create fast food classifier
Browse files- .ipynb_checkpoints/app-checkpoint.ipynb +374 -0
- app.ipynb +249 -0
- app.py +23 -4
- export.pkl +3 -0
- export.pkl:Zone.Identifier +3 -0
- fries.jpg +0 -0
- fries.jpg:Zone.Identifier +0 -0
- hamburger.jpg +0 -0
- hamburgers.jpg:Zone.Identifier +0 -0
.ipynb_checkpoints/app-checkpoint.ipynb
ADDED
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1 |
+
{
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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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"id": "c68144c5",
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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": 1,
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"id": "ad76e8e1",
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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"
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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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"id": "b395a732",
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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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Hdhw4EJEhGAAwI5Fn59g58p498pa87g2ViJEJ3Wu8oghMxD0RQL0vRDMjQGICYzPL0Nehtol6j8TfgMyvwRD1bqqvUZghbgmq14UpADBThYPbD6bj0V//0b/883/7r86evmjnm65pYxs1S7pcxPWmIJtVcDgYeqMiuHHpqYtt3aSYk0pGFkZDZmIgRnKGAGTbC9A5BBOzo+9+MLn34PKqBaas6fitd48ePJoeHs9ms2JQBe+qsgphxINBKGdUVd4BEWGCy6uzX/7ir50rquleTgaaAAxEwEDRskhvQzlFUwveDaqKXV/ds965tJvG9WC5v1hD8CEEAHgzS+9htYh0TRM1PTgIv//e8UGBn193Fyn44WBvNCiKIhAzIBIC9N7cDCD3p/w1tUMEPdfXnyRjZia+OVME9Dr9ZuYQgveeiQBQ1YAIiBxx/5WY+yorqvT/SH2QQkCibXQiIkBySEwMfe0RzMwIoQdVqiqiO5fT45Y+Bu1wzK8gNtUsIn0E3RlWbzsG3FsVAiFUg+rw8OD55x99/sufLk7PmsWq2cSUoopITgksIxZEqCJZqhAKZOu6uGkkJRBQAENgF8j7/hBx0AoFRaiqRsMAqI0b4PCYpndAq8Gw7Dpbnj754uUfL956NXvw8NbD+0d37+zNDsRJomgJCZ1DhLJiB1TA4dHB++9+/Sc//XPyGPxYTEUFsiKAoOkNdyNqagYxFSEQMRH2hCQj+YlzXdfBTfmiDxy99bxG0EQpdW2bffC/fb/6zt3ppu7++spSMR3Pqmrgg2Pu0TJAH6/ADM3QYJt53cQsIkTsK+RbvEvI26SKGQwMAREds3PbiAkAospMzjE5j8Rua3N9DUho5xbwDTNAAABGBOLu/IWcf2xMYXgUDh+wH7qiIO8QXJaUBRABmfAN8hpNyaDna/tMrjed1wELABANEHHrD8Bo54qYGRn3Dm4R4vPnn56+fFKv6naz5dg055RzR4AOAkMZQlFw6QlT7OraUkpmYigExMG7QB4cwhh0SFAx1su6je1BxU66uMT27HRx8nJz+1Fx761qejAY+OXyenHy6ur5s/XZ2+v3v9Y+fPvozvEIgRyQL1g77CLaiIMrBnzrzt3j8zvPHn/68P7X1FBEUNXU+uqrioIoIzpCAlRVkV4QYXRDuDgA6IFLD5p6AqMngYjITJsmtjm/ezD4vfcP94v8yXl3mbmYjsbDQeFcf3G/RsgAYNDnXEZI+CtUXm9DRMiMzEjomJluMAcgOOecd55d70J21RXvPTMpsAGKqpqRkXMMSDs+b/cRW3aG0BDLuHo4PavKC5mfX55f6MVUy1nESqb3de8rWB47F5T4zdIHABACgiEBEiDgjZhh673gV26qar1yw3qGlLYFztF40rbt9dlZs1xu6ial3nNpiimmpGJDx8MA0yoMmSF2sWs1JcmQCTMSeO/KULAVmse+CI5YFAIXs2nbpPMFHB7ei1dP0mojcVl//uRq+tPqq98c3X/74PCB4+Llz3/87PRp+/zz7t1vtl/9+v7toxA8mxUqLtZpXR+8/+7d3/r7xcC/8/bXz16+vLg4mR7cMe3r76AiAABqaIBqBorO9TgHAFStB46I6HbkctM0fR2+KApm7mthbcqO4Lff2/uttw9X6/ijl6kLg8nRIBTeOde7VsA+UO3sx8zACPvH8aYggFtWpj/hjvB1yYmYnCfvHbtww61grwZCJiJUAxUz0DddzQ0T09fJ3yiDA4ABqylz0V7ePeqmH/ygWzwvvvxhe7kBccv6VT57Itc/i8UUjr9r0w/IjRDNUGnrAoF66iGJmhj02RkQ7QAyIBiY9UVxImICYgQ01awKoSyqwWBzdrqeX7ebmJqYcxaxrkt1vclZxkD7wR+P/MijrBvpkoiomhhnRSUuwsCXPD6+NxLQ5QVIR0QQxQOMfFh3sl5IvUHNGM0lte5icXnxR3n0k8NvfevwK9+dPvjg7NOfvPrx3yw//Pjkz/7dZFBRzra+LnP0VTV59NXRQYXTvfvf/cH+7PDBg/d++pM/m0xmiB7AeiMSEVExMDVFhJ1oLOeMaO519uVcLxPLeYugvfc9KamG+0P/Bx8cvHc8+vjZ8mWNYTqZjqrgnUf25PrqEWxVI1sOxLaE3db37OrkN2e3d0PcE0LMFAoeVGUoCgCQbcKIZiamZso9g8MOkflNlc+WzDGAX8m6t2fXDADIlMIkjNCFkU3endxahMF8OV+wICo57mz+MWwe0+gndOv3cf99RwNz2UABLEsyJTMwIiC8Ycxfo2kwQRMido6JEEBUVIDBEIBCKJidSBRNXZckZlVJKW/qJsZYAo28HQ2KgeeuXaeUIYkaZgUzFSI3Kj37AouQBdsNxo11uRMFVESQrCgyXy1AIKnWRi1gIgJzqam//NFfXS9W7/7m33WD37j+8sPN88f27EVLWCA5p8mwWLY5famb+7/45/+n4aAav/3tvYMDTWm5uJrs31E1A1ARkXwTuKX/yT1faGbb5JgdIrs+S38zUc85t13TSfr6o+N/+M27lJu/+PxqY9V0f1SVwXsHRB6Ie7u5uRxtq8O6SUV6v05b397LwRAIwBDNM3rnyIeiCEXpvQ8AkEVMERGtV1AxGRKywz5jv4lQfTmjr9bDNkUyAEXsq2AKYACGRgRUHuyVewNdf+nLPTe6NS2n5i81a7NaKVCY7DWx8+sPLZ+R/YD2vx9pJgaw1XL1eE5RX8dnvKEJkMA536O0nAXADAjRAMlAiNUHRCLng+Q+HbbYdqmLZDQkHhACSNdKTiZZJYMYZABADoUrCk+hnB49pItf5qalqJqzmhoRsQMjNhPDhJoAs4EAKoKimBmKnX/2y8H+3td++w8m9+4+/+lfNJ9/FsGgKKEqyAVidpIvTr7cPP+r2RC+87/6r0ejWTGs5ovL8cEdg5791l01Yldu2oEcRHCOEUnV3K502pdFRXLbRa/hd75z6x98+9758+u/eH6t5eRgPCoKv6N3t54GQQHAbGtMYFsf0yNMIKAe8yAiMbH3rnTsQ3AuIJIAAWCKJikC9+ilz86ImYAJiXsaiG+spwf/1D8TwKC3NuiLsNCfRjZG8kxELujamhdo69S0DhKE6eTWoStmq4tnoL6tO26a2DCTd8uPc3sCw6+50deyHxnIVn9rsOOlb/LH7X96cnbHbBEZ9kffTDUxw3Awmk6PHHkzyCnHtoMswUHpYFoGh5ZjztmyaFLMipm5LMtyUqIvD77+g5Dq7lnt0BmqQG+aJAa9pkcBsmECyACyzf4EAFnRG3z513++uDh96zd+8+G3f+ticDgIfm84aq/Oiqk/uH/H2s3i0yfrD9cvf/7RB8u5D5OyGlycvMRe1iG5P5UxxhuOdKtT3YonRXozEBHHNyIeEelS7No4GLn/5Le+8r33Jj//+OUvnjc8mo1HQ79Vc76Blc16oSoA5K1L2ALam4x6qwMlRO9cubW/YAZJtUdo3Hsc7nndLfvSmzK5XmjV6xC2zgy2eHWLkWGLyukm9zIidM71ih+BvOhcm8nbEsk7P8ZwDLoZTgYhPBSR1XwhF3UYHKAbdG0Tcj1Y/2gz/0QOf02H7wOBZemFowjYl88YEYhE+4O5zSh7w7rxWIBmse1AZDAYHt9+MBjPsr2IKSfJhFiAjQuqgsOUsqipiXE0zIjM3g2881zde+/g279b//JPKBEWbA5UUcQA4IbzpqwSRRJARhQzUTNCAwLo/8inn3zUrq9//Q9+u149j+suocH6shwwre7n1L38m0+ojtP5OrU1jMcM2tSbnFoFMRMzSGkrft9Bn21WL7KTxjvnXO97cs51XWeJx7f3/8d//2vvTN1f/uLF6dKmh/uuKpiJcUup9VoLBgBDM0NDI8QbFWJvW7uEiIEIERwrYRToRBATMSGh866vqvcyCybfizQQX5PRW9xNpIS7ajkDIoBuIx3e+DtgQt8XXBHFLKsQYGPFaTMbDeaW10ARbFEUe+aHxOcxbWbjW0bYXD1pN4u2adVsUI0on+Hnn/Ph92Dv6ynMFCsC9ESeHSCISM5J7CZ736YPuLuowADBUtu1dVMVw1sP3z58+OijDz8UEQUISANyo1AQkQIZcgZJZpFQANijWMpRUZ2MJ9V77y7+yqOpgCVEAQODZJYNTEEUOqUIltEygQBkQ1M0wj4FcN7nevPZn/2Zy2ai0YRN1pdp/ulLEVVDU10nVSokp26zibnrckcIABBj17NdO5JZVdW21tMTPT3o3HZWpDbGnL/6zvE/+0ff8bH713/y6XkXptOxLzxtReq04yBFRMzwBgCZ4hYeqxAhARmYEXpmZAZCMxQBNej9kXO80/HQrvZOzO6Gh0bqjekmLSe6EVdgn/Eh8LbhwRCMrC+GMwKoioARUl9hN4arbnDL0xBdjorcgA6UB+AGjkj9uJgcQ46Ka/KzZnHZrTvvK+qu9em/CfVTd+s30+ARhqEiRu1A6aYw+6bR9GSjvjYpgxjjfDG/e39ydOfBt3/wg1/+8K/W5xcBoWAaOGbEnIUMMpoxZ7YMoAjCvQst6vq0u770F/NkuTMwUQEQwl4rnw0ERIAScQKT/oIhS6pKBowEzAQcQuUCrhuH7MgkxRyTdbm3HjFG0eLonq8my+urxXKOPWGH0LVdTsnMRE2kJxTN1CTn3nq6GGOMfaruuq7ruhgl/9o37v8X/8FvNGcn/+qvvtxoOZ0NQuFpm2P0zgZA1cDyjQqsDxza070EyEQ97eucMSqimaAS0+ucj9xrBc9OfN27HOd6xScSvmE9W6Hga1EO9CZkgAZ9IwYRgYHkbGaIRg6JyFHPSAY0vlxUZXlhKXN5C8xLnJsmNPaiw+lbhAMqLtr1depWOUZ2HIaHSdbUnY02P+/a5+vqtpZvGQyR+sYhhD6kvVH22gkpb/7E5dXV3fv3Z/uTr3/v73z/93//+WefQxcRQKSLGUCV5OYwOgLA4Lm/XGNWPXlWf/oXdv4CHUM0VVNEJRBRNcgAii6iJrJsZMpgZiZGYAhIQAQDDj4Eh9AXljSJRMlJSCwDmrpsph7v/+bfpxBOXn5+cf5quneMaG0bU4zQu4kbcb6ZqkBOIiIppv5Q55zMzLVt04r8zq+988/+4beeP335b3/0ZfKj6WhYBOec/5VikJnqjZJviyh3xDETEzExMe2KprCtdDpm53sQ5Zx39IbCa1c05a2Uh3pu6W/xOgjbphaAGzjSwxxCMUm5UwU0JObgnSNmx9iju/ULOvn5avXZs/wCQjH7Go9vP2A/FhMCyt0Vl7d8OZHY+bIL4zE2jYkNDx6qc5hSt3qhdlo1L9V92Q2+lgdvqSsYFIEB+svqdRPImxI5QmzX62a+HOzNbj185+//R//k5ePHf/zf/nelagJKWT0zEBiYiDDxoHS+CGKCaCoJVC9++G+npScOSrGvCKlqBlDEZCgAwqwIIMCMisSAgQAdMRM7cNw3c2SvACYpZxXNCoikQIpgKtN3H33t7/3j0/PTzz/72XK5vH3v/aZpchLJWc10B5l75JNVRUVMVcH6YiKomBOiv/v99/+Lv/fNzz55/Mc/f45hMhsPgnc79/AaNQMYoenrlKSPR845RjJCJezz6T5N2VlGrwzjN4xmd4ff6H9ARL5Rh98IlG9IAUA0UFNDYCRHREwiGpOq5HY5h8uXB4HwwXtUHTpCNZSY/Yu/qh7/93j5LOa48igFr1avHnzn94b3voFUAKi1UZcfWzZtGmQezx7ZBOvlE5Ml8oSD51BpXGFa8PLULT6y0ddk/3s6uMNGBmho+IZGZcdC9XRa1ji/XlA1HFaDR+987T/5Z//V4vLqo3/7hw6hTkLODQpPaAihLAsoHJhJEms6R1Q470A1iyKp84akqooAxADICL2vATNWI0JDcuDJYV9qNeuTcQNVExPp0YuK7tQRlrx97z/9p7Nbt37+8x+/fPwFgXdh0DVR9XWq1d92rVpmisAilmXbOSeq7h/81gf/+R98/aOPPv3jn73EajQeVd67XevgLkd989Z7Dd4Se6hgBgqGCLyrS+3ADVFvPtvuiV9V/PCNIb4h4cBfqX7DVkqEvasjR4ykIjFnUQUkaCM9+ekxXB4M0RJeR05uVKKNzp/SL/57ufrUCkcDry5T4aW15z/9q3uoxcG9KOp5Ju2lWC6GMxe17ZZIWBYDM1FIAM4Vw6xKph113MWQfpbr5/H4d2nyFfUjA9pmodqjfKQbmiOlJAKbzSoslqO9vels7/1vff9//r/8X/9fDD7+wz9cx7YcDpIpZi0LHxgMjINTps2mMUAAE4AmJer1K4RAjASoSACkqmoomUyVCIgBlU17a9ZsvQKsB8CiKlm2FVEjM1A0EX34e7/1u//p/+zl86ef/OLPLi5fDYbHANB1bR+zervpOcKcsqiBGTGZmvTZIOC2ref//r//Lz/66Mkf/s0XUIxG46H797zCm3d293e+2szQEW0zqm1ehTdaUrphm2/qWcze4U1xw910hL2+oX/zswAAUIlwq49GE91qjZEImUAtnH50mE9nt2/J6qmV2JYPIj+abH45uvy8nT/ZnL+oa0WvOEDzJfjKzMJkePf97xb7d025ufwcsMRiKgqxW2bpHA/BlwYM5aGg69aXm/PPNK4DOwwTy3Pp2mb4Fd37ro3ezQRswMyOGZn0poMTEYj4YP/2bO+4mh4MJ0NEvLi++vLDn/4//uv/81/9y/9mbDgu3djjKKBHAoC2k5iiGflegUDIRGDAqIRABiZbsaxK0pQACNkZMSADopiqmTlGJk3bxr2cUopJRHuTUgQwq8UOv/6V/8X/4f9Yzm799Z/8648++Uld5+P7bx8e3t2m62amumOYRUxlW8bRGzJ+y6gQu1/88vGf/+Kp+vFkNOi/eV9JNwW8adXu+d8bRg1ERMHMtgC2FxTfZOCvAc3OgBy7na3cJFWvC2Q3LE5/sfWFmNfiGt7qYllVDJQIvfMAgATSpWr94u54Od67DZ612MuqlTfQD4N+TNWCcBJGI7p63syXfe6Gjrio1PD08afHfhg4aOxyu1SeU5h4V5olRGNXtJsLosRu6D1J3mBcaTkpCu+L+5v0pNx8Glcfx9EHePgDqg4NOCpqcki72h+YQc4px7ZdLwFpPBrc398ffvMHk//N7be/8cFf/It/MTh9WVpnMUvOqBDKshoMQSwjoO9BBpoZ95SpyvZYAaBjDUHUtE3ateC4rwUCQDkaYOHjplNVUUHA2OW+lzeBmVprcO/73/+n/9v/XTEa/+Qv/tWnn/2i3ghxEbhq2zbnrFnUVG/kiNoDeKScXyuDb3JlBED8R7/+lhWjcjzoQwwiAilAT/K9hs+vo0pviQjAxIAOqVdv9VXz3kr693kjhBX9I30WtgPOvZH1DWIIjoiQ9CZK8k5q2Pu5rcERgZqpmkix+PxhdTbaO6DxLQaR5rlwBVS51S+CrmCzToslV/u1NbHr2iZ2jbY5Tw8Pc+5iys672ezQcZW6ZUpRlc0P0OPw8KtqUF89BlsjV8XhV6+efxabM6RiNLxjZM3mJYqadEI5hfub6jt1+RaXZeDChW3HSH+sJuPJwfSAXREGh1QMxkNfVm7TxuuLy6cf/fJP/7v/60f/z38Zzs88AAxm4/vv6dWXBVunuTiYqvHmag1qAODE0DIzOaJtnOpZ05xJTFRFc0YTUciQHSs5AxMwNIyirUoXtctC1fDb/9k//cf/5X8lcfHjH/3Rky8/X25aFVeOhsdH9wUpS0ZRE01bPl2ZGZFN4c104aZN3CGgk2I8Gg563EPEAFuCR1SzyhYbcq9HRwSgm5y6V6neuJ9fyad2voeIHHnu28FgK9/grQYId36w55YVjaFnJd2uPRTfaANSVVLtP9bVF3fg2dB3xegtv3+szUkG78Iet7EIwDzscqTS5XzO01vVwd0Atjh9kc4Xly9eDSdM5cSEllcXg2EIrkhqspknWLjhXrc4Q4RQDTUpYUCxanaHixGiADvnQuEfujBMq5daz93muVu9Yrof97/bjB55q0rnVQEdM2KKMYsC5NQsWfMihdiV43FBx7fIV8dvvff5H/yP/vq/+b89/sP/7+z++2728NYHb19+/BN+/MVqVUcFdkUoSnLYtwmrkhKXoQCAQhJIRjOTbJIlKogZQgbaktu2zVpBM2Zw4+rhb//B7/2T//zB17/y/MnHH//yR69ePlu1UYUcB3ah6brcS+jVTM0I4CY43KRdN9ZDN01PgIjoJrORc84jMfGWtAYTVRXdaXz6pxptlRsEaNsaF9m22OB6c3nDgPqG7+CYkKCyZcUSbZhhCK6nb3YNGggAyMZMlQ/OkeQtOO1dKN3MsiCkvtihiDPcTMdSzY6J59J+aharo+9lAUo/Bz9QWflh6YpjhRAtsQ9QjcmMc33VrWIMZQFRBcnats2sZA5MJUUQ7hL6ULjxoQl06RLaLqtxMfXlGCSpxenBu9lVsZkbb6IRxPWEPouXZ03z9fXka3l4t+Lo0hJR496DnNrgipSblFtfDjXFuvHD0XAyGVeDweT3/wdf+bVf/+LDn330p3/84f/n//3ge//YPXu66T4lBUIQIAuFMwORLLkTSBhEokMD6ygbgOtBSxQQRAVSQDAENVNTEUNw+9P7v/nb3/4P/6NH3/y1+fXZX/75v3n55PP5fNHUyVQpBCRnGJr4unABAGTUp0g5Z0TeJZs3N9qpcbbtdv3UiW0vGZiZGt0kQNvAdVPCREDrecMbW/wVyRgh9lx6H7wIGILlt4fdo7uDdWyeXV9v0jT7A8CAiIxbSZl33nsHqCKScj/3Y+vd+vjFzAi46/tyo8rPHpb3vpFS7SwJJOcQHBpkjRlyhz7R6DC4GROktmGgau8+GAB/6d2eoOaLV9GA/CRywGbJZelizutLadddKIN0ZklkzXBdr5bl5Lab7HM1AvTAmNYvNG4slNXhnqYIkMrC7dOry818kX+9kE14+Sepifqd/6wrBgMOIbiUY1w1IeyJFCkLey6KsqyGhfeDHxy+9+3v/84/+Z88+dnP6vPTdZc2zx7XmyuKiaBmot6GkChrzik554QoiIB0SSUbKqJRX3QwEegA3HQ0e+8rj37nDz74vd+e3j6+Wlz95C/+f8+efjpfXDZNm2JSQXIebzQxImLay4+3aOH11Wu7MvnWCfXMovVynf4feuDdKzMVDGBbGmTAPtwhbNWbeANwd+k1vVECY3KEntAxMROyAwA4CPn9r797cOuW5M3s1ScvT76UQDS4s16dCU6z2wMzNW1uevL7JAtu5s7sgHzPLhohAYvbowFTcKGaSXtuWVL9GIEt1XGzKGijmGHoioOHaMbNWruNpDTcv4/lEA3azWJobVc36BwTtkoRjNgJoLQNNOu4usQilLPb5fiAio58YYbtZoHsyn0ARC59UR7HbgHWDWZ7w+nddnMxvP7QaWPRmTT5+jz+8k+L6g6bG0yGzjlJXZtOMU8gDCj6uGlc8GVZBuYwmA5CdXR8++u/9zvN5fXpk6cnn/7i5ONP10+e5vPTuLqS1TJL6jSLmXWZDbzatuveI4UCQ8mT0fjozv7Dt46/+Y2jD97fPz5OyU5Onv/iT356+erl/Po6djHnlGINCs55IK8A4EhNTY37+p4jIuqhC27nI+yQ8FbXQdTnJAaGjolUDak3K7M+3TftTyH1TRQ3iATMenPRm1JQH8p2GVYvzrtprmBACJrvHdrB8T4XjD4c3n2HB15ywKBLu+6aZ+t2vNT74mZvNpvv8rXX77xjExDRNGHotCgZyVeQfECH2Eh3xre/QsOH3elfotYlTwADkFIRRDpGQJOqGonEMPum8S+g/VByEiOTLEnMD8vJcbNcmmQF4BadmwJXZVkAg/CQNaf2Oi2eKMvw8CFFi+sIoqvzs7iuu2YtyJzPBQcym+RNvn78yzx4K77/vbqbTWYj79FE86JWLnh4ABxizuvNmpC8947Rez8J49Hd8d7d++9/7+90bddsls3iul5cr68uu8W6Xc6beh1jhJwRmXwoqrKYjoaz/eF0fzAbuUGh4Np6tbg+/+mP/urq7OTq6rqulylnMMsxSU5swEyApIZgQEiaBXoJODvYhq0ttDADBcWbkU3wxnQ2EwMAx4CEkFV3TSqkBoCKhMyowM4pmhJ4RNyBKbBtyQG3TZ3bM02ApMTGhMzMDg9sc++4cpwgiycS09n4sM1dvbkYDSaFtU6ee1wu7d0G78CN9ey82g5IbyE3ACkQ5OQwwUy0CjiDYaVxFdufgrbMVD76jfL4a5vn/y41Sx6tiNC6tihnUbu8uQZtfDGgYlRWUx1OVTS1q7JkhSGNb/vpO77Z1POXsLhqFy+vX35UjWYGOhof+6FPtkpda2dPYDwFdxwhhaP7ua1D7lJcjw7eVpNu/TK2iQTw9gBKnl/+Eia3Y9umdjwaVkVRAGGur7tmCdVeUR1lAJOmhaaPF94hMoHjvkHFlcNJUc1u3+v9ft+sbqYGarkfvpRzSk1bN/Xm1cXpZr1YLuZXl+eb1TI2mxRjajroiwQiqKmnJQ3RgLS/ZIUQjJmJSVUkGb4en9Wjn9cQqD8bvbH058jBVldou5i35Wl6H7INKH3yfsMi3uBq7hs0iR2RY/bOe2bPjj0jIzsLWY7G9Wx/X21N5iWrrC6ydG50ryhC0ktJxh0O07m1S8kpVY/e5DBfB68+OgMYICN655ncqqnDxak/NB6OMYyNSu+agD7HkzC+V956L519Kt3GF5R1YzywZilxA6Hkao+kHu0dD4a3mmazePlDh5wtuvGkGA/zaEQVd1JbGjbX8/VmjojWdQONyWJqYycRlxc6v7LBcP/BV6MOM5orbnfdMm6WkCLlSEHJF2E4uj26s7bLy+vVcrFfVcVkNhrtzYjIYp3W86Y899UhuYEamFnKSTWnnEAVAcUiIRIgEyqgbgniZCYpx9TG2LZdt2nbTVOv6+WyaTZd13RtKynmnLNmUCMDExBRANiyC72C01TVPBJxPxACewqRPN/4GjAVeD100ehmJAaAGSAjeR+cgaiZqN34ICPbiiVQexE7cF+77N+YELa/ivimZcI5x86zc300A+21OlrI5fER+1BZhowRkaEaLl6ui7zg0pW+lFA5X1vXVbCI6z9fLi/z5H03mlrf07EDWCiI0NdkCyJGNLUu6nKD1SiWtETvgi9Tzpzn1pH5jJRdyaqQckuEFBfB+zC9I86ZOaKupFkD9aA8NvlOu/oiuEk5u53TyonV9Sqaw70HYK67urIm5zzPbbLAWVoiNzp4BF02Xc2ffuRGEwqz4EYggiFlBqMNmEhTqxmVflQBBbzu5tdn1fVltb8/Gx/sF6GSrHF+2c0v0U+pGBMPEkJWzUlTanOM63oRY1cFJzlryjnFlHKMMeUu55hjK6nr2k5yzjnG1MauJetF72imYGkrGjfDrcNQBECjpGhkrOZcQQwZtuPrtlnSVqPS61YU1CHxrvbQOxTnyHsHBo6IDYR3KXU/PYUYHW8pnhsosnMGiGCIcNOb1zsHBTUEBiNV750P3rEbgIzKEQKbicUNIvnh4eG7d3K9adcnxXhvGMaAbIYKqYqt1D88X57Y/rfLyYErh33RtZ8Q5JwjJkQUMEUDNg6jlLu2ySEoam154SgAVqG8TZ69G7S6wQS58wBcDIlC6VyZJRk4EAAQZkPG8f5dws68Q1NpriGnqhB366julHNTiKmP64vLzfWSQ6j2jzCUVM6gKDCtcrPxIQiseDApeQaMrMPcVpZiNR6szy+Ni+Lgbjlsjr27uJ6/eHH57LNX4XR0dHw8Ho6RKUtuF5dKntgZj8yN1DADZtEUoW0VRFLXae5yiinGtuskx5Rj7GrLSURUcs5RJJmqqpjpzenfnnME6Fl+gJtWkj6NIjPT2HWCTEj9rBeVXp7zRsLVV9mIzJSIvXfsnJmkJAjm6i7pjb6n15XKtmxCCODU+jFifccPIioaIPVD6MCUjQxBCRgpGPrgvfN95kSAVVGULoBkxMypbeZPB4df8eN7xeGBH1exWbtyOi6G4J4CEXLth8qLfPLqh69ezIr9u5OjO6PhhAIYkIgKgwv+BlgHZrUM88XawKazMUJJWCMrynVePYemZhuDa4EGuc0x5wJaIQI0sI6Dl2wIoKkRydXsWMG182eO1hhK8pPh8K0qpcpzXZapadSP52drytG7fUnL3GwQncPSMFs24yTSchhV/kDQN37lS+/DbHzLkkgInpxpWu/PYDYaPn/afPjpl/OLk4OD4+l05gYlmFpq2pyynHRGWUr0pXCRI3UpovjUJc2qmrumTV00y5ISiKqo5gSSQDNI4l4nbdnsjTaAHrEiwLaShZlIRIwom0i7ZiKmAORMe0UoGZL183QUCKCXq4OqI+cDI6OIqMCWKN5NzAQARDWj7VxU1X5CzS6l3zEB/f2tfqfnDp0LIXjyvf59K9IjAMCcmrg5RwYyQyNcL1Uz4kPhcSi8ELniaMZcunJ9/Ty7cnxrOruzPn327OWLH14vjtvbX6uGsyIURQi+9EDYDyPDXhzNLslwtU5VtS6wBH+MfqQWQUhQ3Ox9gw12Dbx8smmv4WjoJxpG+0Tcz1FgIkZjVSkmrrplgG7tqDwQiWE8m5bjV/Hc8rUDwtsHo3tvXXz4i1dPPvcQLcZiMhgfPCxmD1xFUZq0WaVYF6NZUY1dORJLWckPR6ULInW3PM/dwjMQtbdvdbBZfPThF89On8+nx5ODvTAekvNKXg20rSVeptR1Skl8ndPGjdAIuBDNmmLO2TRnyZKzSFYRzVkkmSn2FQeDHfvaD3voAS5uM3AWlW3CnbNZJ8TMwCwud8iUmZDQJAASAxMigzKzdyUx5ZwkW88IGoD2Y35734OIRHAz3A0ZEG3bpq4EyNw3XjBs5/D6XozvHAdP3iGhoooBGThiT+ycq2X4+GR+t8nDEXiH7GfxeqPzSxApjr6pnlEVJJKCIx3NRq0E0AK99yEcHd96eXp68fKHq/E77fR4MKyClUEL8wV6IzZjQxJD7DKt5zGMwAZ3gUBT7f0UTLW7VMtBWU5frX704+b2YPyDb3DhqNh3XDZxyUUFsdOidM4IEg8mrUWQlikD1uvFqhzcXuszs85TV9fz6e2hP360vJovrr6cEDh3zsErzfx4T2Jt7ZqNAb1oRLCivGXksCyrcEBMqZx3zULXr0zWe7P47ff5xav5ydn88dWwGu8Vw0lRlWEwMUDNIl3U2MXYgcgmSsqmREABrI8yhsRqKVkiUcsiEgEy9h5AU+9xEFFMDA0AGZz1FSEwopyFLBtSQgEiVaeoJMxmRNrjIAEAIWfsyHlAStJBjkiIzIBggEao0A8623J0RPRaD7/zNDdOxxCIe8HpVuHD/QtU1USJuO+42QqcmQnUqHhVT6KsHhEWnKuiRKgBEqbMYuxLAFVNbdtAioPJLR+benNRhiM/3ncQHxS398fXV4sXi4uLTX0rTfe1LKwYalGJ894ju35SJy5qrcpcdHOCGmkA+ZpkmZozArUUGFcFnTUvdflT9ljQfS/g2A3QuyxGmJnZoDXoyqqSKABgskimnnm0/5WlZJI6IEWSg+n+7O6960+61XzdXn+xvnw1uf9WEQ/dYEZu1KwW1NZcBCalRGQKWmuRDN3w1rtV1OXJJ3LxoStgclyNb9+7u9RPPz55cvJFhKIcjAbTfecL55wYiiiKWsyQNpCj5k4EJfcTl4iIFc0Ast0MI0CEvinOcu/7b9Rj25E3/dPUVAxUQVQZnKISkqkYoqKKCm21oJmJuUBiNLPYRQTH7JkIRZXIEAHN+hr4jrV7M3/ekY+I6IAIeDfwHAnBAEQVQU0c9hN7+2oxERE5JkYGYeJB5fdKapdny9TdOpiibNCbJ1SpnXrHQZCKqhQ+MOKqrAC4blcOy1CO3DCEYjAeXlycnDx/+WV7fRuO3omjvVTWRSh88CGw9w7Rt+DrTANzwLdpeJwXP0/reUpN0Eg4S7ygygLOutXq4uc/Kxfng1v3y727ZmTeOR4QFKodhwKhSOUYcmftYhB4Xefq+LiJp92iG0z21a61eZmjlNMqusny1Xl7sWrbzw6/Wg55EgZVclUWZ60J1jl3FYvJiFxwANCui/JwdPQQtdGN01SnhNPD6p3kpxV+9nx9drFcLRdFWbkqODc0QAVLOauaCmg0MEFVMxVTIUKgvsqJTGbwujptCv1AbaO+EAFmSgkAs5iYKlGWbBaIDCCJCkEwyxn60bw9c+z6cQq57fphY0DZwNTIEEF6I0PpNy68yd29aUY70SAR4W7gWQ+lGYCRd7LmLdcHvTAaiZCQyfarfG+io3KqsesWl+vrJyZtOZjhcC7xiliMCtAcqKlBczYExxwKWsZ0wb4I5cQgow2PHz304dXLLz5bXX05OHrbDh6m4WEVSquCDYsisHfDpmnTcEDoGDnxAJM6cGaNrp7Esxe5IxkS5azXl6vVdf38pHr7K9N7b4XRPoWZgQTlnDI45q5Jkpg95GYYKMmycOQm9wBGk2raLs69VxlatZ+m07vXF93m4gU+edKt1+Pbd8e33vHsChc2y2fN8lQ0DWe3Y+OcI4MRllNfjMP+XSxpffXUsIZo1cgfPxiPD/Dxs9XHn1/Ol0yld65iZnJVP84IsqhsNYUiYnRTjlIAQtObB/42VN3OLDAwFVOzJGYGGXIWY3YiwkyqYCpAhqpISIGJwcBiypiFmQ3UMjElpeign5KfULOaodTO9ROZ3HbI8s797AofOz9Eb9z6DlJH2+lOHrFfPOGRHTIiFYyHfnVUXgWLSLfd6F7pJ7neP3v6uGm6wxmYYYorx5lBs9QEUcUBmOSu9CNC69q2XjwNg2OqDoq9aTE5DqPyxadP5OxzW5+lW1+nybFzE6cFK6jkOsFi1R2MY3f5hW5OyLvAB/G6SefP0tkqrkzqTTKJplQ63qR15LRuJveOh8d3uRhJjpo3ZDMTdG4MkIhL3Lwio+HkODYbKo+yCTnDTiVnlW4wDnuPDq+fHc6ffbS6ushtY23rRtM8GCQCLPZyF2MTC67Vo0hyvuIwG07vip8kGLp4FetFAa4YJqTz9x/hkIafPM4vl7VpBMfe1Y69IQFiH7BQjbSHyWaqPfDo02wE7JdXZBXyDhEVboZsAEg2UTXTLDmrKhXbVSyoSASocFP8RsOYUNk8ZTJxklEILJeyYO2Y2EHHMseuRjME2YrI8GbbCLwxV3AHg3Z/vhHvmIhpW/va8kVMhGTIWqIcwskdXxeURSHVJ2F4GLFw5XTv7qOnZ8uXz57HlIaHtwbVBLwnpopdl9cpIWJpPPZuLHri6gtsiMsjrCZs3fT2/emtb1w+/un1F5+2L/4Gu4cNPQKyEGIoCu/dYpOqEnl9wpvnw6N7yBXioLlq0zLlFRiLInSdSZACiWBxtm6+/MlnX/97P7j11rHEFeY10Ab8IdI4S2IXcPLIm2i7VFbJm8IVPJi0emGWkUrkEksc3T+g8t20rFO9vnj++WBY8aAY7N+naoLFuF4u8ubaj8fl+Ha3uhK+LqpJUd0SC6kZAV6rnlluipyY7f7bxexBePm8/eTjs7PrJnIK3itCv2SoJ3PIQBFupjyoqW0HpNzkXG3TFFCRcz0Bo6o5S85b0wEw6Gkesz7YYS/0YwKDlCJbV0IOtvTWOsskHStibp1lMCBU8qYErKAGpugEAQG8Wj9VxRD+lqz9dYBjAtfzz/y66wIRuR8+h4hIzIWze8Xz/bJzFBk8VuNspvUa2ZMfhgmMOzp9ae0nnxyur+X4XrW378oRmTIzcAmJmtUzX00R/GhyEOM8Jy8NA3M5vm0miKvZvT3Fw+XphTyZx1tvp4N7alO10oSXq3qPwR1+VZHj/AUTD9/5hmCF11dWX+WnDXaYO7Cyta47OctX13D+6k9+8z/+jduPpqBqumLw6JyF0mhAZhLrUByqFWn5itqVRxf2b63mZznHsrwNzoVQTSfH66Zurl/lullfncnFyvJFeRQcD8XKSISZUz1v67kfDJars8G0Lcd3cyxNoyudyjTQOIzv4OoVxzTdK2/f8j/7+cUvP180YgDmfe5zHyXuVZsKxsyqSkbU8849W4MWgkMzkGwgWXKXUs5Zk2QVRUYmo+CIDAkdgfeEQrKmdR1X68raKtTe5WAdI5BzRGjaDwkSa6VNAOw4ODUl4NjlmyysnyN242beTMFwp19m3pbZcTtKacsCATnkIgTnPXtfUDOG62EYq7ZIqareSm5qNGQKWWqZf1rofLA3XTWHJ6++SN3ntzmYuqKfuCAppotueUKqPDwkHoJ3kBm8837SxVbXJwd33u9SPdt/e3nr5cXnP9WTn1h7mvbebsYHw2LK0lYjKYsqNqtUv0IMND0cfed+4WT50V9uLn7k1xCzedOXC/r5x924Avvi9Id/df6Pv/otu/wY8ibbiuoFDva1vE1EXerMAodp9g3BStBROQ7jhHHBRUc8WZ1/yRQGR2+5YZlXyzAepDqJ0PV8Ccv1eP9oMLm7Xj/r6pVzEvxD74cxLeWiRlCDjfcDpYDUIh8Cu/XFM5V4cFz8+m/cHVb0+EV9tYKui+wdICAKEfczcOxmHQUA9JultjIsNNVWk6pITDHmLGrS9yExgiD64LwWmBmy7zbOWp83vt6YZCJg8w4BuRIAUxAxJCMiMeiitBvIkogEmZhVVVxvMUZkbywGuCGmfwVQE/F2EntfYSAXXD8M2m8HaIgpxdZCKqfRVkwVaCvrJ8Pj79rsnbZe+1wmHFMo97B1frDGr5zPH7uTk/HU0igMpvuQM5Mfje8Kl2IGQIPpOxValxIgq1aJSqy4dL7RPDg43o8Pzz/+qTz7aKhpA+9vNl3nHcbGwWXoLhgLqMZEgXjPoK3ufWPvB7b+5c/9ddfWcYIYClzWVoz8N37/N33z5ORP/sLduuvGJM1JMR5X7x2kmLxpZxmxdGHQdjVph2jVYEYu5PbclH01S5vTQWoxTMC1UHhkJb8fYqwXF93y4qpdjGYHo+OvaZqrBWuW2nTmCjB1qI7HidkLFNV+6loIjDLygNNDeO/9dHQYrDz46PPr51+c1jGRC3QzrUfxRgws2xkBWyV/v/hCABRFJCuomaIQWaEQSvUwHzTRYXaemBL1I7wDUXAu9NJUUjPImlJq18k5VwzQsmWlLkvXmqkQm/Po3M06O9y2675ulrA3xiW/2RDobtoCAdEQEpqaaAZTAianQcnXcjA1VUIeHiCYxLnvzgouMg0RifyUdD1Ojx2k52n62Wcvbk2e7t19xI7BhJDYkWLSCE1zpgqDw7cq2rTNJVEZwkS9KHM5/lqsXwwmx7e//Xti1er5R3fw+ry+Ou9Ce+1KiIdjDuGOlaFbfhrK0GzOg8Hwztvp/FVav3Ikd4f4+7/u//RH3f5X3/ngG5PND//86sOzyz96Nfva3YP39iCt7ZM/c7N9HO0XxdggE6QOLKUoaeOsK8pZSXeb9SWJFKOjFNcAbTkYSxEKkDC839XzUPmcGgPfaQqblTEACGbrYlsMKmZGJdVEuQ3VSBl96QeTA8lE4HN96Qs/GpeA9W9+9/DyXvXTD189f9UIwnZaCCoqAvbX/jZo5Jz74pcqSAax7BkCu4IEKZU+hhJNDZWBZDv5pM/dgQCkT4+IeVufMDODbp1zk6sBE2IITrI0neVspOYVt0NbHPZbq/rpJYBE241Lb8xv3/ZsIIKBiPQDnlgUuJcBYX8HSC7icFRfjELTkJTDPVXI7SVNH7C54cGDDQFqly1UeXXoV5+ddKvTqw+8Z+Lh5LYfOhUBDmYKWBKOrGvNJLe1I4FiJlKbaTUqJTmeTMowGx7ca27tLx7/TTX//Bj2LuvR4y9o9MHX3HAc3ACKd9vlL1wOXa1tc8JHj+i6CXLJhd0e8Hd/vXznP/gta59b3vC4qj+9lr95XJ+fH723N8k5tSs/W8FoD0ZHXFSluc6NGCF3y7o79TTBDB4T+QqKEjB0XSRmp4LNY4fFcHZP0yZly6mbX3yaUjPwA+RQDvdSxAgdmXBUhdZ5MvCDcjAafjflro5RRH05ryb3TLhZn7z7zsPbd4//+g9/9PEX9doxA/eF9j5QoFMw0QQC4FgNxDOMSxwMuAgIWaxpzRP5gP0IHGKVaKaE6ojV+hFP/YgIt9W2MpLjMAQhlKzCHhkCY5daEgPDpBijbluYXV9Z78sZqEyYYVvS6lsVe8jWoyJBJKSdhGw7u4eRmJGQwCIVL5fju90Xk+Nx121wfKi5DuXY8RGXBzKIbfeqHLybD7655//6fTn7+Ivw0YeP3163B49sgLeLakC+9CIEYVDtp3ipUlMG4eR4CXku0ubmdDI66IIH8tZeFKNhGFXeFOef7vHwbLn3OdFXvvn9DKkIYyuOxNVGAwdBYO7v3ScPXudQhFtV+eD9t7KeRlrsP4wqnBuOOZ7+4sXyejl5eHvMw1x/UXRLGt4nmnnnUsqJRt3ls6aQ1WWq3LKatbrBwfi+p8CjPQBXz08cO4UsoC5QU5t3Ik29vD71xSBlVZCiCIXZ+Rc/Ht67y2EPZZ3ywoXW+0EVch4WIY1dURFWGVdd3szu3P/6t+5g/dEXF7oQyVuNFqScKWOgNC5pMCiGgQsk9qqohKgmWbJ6R2UAMjUzVudYNeSUUBURyAAcmep21IgpioKZGhCjVoiCUbNzDlhcYcFIImY1M9juVRGEflwSKiBaVjOwGwbx9dwJ+pUtpL/StMrIjpi24kfo/NGqeTCSC0xtt4rcODLjcKzVXlEGGd0NYUJ+EOtnI8t/Z//O0ydfPv3i8WLx8tH73y0++C1TIfGii9h+QVzF+hq6DYQZdAvOC8nZWQ1chsk9SJ0sP4xddLN3Dr8+vPrwz+pr3MOyObl8ST+68+5bNJmObv96bl7CaglYIG2G1btSeZ0/FQnjgwduVHAucHSEk015N8eWfAa5kuX5cpH9rXLqKkjWhFjDcNpsTkgUEuDyRZL49KOFLwff+b2DnJa5uaJiYh2jmkcTWRNqUR5qjgTLuHhOXXTlQFTk6pkxL1fJL1dt89ICu/JVsT9TArQsaaMplh6Lo3fZDdftZnr04PrZpxePPyKig6NqUMFfPYerThmlcFA6GwY6OqhmEy68M9OY1ICyMhiwKIBAVZEjwcQAItlyRmU2gz4ZYlYRADTop5mqRgMDcM7QsQMyi+tWumjbdnsUAzPKpm4L5nupMfQBascA/Up386648Wb1Y4eTtq2UN60UzLqZfbUtR8P4kcqcw9AkqVxqPXfjdye3v5lSg9BVo8PSh6I8CIdHzz57cvnk8ekXn4bxgRtMqsHIMWvXoEOrr23TlvuzrttoF02SNM+K6SEUg6xLnDyglGx+ln0YPXh3/P7R5ZdfNBer5cuXAPOjB2+Vs9tc3k7Nutg7ms8/9qXBuCqnv95114MHX/fVENfs/J1kT7AgME2SqKQw2tv7zq85l9xkEoo9oNKPS5QON3VaXbRXT7oNz7+8eOv3/0Exeoeaa6U2xyj1S7GslstiBKTd5mXhRtjNg6xTW5e+02IKg6FJgqZepnXUqju5avTjWfvAD4c07fdvmEkcjG8laQuvXdtW42p9/ayyycH9B68evzo4YJm3o8JPKyu4LYKWEzOJXZONwBgJHZlw8IhlKxtGEpXt6lYRE0UgQiDn8GY1kamaKm6rs9B3vxtuG8WiSGrRlFLk1FmteKXYKL5mn3cV+NcIup9ieyOW3xkNv7H1qEdFxmiEAkZADAaQ0FnEcKnHlVsGPZduGesvC7rHYYYUyWE1utuszv34CLzn6qjw/M5wevzg3esnH33xk784fusdd/t4MJ2hArQbijUYpa6FFKWJ5XDG0lCzzB3F9GI0+4YFL1J7ykXpu9zcee/B3D9bnZyuHs+1Wzpnh+/+wI9v6/J5OaoKx03XqKt8+VZ1/FV0w3Z+2rz6MNbzhF7KSZgcFNPj6Tf+h+WwkuvPHCkoxMWZvbiCdNks2+XJebfonp+Cw/Do/TtcUMwF8hDimlXZVSluJHcgHSFlI/XD8uDI6Cyu19S2GktrhepclTSYHLVJ4iZfnDyd7B2m2FSTsXND5qpdnce0GJZ7fjyB7vL2rXvh6Fvu6knT1t+cbK5HxbWJA0FjI8yRQclyVlBfbJNsEKHgi2GlppqSY1Iz772IAjlCFiRR6xk8SahgJNaPBBJgUVPJkjUKxkhtC20rG4GNUqsmSI4r96YX6YVo23Fg21zxtXm9Gbl24JqJwDFtKaL+pX37T2Dm2vYu4a1b5UjmH9GrL+S4keF9cmME5sIXYYLlnTY2ChGz5W4+GQ2Ktx5dviwXJ09zfXp4cLcc7IWyBCtdNUiLJ6otVwdY3eXB2ESxe4Fx0aa/5smdyo9kHMS0iJsufTnc925wu93EcHRU3Ptm0lqXj1Hroixje8LYtuvPI93e3/sHlmLz4tPYJX7vH4333rNQFbPbRTXmapzaDWHN9UW3uRYr0+o6btr27Ky9OLm60FeP89EHb09npQIWo70Uk4DwcJrJOVejdN3qtFu/cHzJxcgN98azw/bqqr18xu26jaLZMAPU7ago1otFJ7Zo8mA2zU1tTkNRMHnPZcJNUeyFMCiOD91sEuFgdjTD03aROsldMfKmlpKoJVRjQAOQmJNEFCXvtopEM0+oMasobVWrqKr9cOYsYqo5qWQ1QQQXAYUKJI6pU4PGcNHIcpPXyo0RIDmPwRVFUf7KLLBdC9D2Pm6nMLy2sF0tjAkcAfdLQG6oyO07KW83lRh73Njhy9qOioe2WsjZc3e3lHCUbJOsCdXdUA1TNzZpPYcOxLQ2htn9e+Hdb168+PD5R78ohqPD+/fLyW22VHdr8gOqjqBicarNKQIGX6lsrD0nf2iMfnhbutYHV9664welA1SXIRSwnmt7mbVJ60uLWZo6dzVNnKTNctPqvd8t3imH06+hG1hc5nQqaU2wxvYMnnx48cmH6jeu3B8cvo/VYPH8SSu0Ev/qsn3/K28lUxAIw6pdXiKQD0MQbXJk4IxDgbED6OqNGA1mjyaDB+aY2hWtVrZpS6ysyddXFw69Jzd/ddIs18PZxE8qG+jszsPJ0Tvt+lmOF4wR/cRh55bPYHnRrGox7hodDlAymJpAJjU0AIKkqipsgEb9/GqUbR9E8J4AU+pSblUtZRRBAUsxt52aAjmXwQwhi0qSuskbwUVt62hJgYi8c+ydL3wIRVEUOz3QNhghEeoWFW0rJW8OdtnFO96uLADs110gbT2Q9s3tvdiMHQCycHXdlbNjlqufyGJTVWs1I2RwlSGGykvTigcfxto2ZTF11cSPJsO9g/ne3eb0yeKsVm10HFw4EEsesmNO6Rq0lXDERWDeN+qQOydRm2vn9v3hA+nm2l60qcbkYPPU2pVmjKmLiREZJ+9W03f85Pb64kUxugUH7wRP5AegAHLp0Fw1tOuP089+eP3lq/UKkV5V1XVXHNSbZexkuaDnz+vp3VGVLq4++7CYTNrRPsgGQ5linVJnQrHbaNdgOVt3rUdnkeJy4wZYHdzFtKHh3KWcM1nMOsLufJMFZm4kiZanp1U6zm0qRksazNN6HqDRLuGgq8+exZcv8rPzsMyFDFEptZ0YmIHlfttLv1geyVWCBIgkkmPEJKraD77NSdZr1cBEGEURy2zaZVmtFYl9SQkVDeuY5htc1JZUExA6dh4DOc/MZXAhFCGEEG7kHFuZPKLeDCp647YdBYSghIwAAGTI/bgsQofkyHlm75x35BmcYyLIppKAGMjzWvea7t6jyVKvPuoU3P5DLKPlVwIlQunARBLDmAYzX1RqXc5NNblzUI5a3zUXr5Yvf3Ed9iaHd4bHd50LmpLaupw8ouExQIugmjsgNTjIy6eWP9VyX8WZtb2cBSSJER1+p3BV5Rhyg0VhkhSkKh9SNeFyDy2zn9SLLyqHUoy5vkqnn0halu8+cI3G80ZSefXzXyyv5k/Pupevcuuq3/97X0unX3z+k5+O7t3e/8rDYnpUTJzqInWNqY9NLU0dkwBCct4Vw7aVkmOYHLrJoZ8ek6bN/KRZLAYH+2FwYKqYu00T0Uq5Pl1ec848aFYDSHVaI+Tp8HBz8Vm7uNqcyvWZntoK93zMROSISEUV+l16oKKQUlaNYOpQRDArEuVsCqlLdnVlfuzK0mUVlZjRJCNwEMYYNSqss643WmfMu32QDr1zntiz8yH4EHzwvgjb1mYE5e3Gxu2Mv9eV1Df8k6LdjNTYrr6l4AKHfhgnIgByBJQMvhcFMRASA7pikOnRWYPHI4P2ebd8jqMhgmAo0PnYJi6OxvvvCWfI57mdO65Ss2wvPtNxORp9D+zHZy+urvVs+OBbMhtSyAP1NKwsv7Kuk2a9uXrMJM4fZE3oqq47d+CtKIkg2tr7mWdy47EYUFyICZtBNaby2I3vW/3C8jlykZrTinO+OhPKJtY2tVUDgyAwzyGs54vV4+uTK3l8QQ2GH/zdt71bRk4lQ31yuXc4TOZzs/HDgRiqmqp1ojl1ZgoxO6wcI3S5MMdhz4+YpXXM3nNTNznUqM4iAba8l2A6LJe5ef706uWzeUXOS1kGTf7qarV4ddExPd/QieTZrBfPsMq2KStpRgCImaKKYmbrHBJzzgRIIqxmSYhHIoh1gn7wlIDljNFy2/Giw3W0ru+dIOewX8zmnCfn2JMLzM774D0Hz95vszAwMqVf8TqwHfmpN0NTmcixDz545/odmcjc734XMFXBfgrdtheIiZF5K7UkJMeh5kcvrbjnx97OdX2lhpjOpWzN5TAecKkqal3W1Qth3iwXaflSXdWKlLfef+v9W+HwdrF3mDbnuXnlwhHGtV0/7a5f5MXcutSxxWkyq9xoH6sJjw4MUOO1swi+BI8W5wYUeViMb3kCnr3FXHTNM5ArQFAVtQJ8IWS6utJ2nWJdN019/SKuVs0itVFf1vTJKyHm3/g7o+PJMq7WbOIn3hS5HJfVqL5+KnFkzhlAUp+6TtTUAlHoNufcchyOh/tvORiJZmDDYrh3/La/fpHKYn3xClUKAix9XG6qQWlg6fy6rhEcXzcpfXQe2aSDdc2XoI2nKWKOSXA7nlFyMhAQhAzSN+Iwg2NVS9qzy6SqSXotWF+LxWyYstQtzRN3mcVQDRAdMzgG5ziw986zA3bkyDn27Pv/u34lam8w2zFqO8qHd3nWtmL6uhaGAP0gRtc3OzIiGBNvV86REW1V3dRvUkJSAAIILsjo9pN2cBg/2m8uFa9FLeBbjivdzPNyruTj4vz6+sQHLopxcftb0ASni/LOAVUzxCjXX5rm0h+Hosjzl514dYc6nWIxDmGYU+vcAVVT9MjjQ9Au6ZpFJJ6YDWz6be+mJUfw/YbeLsca8iq4EQAoOkptXL6AvInNVbN4njpZXK/XLy/bVUxSPHusi2u6c7t8cMumcL3+Yk7ks+YImM2dPXl1PwyhWRpmqA7r9UpVU5aMrFxxILLCDMiNmpRJJSVyviiqt5ruFU/v+yTG4+7yec5rP9Tgq9W8zbYeHA0KrurOFqk9v2jm2Z7P+XQpxzO/H/qBdKAaCVFU+36JsuRE2PRMoGDS7ZBNNeiH92YBNVNyiJSTNUpt8q32czvNyAjRM3oX2CE7Cug8u96ACJ1zAZjYO2IO3jvvlIgZGft+wW0iDq+n/SCZmsBW26ZgzvXzh+1NidkNRURETM4hEhDKDSnZ95EgEfuQ+OCcv2X2YiYvXChjam115v2oiVE1czE4eO/7RTkybCxp+9mTdPmT1h4V40NgQiSHLnoXN126WGfdmJy7cqIAmjuQxk18ObudoTOrnRtnLswaoGGYfgOrI+TMokBZLOrqGlVQ62gKRpJX1ly0i+ft9Ular9qG29pdn67jdWrWenraza/l9j3cG1PX5rU6EBEEFVGF4fH08qo9WCkPD7AwN5xm88uLZ6lpsyGEqEC+3CuKgVGxnJ9xUY4nx2qiVHD5NsDaNhflzI0m+83FbHX9FLNWRYBhoREzK9Qj82l2F//4x+efXTV7gxy8goAmUvJZGAg9FZMpjYdQjvzlvJ0/bztRAzK1bNjTv/2qxASVAXb9tkZVUVIkoy1j46mvnZNzzvN2VYVjInZESOSRHJERaBHKvb09BwqIZiD9mtidB0psDNvtOo7emGdIaIS9wH6n93jDkgj7Zcj9Hq/dljYzA3OAwYdAJIVbNsO2dsd6ORoOulgT1cMZGFWIhE48WoJh283joEF+6CYPgTpMOcZNAuFCnD/GAjAlNchZUVs/OKDJLSCn+co0YajUBE1EOjfYo2KItuFQsXZp8Sy1DRWHJmZQqwloqC8/j1efdovzbrUSCbHD1fWyua7Xczk799cXOXhoGnWMwQcU8ujqukMANOhWq2Ggy1cvH/7u70eIKWfYfM7ddb1JWZxCZ222/QBIXA3JsKsbxqWrAvb65piAKmavsAyz46AdxQ5858pJzk5yrvZxGsmk+4fjgw8+kC8+v3r2ZKPOxsNBdbjvwyjAcugVUu3YpO0wpZRg02ECELM2AyIgY5PIzGPpiMhS39BBQGBMjNtGZKbdEGby6Ji23oCJCZ0SGBuRlcFPxqOiLJwpiSGR9QtM3ixybQUeb0qh+654ROwx0htDG27uECL3CwgA0bDfwqSekckD4XbWKCD5rGdznBq5uhiJAab1hStnLrjcpM3yypTjZsGEVhVOr5hHVo4cuhyvLC8BO7MOcOSG98A7lTWUE/IDIg9ooNlEhVrEWIQp0xippmJoedldPZHc5voyXjzWJMTkJl9pm/XyxZft1bNYd3ljMW9y5m6Rz59L3RVH929dLV/VXQydoQdK4lCGQ0/eeTHNmuqMjAlS127UDTRDveikNnajdr3YLBdQ1vUmFbN9hWJ8MM0G7AOQy6aMJJKdH2QRsIQQy8EhjEkvnkG6JnTZcTE8ijFZYvLFu3B6azi8d/vw2cvGVwWXEGBJeROblNvGTNGwbXghbhU1qiZCRe73ISAQEWpMxkQGRGT9kuIbd0A3809pO3SXCZAZewfChD4wezIBdgW74F1xA6JhRwfeWMPN3J9d+WIb04gd0Laz+Wb2Zv80MwMD0360qmcmckAIqDmrSW7Iotf1zG+Gbk1uJcfXVTVt4sp7cpIgeDRtl+fS1oDTpssIyKMKwJMbZ1OLG7SAGFJdk4vZleBcNT4WAF3Vkhp0hNXUtERmkAYgWRnYj0IYqXWyPE2b07h4keuLdrnqYkQMmny3eYwUm9VVFsmJUyvdqkudnj7LXY0HD/eqPe7UtY1UAyMy5zF7GBfBp86ZtZoNWUSX88X1px9KMcXxQIo7XacppZQy5Dx/VZ9+Kvffz7JuYndvj3k6OlbLYG1RFJlQciydBy2BI4ahaKYwYN6Y8+gKKgdZE3IVdUHlsBL46tt0+87hi1eri6tFZ+IQDMSEUspITgzbLLVZ3wGIZgh0Mw2sH4gLwtsZptstA29MQLhxF8yAjOQcOs/Be0BUBFENRTUaT6vhuKwGOwN63Y+xbShixH5y+BtP6G9qxttKmaFtJygSkffOu+DYe2Z1ziyrEmEe4OV+mKM+1/WrqhqTrRFGOHpk5dCkKYoZFXsGjZ5/lDbXMWcEVmhdOFDoms1V4ccpZuMRAVJBWE4Hh9/iUPH1p1Kfqq2d28thUpTDUBXmAZgNQJtFXj5znqWY1nmRFydxddKtz3K9ShEECkmOaCARmvlT1C41Teaq23TNVb2+ThenjISHt4gCdqphQlfXVrcGDIOCiCAbSlRXS87oh4WDXJiu1smadW5pMJ1YWOX6FTKFcZUX8eKqOf2Z3jpa3VrU97tIkaa3H7CTLl2F4SCLrtcXwYCQczatF4glT45CcFbsxWSVm7RdRInFwbA8Kur1YpaVPAwH/Opi3TUtaj+oNLSdtElK05U5BSTo5ysgO0airfAVyXkkYr9VexET9bCXt8MPlRgDu/6UQs9wAxBTWYThcFyVg6osy7J0f8s4EJFI+77VXmDGbzinXecRGjgkxy74ggvfzzzoPVlWVEWKi7GnaZUG+Kp0kfMiU4ThgJy3RFk6yrXGVcGz3CRbv7Dll226BNtTqlRXImsyVSUyXzcXODwaH72LaU1hECa3XTHoLn5s7ZVzh3l+1Zz/MXHsykJCpRRyKLEaa86YNjlUuuG2fpU2r7RZ5e4K6JjDA4uruHziBoMYUzbIG2mWjSKuruvFSbo6pdjZ9FC7VmNeKTvLTTKLQg7Mq7rIi9MNk7oIbACb6E2anPNlg0Pwbj8JpWw5qxJy8OQzkczXXdPkZy+aLz5ffuP73dd+Le4fv8Veu7ohYtC4Wl0jJJA6vjolqScP70KomNh05Qt0fsIMbdOkKM5XFtB38WBfy/2js9Pz85eXIhGIADml5PqFRui49znU9wYBIim5fp/GLlR5IOZ+KBg5QwJkT945QCSCbBmJHDvvQlGUZVGEEMqiKKsqhMLBzdpRA32jXPHak7FzgMi/uuBi6/6IFNQkWzIjx8Ss7bB9PO4+qxwfPPym5Jc2fw6DIZW3GQsrRefncX0KbsqbF4Z5LVdm5Djo6kplLqE00GzEbqxaUtiD4BnKvbtf5UElG6H1qb56sjr7Ml09l66TBKnblD7ngWoYCrKhE56qL9lVJglyp1giICDnzmsa0HA/inaLeXt5kS7nzoVuvYzrTazl8mo9vxQ2TGIKWm8MHSZcK6O2UhSY+kWwxrGDTqRwkLIiYLZcMICj61ergw/uLVstM6uIIwJHxOjDbjgpIOnpq8Wrf/038+vN9/9uPrxz2xMgGyA4X6qYd4fhaO/q0z+2k5Py+N1QBTQmqJFgWKEj2uSW0TKgDwVoHILcvjWpqsGzL54vLq5RAwAyA7MhMTNvx8oh8rYRq9+KA/2CPyZkJO94u6gFEczEIJsSECI459n54Iu+erHdrF2EEHzPMW4NBQD6LQWI1D/qnCN0zM4IdwO/tzsQDQUsW2LwToYl6wDP9/RsnJ4N6DJMS9r7HbIEWHX+WGFVzh7B+ZfN6fP29Gmzeu4GJ+IQB3t+8s7g+IO4/oKmX3HoEEhNqAiA5Ae3islh0I2F4DjK4gu9+jhu5tfP2/bV4zBImsWyARcJBs2LlTYrrAjHpZ/sCUX2gK4y84iCADl1qjk3ierPVLhtNqogzaaO1zlKc62LK2xqrQKBaYzoPDJiFw2YjVxR6ljSaiHegWPwiggQszoF7zgpgkM1aRbLq5MTGM9OU7c38EXpnBb1ps6amRANkxiSeE8i8md/8ssnL+Z/7x/8+ltv3yrLQYpLg9Z7JyAwyMN3vxE3681ySTxBcxJNaEWagrTq6iZh7HA8OozD2Wa5SPVm5PLDt249Te7yZMEhVE4OiOaIWRAB1CFtJ+0iIbLbTln2nr1jj8xMhigq/dozICRCYAImZl+Eql/tvYXYzLxdQ0quj0k98bNrIFRV7LvzUdUyOQYRAHRuu04OtpOow3To708Ws3AxhGtKZxpcMfm+xEk3bypXucl9yrUf3yvo4vKTP27PF9Ep+zLmzpUjLG5Vh1/n0QziqNp/mARM03Ry2CweS2pDiZY+T3GjXWhSJ6tXurzopGijGheb1gACalLD+nK9/DKmlZa3dfReFTxyQTlHP5iiFal9rtIhcuyyiYgISEyx1saaZZNz7hq/ODcU2xthNFktoW2oJIkZoTHwqiKAoEgGKGadInrVqCkDA3jIbBAzszMAW12v6svaD4aH37zFfoWdOCZPYNZXn5EMAcyTIMGLL1/983/+h7/xvbd+6zcfDApCFAgDHoyJfTEeUHW4unyyXp06Kl0ISjGA81QaR+UNDSojLsCpD0278objweD9b9waT8vnL+dp1U0rGlX51aaI1m/BQcZ+rUfP7jlmMjQ1yP2ObHLEAUiJkJF6Sbxj732gm7mt/RzEXdINBq5fgYCGWZUB3Q4yA5Oi9fu1t0yPQ0Qlcw4nA62Gevfu0aO7FZz9qeUrAMfTr4fRB2F6b/Xiy7z+RB/e5v3b5f4BzH+aL74Y3n8X+AnWl1G6MB4Ws6/w8H67PBtPimrvXrM5BRA2mb94GrtVWZX12TmAUBgla7v5Wbe4zJuFRSUKuXS5QRETZc+lUM65Mw88KECLnEUIGDHXK/CQm5aZ1FSiQMa8iVI3mrp2HXMrqfVd1OAB3c06t4TIqmiNGBN6syw5Ki42umlNzMzzaG9/UBVMYTQpSVIX49E771WVB0/nL05+/pefhWqEJuODu936JYKOBin4DJ05k37EvyAQQMG6Xq//zR/97NMvz77zwdFXHlXTvRlSNZodNetT52g0Oeq6RTWeqFJbd4PZDME8FcBuwNw16+urc41SjqoMhYAbDMtiOBodz8rHi/nZZRVyCN3zVWHIjmm72wQMwUyTGZkLCGjbTW89ZOknG3gi533fc0HbqZqIwiSmCgqAagYIrrcOBOx18bt0jIgQAdmYCMEhkHcwnTS3J7I3wtn+oPRWDeeIkMcPVe72wmoLVUyi5agL07GuYfnc9g9Tlji/Yl+627dCdb/p6pxaLErEeTXwsTmJ8+ddfWGqJpuckmLZMiZBtAKAU2rT+kq7jXbJ1BEnlQ4Sg58ic9OuFbE6rDJHmAyTMLYRMxXlUGMX21MEc0WVxeKmSRdzXXa5iQaQCTIRVuCZwKxLlgU1Y0ymBkTIA4eomsQQRByZe/Bw/P7v/OY3fvfvHN7dq4ou1i/MnKV1bhpzA4kdMw1mHbSDVeRiMiC2ogybFSXJgwJ4g6ZouG0CzmqqNDJ2KmfPLn50elbfGXzr735tMLuTu6gZseDRaDCeDUWr2LZlMW2jlcFHteHwmG2JqZtORl43CyiBS1cNN13CCGbx4DceXJyOzr54UUodDujVMiQDAFA1BUeEno2I0P/Kntq+KdB5169Hon6qZq9jBlCAvmSLBsxcFkVRFNtWnZsp9G8MaGZgBgYHCJNRfjijo8Gr6b4OqwN0hziaSbfompXHQTJMbWNGjt312YeODl1we3eqiy/+cnbvIRe6nrfl+Gu5e+VKb9XABU2LF9ptkrU5ZbUytZepWyGSCoB5IOviKredaCAIpiYxqzJAoTlTzGZkapBWkrKp5hhhHPz4gaCgL0BBVxttRDRqXEKXzEw7bOerVAs5Nzge+cqpgrEzP8jqtVsXm0W7jl37/+fqv341zbL8TGyZvffrPnP8CZM+K8tkme5mO7ahZsihmkNSHAxBCcIAAwygv0uANBe6GQkywAwESASHQw4pdpPd1V3VlVmVmZU2zPGffc02ay1dfBHZlM5F3ARwgDixz/7WXmv9nscSYS7SGjgoVPn6rUeP333anl6+/dbbl2fD4oe/4+j0fv2C0Qc9jtv9tIvx/lqmWxfm/W49rLaBSoXXq5dlPe7qEHNWEkQAMkUjRQEAMiAFBqhYzjwuW1m2VnN/+/FfH1++RRcenPOhNjjA5Eh1gDS47kQ0TLHMmjnbjHe/DlHVNca4n/oczaGj2qeiaNPpArvvnq1u9243wIJe9K0aenYHKBQ7QzrEcQAPwwp8dWi+nTG8Wi18BfG1Qx0cQqirmgDjFEuxV8nUb/uB3w62kAmYFeDdy/bH5zdHHee0h9xaM9cwG64/0TSFai7Dg2U1UeAjrWugqjl7M8QXeXhm8f7LP39++f1Jp35PNx6m7eq+TGPcb9RU62XJiZmDXwy7B1FDYjNQKZJzyj2HI+re0Bw1TinGPEnoWk1ZNQGxJiljNsBcDNGXaEX6rBMRY1HICQAlq8SUx5IFCnC0MGn1/nefPPrOfBxGX50DOwXM41Zjk7fZyyST5Ql9V3Un7tH7T3/8D//uO7/9W+Smpgo+XIzDPSSNMjiFPI3DZjVttvv7Zzps4vZ6uv8sjgmqeuil79MUxzeevIXjyzg9IOKYVdQcAhgc1pAdUBtwObfTyma1VRW0c+e7+vbjP0v9W8enp0k9d20VTnOOxMsR987V3tc+LLexzNoFLd+B+29g9bIG7xaP3MWTfqSpX6tzOSuRcsV22hVVT8IhXm07o2/XJQwJD1RM7zw75zjw/6/ZXQ+8TjBCdN4F79l7RBzjVERCqILZK8Pe35yb17eZgAWE7751+qNzGD77uHz/73J7OVz/FPpfJHekwxq8Q7cMs8dFbqBsiEcktzx5z9Vxeni5u/0G7DpPm8//9FnTBEuDDMO03ZVcuOqwnhVfEIpjRliLjGDOnAODFLNallLqpYdhL/0KUsn7Po6D9FFEAAGhmFhOgogW6qpuYey3d+t+PfngDzAs1SB9xilJwYlsYtoXz22YP3l6/t03yzRCfVEKlf4hjyEPPMYrbHx7+e6TH588ffuoXUJzeXz8wd/i5o0pXafddYkZuS2FDCjthzKs+ttnud/q+mp7f9+vduN6AuKCU8kY92L79dBSrb0rMiR9vkJRRDMwEtK2wtOGlrU1jS06alpuFq0Flynsh2Hzi4+2p6eXb51y5+vluDx/r6GOa08AMva+Ocslrfdj21zgsTXdhctp2q9w95XCooybzrlMPKRBoKRhq7GkIZ4uESHeTDUhIIEx0yvJ7EHM7ZAJCF9pzA0Oo1ZiCs47doBgpiKlFEZENVWTIsnZf2SVAzjwrRAMTrv5b73/7qm/WX3yP5nMU3Zp9eXD1x+1x0+Rddw/XHz4D8LxZd5/UbbfIDUYvHddXn12/+Wvh5tnabdN63UpMaUSNzqsZXsfLYkRok8EDwAZHPiqBo8M5rvOdYEQtJAUyEnLcEXsmTGOqexGEATKWTIAlSJA6HzFTKmPm/tYptQ0dcru4Tb7AMtHXd0et0eUdsN0dz0nmZlUtMvSL2ZVe3RRSkRwwzCx+a47T0M772bt337r8s13wv7reLfJbp/hASUrMsatyShQaUqlgMo4bZ/vrj+b7m/Gftffb6bdFPc5jZaxiHG/s2HUOE3dLJ4tRAxvVrxPgoSmNmM47+i4gzlaqOHorGlPW4VELoymGOYGkqf+5mq1vl49eufo/M0ymtRHF7N2OfYbdCICaMlKSrx086VM1zKt2Qr0GzfuulKUuBdc76b9Zhu3+fZWEcqsmc5nqