkZuRxySI0LyqGnh2R/OWeK9VMhmhq6F5ImukDmIgjp17E9XlajPAInwzgvKHs5QzzCnYXIkIAY3AZwiYmANhMhNzSJzNoFygHm6A9p7QJ0PgmCC622mdHE+Rhb6B+kfQopO7NxUkzMQAkPOsBz/VfYwRVDzsSlarVSwoQ53yqNJkItM0javVsnRkhswAOEQ/pEoAsts97Mfd+tgsxwGCk2sz4ol0/RFr7ODktru+4/MzZRjHUWQ9LBZDZlVbr89yRvOKiCnn+7v7fuiHxUBlSIA5pVQAEcbx0Frd73euy9IVQihdX1vbbM66rn/z5vuc8oxkOZ4e+geUwtPoHR694mFkIsaCVLXietl3PRCxes/EDkCEjEw4qzgS05HoUDkhYcYQ7EQCWMbPRITqfrin/XRvaC6qPgAQ2sQzWgAQckoJ2S5fPKWhgSMzaUMHZIZoE+MiR2uDREc2jjs0QiEAgKLigAkcRWmbJpcRwCj0Z3Guh2a8mPtxZRE0VQAPAUaIgYaYMjISMn9Eo3NCZCgppaGPwjQWkXYkE0c9WuvIXSaiUjpVBVBnNPOUAn5Ycy59P0wyMf24bU+nCuMUhI4TXnW3nPLZZvPy5csJdJqmzWZzdXWVE0lri8XCpIIrRa6CdHFxnlIaFmeZO1EhMmbuS0XE29vrnNIwDOFov9vtwKOHnNOwmgZb+Ufv79S+HjvVqBltVucERSwAmFJerVZUBkxKlDLxKf1FMDhZRVII5jsRO3MO8FriRMBEqGDMhOK+lN3uoWlDAAVzcDXzIxTGzFB9WK1wsYbU5q61hD+wxZ2OlpY5zxETHOZVtpKLaQMAdSNObkIIw7CYdg8AjTk7oqsjfdTb/FgRujuifVyKz8HghMEKhrKZpcRMXHIWmXmoOBOI51HfqZAi5pRIdU8EIU7JHBRTVa2InjMGDCjeADwqSU8H6hHq9vhVLFU5palV4/mE7ff7xaJzcAUz84SpK/0wLFrVrgwp5UxFTZkZcc6vqsacYs8/zfCApGq3d9fTdFAVnz2NYLZPfASYOl270xfurqbuhpgQyQ0NgYnaofbdSlsD1jJkMz89iPGpOEj6s7kzOggCcGITbaZMHvesTk3VxBsmRCf0uBCKzggW+UhBAQ3MwySDCUUk5yEKk9N2M/Z2YEiEbhClsIpigA0BAEiaNKlq3loFRwBkTAqu7uBgIRB/HF98vBQ4J8TTGYo/UjUifvbs2W633++3Dw8PrdZaW3hkRdFzOga73W4+B2BmEyLWKiIW2w9TBbTWqpm3Vsdx2u23ZrMb8OlB+kcGiVHqIyAhNpHD/qCuCr5YLO79/v7+9snlmhPt9ik5Zeb9YSfy5nA4jOMBABCZeC5URISQHLzV6m4RgUopNzc3b96+yUzL5SosPKLEiQfIzEQ1tvaImJhP73j2rXF1D/vbYgqMhsaUQExNlJCmqSEAMTMBEaacY2avob6eMzOmzIhUpxbcq2aOSCDmDq01NTCHRORmYR3UFMFJHRnBHZq7uqlIZF8HlKanFneGfQEykplamw+xmakZAaA7zcGAwNFUWxN0n8+ZoitroOcofHrmctoedfLHUlrCihoRET2mxovFYlgML189j5CTePgBxtO91endu7fhyptzajK5YRwdBFTT9+/eb842zBS048Ww2Vyc51xOhXIcvvlxd/OP6IFj1YYOIlJVO7XS5cxMTCmTSN0fasndUAZGQMOU+PLyyfwdU+q67vvvv+v7AQCIKaXcdyW+Z8jV5JwXfd+lMuoe4ORt7cw8n99Aj6meAhJAqL+FQECg6iyQmpk8QRKbXCU71SokMfjXAAFnMQCYzMw8h8IVMCKJqyoQhS0uyRHni5inqbWaAQBcILm6CRBTNkiByxCA6kJmqIjE7qauzHQasptqiOG6VARkZnNzdwacJUTE3Z0ICTkS3wzrMvHKIqhmAI6OBrNhGAHoIzjO8XYd63dwQqx12u13pXQpZ6fMpctEhF0IC9ZWE7OJispyvXx69TTmzok7YDgliv1+f2IaEXFKWUVLXiHRD9stn9v446ThY1qNVFdy7tbpfLXpF30upQwlZcyFdrvtZn2x7AdvAog558ViEb1i3OycS2gJxObrtMSJR1NEYgUwtbpyNzeDORqrWcjBnKYdcDxP7rPYNlE0KR6uLkewuzGlzA6htEB0goGGNUcwExG85EJMxAj2UQP0hBI3M8ewNQM3cQe14u7s5tak1dIVN0ckBiQmIOy6EnwVQjIDkZZC09nQ3VLqfF54RDXt88hDjSJDggFAZkZnAnU1MxAxM8NHd0Tj49PHYuMffRHRw8MD82G1Xs9jJUQ1ybkrJau0Oo4hU09IIXphqngENLu7ytyj2TEj55zN9P7mvue++yFaPZ22dKcyDR+dMUR015xT5JEmkzn1/YawMBU3E21IHBYvp7MYDvNRRcaNCeGOeEPzR1I7tIOaEKETuf14zDpnWTdzKkCorlMNwlSoMbk7mxlBkJopcos7EzEjH0kdRARg7lpy9gKiqiKLVHICsFCzCTgvMMcmB7qeTLySOAhDRkjNm7TRwDD1DrnkZEpIHaVkYK6GGQmdXACM0WoTdxuGXtVnIDqwiatKTK4JMWVGwypqTG6GJRuQEmpwhJFh9oYPnTJQnOuguSc4GsiDP26AMOd8dnZ2c3t7e3ebvvm274OM5cydqYG1aO5qba1Od3cPAPEOIUjQET5T4lrbw3ZbaxVp0uSw3z/sD58Om6Bbx4+bIa0/CIfhK2aqZqpaW6378QZvlutVP/Sg7uDjKHVqu+24HBK5mmvXDX23jBrttMoIZ1c4Ul1PPLeUUq11WC27rvCHd6GH/5iL6cdZYsRFM4vm58STcg8XKEBHRkIHFR5S6hgMGBHD5wccOHGMT+JAIyBydjdGQzVHzCmJwVSl5MwJXIVzSkS1GTQgyMgI2NQbMJk44NI9J8SqmiglysCWiOM2E6A5KULuw1YrnMIwlmA5p4Yx/oehJCQ6HBrnnAyqGTRoakmYsZuA3Nk9IHXqIXL3CIysx1HqCcXg7gBubrUG6rkgYgIMW2IDG3d3fd9fXF2ED6OKp9IZUGujeW2tXV9fn5+f19qGoTfzWqeoI3b32/3D9p0Ilz4EPU73yN3nhbnIDDOYOwhHdEIk1TZO4xbw7uH+2bNnw2rFKeVU+m5ghpR5uRi6nMfD4e76hsOT4Hg8Q9Y+Vmzb7TY8gqMzUtXdYXIXAQNEM2NwAnSEOW4fESbH9Icn7Qeb1YBgS92HYZ0QulQcO+q7MZc0x9A5c8V3SDk9nio5GgAhMJijI+TkvR8ACJEWS0Aghfusu8GZiIkM2eFQeVRPDc/cWUxrNku57xyDAmgIkAN7aK7HhIyGBADI8zgBEono6L5DZCAYsllz5YZUoVYZwJxYb1O+9UTQkaomDI/0k9eMmclYzQ2YgKJJDPWS2eJ1t9u5QxgHxGYp/uF6vV6uFofDofTF2QCZAJmLqy4WvD+UXBjJU6ZpmoZF10RUHAhKzqWUkgqim1UzJ5rl6tK8fv+HWRWRCHPOi2HRl662tlgsur4rkZ9K1y8yMxKX0vWcdtNhPKGNIn48PjGRU2cpe4DEzESHsUm4Z5hZ7NZdOadArx7PopmhH/V4VNVUTWqlwTc/3T17tUiciR2xZa8EOZg3x2nkHMkAoixKSLPrpycA1mPGjHIDEZEQHDCjPXuenmE42iPw4P7u+1/35WJ4euXmybIxKrb7UF5zMHAHNzDLjo48fx6A9KO5KEGHaqquRzs9U0MYTHTnSyEh02nXQcVxKAOAq5hqHcfpbA2BWT5NfQRNVczNbM7CDsDM52fnt3d3MUMBmP+Vmd0/3OcuuZuoIDIRETEiiELAKGqtOWWzOdoF6QcBAxk97vdpsel+WGnMrs8U7YPOmxqzo0+VzXVrLjnlHCs3IhIVaQkxoava3lU8HHqOinx+vN+llFLKw8PDaYpVSiHm/Xa729WLi1eJWa0aJvMAX2mmMCYNH3k1hkoAiNs6qlnUGqv1+tmrTzjllLuMwOhIjEQplwgDCcAQzDzUYAycj2pLp8EiAEedPR+jeYV5IuE7cwKMgwCbJy/Mj+nY06ldn2tHclVRN2JCoEDqIpjEQhQwxUQKUUJ83yHmoTGzhmP4coOq0rcJXtpORvGJAA1BNCwKwEwR0RAc57ZCZ7ScuYMiKlDi/smTfHd3u93fN6uUOdaorcloExOhkampGgFKiM+7tdb2t7tjNoTdbhdY+CYyjuMkdT9NS1f3FCAO/IfEwsevGMKEzxSpI9Pbt2+6YaGm6/W66/qUGABKIkZwt2k8RMo41c7jOCLibrcLIP27d+/isKaU3r9/f39//+TJ85SyA0x1YhZ3L5AZidTIQ0B2Ds5NKia8vn13kJpLwW7oqNu6o0gCZxP0WV8SMgEAOhYIe9PwXnVH4JQwMRBigC1TIo4ZcbTrH2dNxwdM0WrMbhCQgNwsHfU24wpG4+nurVYEIIi1mlcL2WxURkwE7tSspNxqbaaQGZgims6bUiQTQgQmMDBLoqaA1mRP6iq23z3A1TOYjzsizsqNp9fjLlLVgHxYDM9fXC2WS4HoZx2O9kuoiIDffvPtarGI+3hidwSyzMzc/OL8gphEtUoTmfZjtdQ/Wu7CfIB8NqDAjwKJ7oQg6M68GPrNYpkXi67rhkUHCMvF+u7uXhVW69XZ2TlhYnRyyaWYWQAOb25uIoVFzlqv1xHbWmuHwyHMwphJVVwdoan69999n7l/8uSSiAk5dRlCHdKl6xMxfXjznbnXtjf3oesTkJm2Oqp7JnRrqc9OZmboZJgJ1dxFICV2h1obGiJj+EertdBhS2DmRlTyvPqBMKsziUGTOBkjg0NcWgRIJy4UeGA1sfCsRQEA7iVUi7gUJnUpXU6Q3YwoZWNAVBEmBk4CHmnTEpq7mCICuycCB/fIUCLff/13II05cSk5ZTw63cb1NPfddveTn/xk0fdo/ubtu/PzDTIBJwNkZ61KJUsTB8ypS4XrOB3BIwjHHv400Q5XeVFhYBFBAOKk0I6oEjezH3Dj/7EXAqR+2JQFllz6oeuHfrEsItIlXA8FiVZdn4D7bkA0BIlRkKoKuIBF+fO4mD2ddABImQ/jw8P9drM5d2hfffXV+/fvidLr198SYymZKTMxERE7kpq6qSYHACdosoXRAYjcgc3HpgBAmWHmgyJhF9qFCXCKRT8hp8w5ATESEicFBwPAvaqa6QGAoCCSUVQJAUE0JqsA/ugqG808zFM3GwA3U0UycwRgM1MwRAS0xBxTWZfmagToFrp2ZHzkbnNxt2ZmbnSczCGSI6TEbTp89eWvHZwwHS8pldy5+1SrmU3TBDp9+uoVOhDb9c37YeitXTVogW/RsWoTB+AMo9eIyqMJA8HRVCnqkNBXiDg0987g4+GgU+N++NEpOaq0/nDfFO/eDXMZFl1BbcHqbWN1t1F32tpytSopowMDEpGo11rNnUqCak1VWgs7jNPSbj6zKTHz4bCvdRoW/TTtv/r7L+/v7/u+T4mIhZkcAUlL1+VU3FA0mHmuGDsmMjXXicLOzinxcd4jTsTgavqAVIg4ogUgdCUjJT7mbwRsbohg065Nk7vijP1A8+yUHGdlAcUjUS4BAzISiblaOMy4OzNKawiOHpt0N9aUE6qYmiGMrWYgQjBVdEEwQjAES6zEFIMeNQBP4K4KTu6AREqWKBdKTgSJ3RwcRKTVaubjbp9LVlE1c5Gb9+/qYf/k8gmid10iwnevX3ddPywHBNzvdrW2lJiIbXbjczEBYhc11ftxtI/SrYCINzc3tdapTiKy3+2a+POffNGv1+4USlOIs47wLE58mvwiIoA5tN3uth3A6ljKIuec0UvJfZfdPZd8rw9mdEN3pVCTw9APyGwJ61RLKWqz7Es4XcZkM7TMaq3r9SYO63fffVNrXS6XPutqNTNnJEQCpyC2AQAS8WnaSeJqCXOgWskpHRUkZ/4NRLVqiEmd3SFxmqoCINMsKlJFgJCIrIUfOROxz6A7E6gITIAOpAColpBUlJjBgZE4EYD73FVwKqxmiGCqwKQIiJi7FSJOpipCKuhAzG4NkgNCRuDcVQMyYOawB5RWwWaH81gEEpEFMyjuKyFnBoFwrGtNY7KHObfWbm5vHeD87NwNuq7bnJ1F/8vMSJjG6enTp1FjMLOiGRkCJSN2/O7N6/h9IgpQ/anCc/PECQg5sbtG3Jk3V37s4Ono6D7HMVVwkzY97O+XOR1202azSX2HyGZQSnHAGM+rqCOmlCilzWYzrNZNm0grmAh9t9uZ+fX1dWw2osrebDattd1ud3d3dxIZIiJzT7Fx4xycLwhxA5rzoJs7OJmzIyVHgrk5j1U3AqKLqIedOlJOCdDdDDg4/AUBxJtaA7CEBVzDl+9YZgJijIkcQENOh5GImRCZmZCYEAyZCJGaVIppEQBpsCDREBEtpUyYzbzj0kzcJwTgTInJ2DARmKtCxwkJiMjnOXpreODY7oRDtgN3XSKqorMdAGc3EFEM8IhhV0rUQ601By992e/3gfCMNUCglkWk1hZklpQ5czKXgGkAzlud0zEAgNaqx7IWrVkzYEAEmNVkI6ucJmweM9/THyAgOnXUdauLnvGwn/rSrVYbd1ithlonFeuWyR1z7ppMnLB0BYlcESAlTmgmcmBOs/fMx1nIHPnjAIVy1jwxYkxphmHMo7c46eZNJOeccxYR5MToAEaEwFi6LsbZtU5IiCkXTskxcZm18GL5AQ5cOBcCTFJl3JnFIqGUnMMshjkBAIEFwQDRiclwzsIcwqSi5hg1jIMguXoDJA+7r1izRzTR6u4JuswgQQEAbyBECZA5U+l78PjLEFQOIiulR2uthSgREYAB5FS6OT94SimlfppqkwkSibRxqkSFmYlZVFfrNTHf3d8tF4vVahVhexzHw+EQJAYzf3jYMmFOaaohV+2HwyF2TX7UL2x1HA8HMRulTlqnSaq0NXKQlOKefiyiTyXhnMJC3dqBjKKaOzs7A4CcU0p5u92CI29S2E+JNAPvrRdTG/fEGRzMatdl1TpNIxxJmXFQWmvv3r07OTjnnGlW/HAiSykRpZQyYYA4VbyGElubqrurNqiN3LqSMScR7YY+5TzkaCohIZBqYgTk2S/SAAmBF4CZAHJZKi1U1FwBGxER0kwJdSA0d4vuI8IDIuDsBYGYgDwWug2JRUZpTSNUOhAlJEcwYnYyJkrJVDQRxqI7cYoojkSmnjMTgjsQFjMnVwAGdC7aVMyUycE9cXaPEZ+7ASdeLLraUFXGSczATYlSyYVTAsKu6xaLRa11t9vF1DEe1Ldv35ZSiLjWaRz3i2HwGUik84RPJPr5aZr6YblcbURkNx1Wre3HdlxZ2mnVnWZXdphNDo7PPBKhu9/fP0yH+45S7srr16+JqO/722t0965otQ+U2N0BpetxfD8BcGL2am5WypwpY9gd8KU4MTFXjJMaByiyAxJwNmYmZObC1DGjux7GexFtrbWZY+AIYGbjNFFrlplzHrreHRCYkGobzVpto7vNYF1C5pRzAkAH45S4LI66qDXIinSU2gM0QkxuCJjSjEQGzuAJgygbOExM6MB56AYwa1ZrhHgnSGTICSgHuQBZrDZCzENvRoSFEJEzcnY40UyRCJj46MrTMoGhq7XEKSS5gjgXSE4i7vvSGroPsTUHT4lLSmk/7jrqwkog7CVUNZTj+mHZ9z1iQrR3714Hu+EUePwoz4KI0zQ9f/FJ3w+HcdzvdtM03u0OkPuok+yoJvWfAZt0PmHeqoe7AAAAAElFTkSuQmCC\n",
|
| 33 |
+
"text/plain": [
|
| 34 |
+
"PILImage mode=RGB size=192x128"
|
| 35 |
+
]
|
| 36 |
+
},
|
| 37 |
+
"execution_count": 3,
|
| 38 |
+
"metadata": {},
|
| 39 |
+
"output_type": "execute_result"
|
| 40 |
+
}
|
| 41 |
+
],
|
| 42 |
+
"source": [
|
| 43 |
+
"im = PILImage.create('door.jpg')\n",
|
| 44 |
+
"im.thumbnail((192, 192))\n",
|
| 45 |
+
"im"
|
| 46 |
+
]
|
| 47 |
+
},
|
| 48 |
+
{
|
| 49 |
+
"cell_type": "code",
|
| 50 |
+
"execution_count": 5,
|
| 51 |
+
"metadata": {},
|
| 52 |
+
"outputs": [],
|
| 53 |
+
"source": [
|
| 54 |
+
"#|export\n",
|
| 55 |
+
"learn = load_learner('model.pkl')"
|
| 56 |
+
]
|
| 57 |
+
},
|
| 58 |
+
{
|
| 59 |
+
"cell_type": "code",
|
| 60 |
+
"execution_count": 7,
|
| 61 |
+
"metadata": {},
|
| 62 |
+
"outputs": [
|
| 63 |
+
{
|
| 64 |
+
"data": {
|
| 65 |
+
"text/html": [
|
| 66 |
+
"\n",
|
| 67 |
+
"<style>\n",
|
| 68 |
+
" /* Turns off some styling */\n",
|
| 69 |
+
" progress {\n",
|
| 70 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 71 |
+
" border: none;\n",
|
| 72 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 73 |
+
" background-size: auto;\n",
|
| 74 |
+
" }\n",
|
| 75 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 76 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 77 |
+
" }\n",
|
| 78 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 79 |
+
" background: #F44336;\n",
|
| 80 |
+
" }\n",
|
| 81 |
+
"</style>\n"
|
| 82 |
+
],
|
| 83 |
+
"text/plain": [
|
| 84 |
+
"<IPython.core.display.HTML object>"
|
| 85 |
+
]
|
| 86 |
+
},
|
| 87 |
+
"metadata": {},
|
| 88 |
+
"output_type": "display_data"
|
| 89 |
+
},
|
| 90 |
+
{
|
| 91 |
+
"data": {
|
| 92 |
+
"text/html": [],
|
| 93 |
+
"text/plain": [
|
| 94 |
+
"<IPython.core.display.HTML object>"
|
| 95 |
+
]
|
| 96 |
+
},
|
| 97 |
+
"metadata": {},
|
| 98 |
+
"output_type": "display_data"
|
| 99 |
+
},
|
| 100 |
+
{
|
| 101 |
+
"data": {
|
| 102 |
+
"text/plain": [
|
| 103 |
+
"('door', TensorBase(0), TensorBase([0.9961, 0.0039]))"
|
| 104 |
+
]
|
| 105 |
+
},
|
| 106 |
+
"execution_count": 7,
|
| 107 |
+
"metadata": {},
|
| 108 |
+
"output_type": "execute_result"
|
| 109 |
+
}
|
| 110 |
+
],
|
| 111 |
+
"source": [
|
| 112 |
+
"learn.predict(im)"
|
| 113 |
+
]
|
| 114 |
+
},
|
| 115 |
+
{
|
| 116 |
+
"cell_type": "code",
|
| 117 |
+
"execution_count": 11,
|
| 118 |
+
"metadata": {},
|
| 119 |
+
"outputs": [],
|
| 120 |
+
"source": [
|
| 121 |
+
"#|export\n",
|
| 122 |
+
"categories = ('Door', 'Window')\n",
|
| 123 |
+
"\n",
|
| 124 |
+
"def classify_image(img):\n",
|
| 125 |
+
" pred,idx,probs = learn.predict(im)\n",
|
| 126 |
+
" return dict(zip(categories, map(float, probs)))"
|
| 127 |
+
]
|
| 128 |
+
},
|
| 129 |
+
{
|
| 130 |
+
"cell_type": "code",
|
| 131 |
+
"execution_count": 13,
|
| 132 |
+
"metadata": {},
|
| 133 |
+
"outputs": [
|
| 134 |
+
{
|
| 135 |
+
"data": {
|
| 136 |
+
"text/html": [
|
| 137 |
+
"\n",
|
| 138 |
+
"<style>\n",
|
| 139 |
+
" /* Turns off some styling */\n",
|
| 140 |
+
" progress {\n",
|
| 141 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 142 |
+
" border: none;\n",
|
| 143 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 144 |
+
" background-size: auto;\n",
|
| 145 |
+
" }\n",
|
| 146 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 147 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 148 |
+
" }\n",
|
| 149 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 150 |
+
" background: #F44336;\n",
|
| 151 |
+
" }\n",
|
| 152 |
+
"</style>\n"
|
| 153 |
+
],
|
| 154 |
+
"text/plain": [
|
| 155 |
+
"<IPython.core.display.HTML object>"
|
| 156 |
+
]
|
| 157 |
+
},
|
| 158 |
+
"metadata": {},
|
| 159 |
+
"output_type": "display_data"
|
| 160 |
+
},
|
| 161 |
+
{
|
| 162 |
+
"data": {
|
| 163 |
+
"text/html": [],
|
| 164 |
+
"text/plain": [
|
| 165 |
+
"<IPython.core.display.HTML object>"
|
| 166 |
+
]
|
| 167 |
+
},
|
| 168 |
+
"metadata": {},
|
| 169 |
+
"output_type": "display_data"
|
| 170 |
+
},
|
| 171 |
+
{
|
| 172 |
+
"data": {
|
| 173 |
+
"text/plain": [
|
| 174 |
+
"{'Door': 0.9960601925849915, 'Window': 0.0039397478103637695}"
|
| 175 |
+
]
|
| 176 |
+
},
|
| 177 |
+
"execution_count": 13,
|
| 178 |
+
"metadata": {},
|
| 179 |
+
"output_type": "execute_result"
|
| 180 |
+
}
|
| 181 |
+
],
|
| 182 |
+
"source": [
|
| 183 |
+
"classify_image(im)"
|
| 184 |
+
]
|
| 185 |
+
},
|
| 186 |
+
{
|
| 187 |
+
"cell_type": "code",
|
| 188 |
+
"execution_count": 15,
|
| 189 |
+
"metadata": {},
|
| 190 |
+
"outputs": [
|
| 191 |
+
{
|
| 192 |
+
"name": "stdout",
|
| 193 |
+
"output_type": "stream",
|
| 194 |
+
"text": [
|
| 195 |
+
"Running on local URL: http://127.0.0.1:7860\n",
|
| 196 |
+
"\n",
|
| 197 |
+
"To create a public link, set `share=True` in `launch()`.\n"
|
| 198 |
+
]
|
| 199 |
+
},
|
| 200 |
+
{
|
| 201 |
+
"data": {
|
| 202 |
+
"text/plain": [
|
| 203 |
+
"(<gradio.routes.App at 0x28cb6dba0>, 'http://127.0.0.1:7860/', None)"
|
| 204 |
+
]
|
| 205 |
+
},
|
| 206 |
+
"execution_count": 15,
|
| 207 |
+
"metadata": {},
|
| 208 |
+
"output_type": "execute_result"
|
| 209 |
+
},
|
| 210 |
+
{
|
| 211 |
+
"data": {
|
| 212 |
+
"text/html": [
|
| 213 |
+
"\n",
|
| 214 |
+
"<style>\n",
|
| 215 |
+
" /* Turns off some styling */\n",
|
| 216 |
+
" progress {\n",
|
| 217 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 218 |
+
" border: none;\n",
|
| 219 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 220 |
+
" background-size: auto;\n",
|
| 221 |
+
" }\n",
|
| 222 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 223 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 224 |
+
" }\n",
|
| 225 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 226 |
+
" background: #F44336;\n",
|
| 227 |
+
" }\n",
|
| 228 |
+
"</style>\n"
|
| 229 |
+
],
|
| 230 |
+
"text/plain": [
|
| 231 |
+
"<IPython.core.display.HTML object>"
|
| 232 |
+
]
|
| 233 |
+
},
|
| 234 |
+
"metadata": {},
|
| 235 |
+
"output_type": "display_data"
|
| 236 |
+
},
|
| 237 |
+
{
|
| 238 |
+
"data": {
|
| 239 |
+
"text/html": [],
|
| 240 |
+
"text/plain": [
|
| 241 |
+
"<IPython.core.display.HTML object>"
|
| 242 |
+
]
|
| 243 |
+
},
|
| 244 |
+
"metadata": {},
|
| 245 |
+
"output_type": "display_data"
|
| 246 |
+
},
|
| 247 |
+
{
|
| 248 |
+
"data": {
|
| 249 |
+
"text/html": [
|
| 250 |
+
"\n",
|
| 251 |
+
"<style>\n",
|
| 252 |
+
" /* Turns off some styling */\n",
|
| 253 |
+
" progress {\n",
|
| 254 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 255 |
+
" border: none;\n",
|
| 256 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 257 |
+
" background-size: auto;\n",
|
| 258 |
+
" }\n",
|
| 259 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 260 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 261 |
+
" }\n",
|
| 262 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 263 |
+
" background: #F44336;\n",
|
| 264 |
+
" }\n",
|
| 265 |
+
"</style>\n"
|
| 266 |
+
],
|
| 267 |
+
"text/plain": [
|
| 268 |
+
"<IPython.core.display.HTML object>"
|
| 269 |
+
]
|
| 270 |
+
},
|
| 271 |
+
"metadata": {},
|
| 272 |
+
"output_type": "display_data"
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"data": {
|
| 276 |
+
"text/html": [],
|
| 277 |
+
"text/plain": [
|
| 278 |
+
"<IPython.core.display.HTML object>"
|
| 279 |
+
]
|
| 280 |
+
},
|
| 281 |
+
"metadata": {},
|
| 282 |
+
"output_type": "display_data"
|
| 283 |
+
}
|
| 284 |
+
],
|
| 285 |
+
"source": [
|
| 286 |
+
"#|export\n",
|
| 287 |
+
"image = gr.inputs.Image(shape=(192,192))\n",
|
| 288 |
+
"label= gr.outputs.Label()\n",
|
| 289 |
+
"examples = ['door.jpg', 'window.jpg', 'doorwindow.jpg']\n",
|
| 290 |
+
"\n",
|
| 291 |
+
"interface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
|
| 292 |
+
"interface.launch(inline=False)"
|
| 293 |
+
]
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"cell_type": "code",
|
| 297 |
+
"execution_count": 21,
|
| 298 |
+
"metadata": {},
|
| 299 |
+
"outputs": [],
|
| 300 |
+
"source": [
|
| 301 |
+
"## EXPORT\n",
|
| 302 |
+
"\n",
|
| 303 |
+
"import nbdev\n",
|
| 304 |
+
"nbdev.export.nb_export('app.ipynb')\n"
|
| 305 |
+
]
|
| 306 |
+
},
|
| 307 |
+
{
|
| 308 |
+
"cell_type": "code",
|
| 309 |
+
"execution_count": null,
|
| 310 |
+
"metadata": {},
|
| 311 |
+
"outputs": [],
|
| 312 |
+
"source": []
|
| 313 |
+
},
|
| 314 |
+
{
|
| 315 |
+
"cell_type": "code",
|
| 316 |
+
"execution_count": null,
|
| 317 |
+
"metadata": {},
|
| 318 |
+
"outputs": [],
|
| 319 |
+
"source": []
|
| 320 |
+
}
|
| 321 |
+
],
|
| 322 |
+
"metadata": {
|
| 323 |
+
"kernelspec": {
|
| 324 |
+
"display_name": "Python 3 (ipykernel)",
|
| 325 |
+
"language": "python",
|
| 326 |
+
"name": "python3"
|
| 327 |
+
},
|
| 328 |
+
"language_info": {
|
| 329 |
+
"codemirror_mode": {
|
| 330 |
+
"name": "ipython",
|
| 331 |
+
"version": 3
|
| 332 |
+
},
|
| 333 |
+
"file_extension": ".py",
|
| 334 |
+
"mimetype": "text/x-python",
|
| 335 |
+
"name": "python",
|
| 336 |
+
"nbconvert_exporter": "python",
|
| 337 |
+
"pygments_lexer": "ipython3",
|
| 338 |
+
"version": "3.10.6"
|
| 339 |
+
}
|
| 340 |
+
},
|
| 341 |
+
"nbformat": 4,
|
| 342 |
+
"nbformat_minor": 2
|
| 343 |
+
}
|
app.py
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
|
| 2 |
+
|
| 3 |
+
# %% auto 0
|
| 4 |
+
__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'interface', 'is_door', 'classify_image']
|
| 5 |
+
|
| 6 |
+
# %% ../app.ipynb 1
|
| 7 |
+
from fastai.vision.all import *
|
| 8 |
+
import gradio as gr
|
| 9 |
+
|
| 10 |
+
def is_door(x): return x[0].isupper()
|
| 11 |
+
|
| 12 |
+
# %% ../app.ipynb 3
|
| 13 |
+
learn = load_learner('model.pkl')
|
| 14 |
+
|
| 15 |
+
# %% ../app.ipynb 5
|
| 16 |
+
categories = ('Door', 'Window')
|
| 17 |
+
|
| 18 |
+
def classify_image(img):
|
| 19 |
+
pred,idx,probs = learn.predict(im)
|
| 20 |
+
return dict(zip(categories, map(float, probs)))
|
| 21 |
+
|
| 22 |
+
# %% ../app.ipynb 7
|
| 23 |
+
image = gr.inputs.Image(shape=(192,192))
|
| 24 |
+
label= gr.outputs.Label()
|
| 25 |
+
examples = ['door.jpg', 'window.jpg', 'doorwindow.jpg']
|
| 26 |
+
|
| 27 |
+
interface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
|
| 28 |
+
interface.launch(inline=False)
|
door-windows-detection.ipynb
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|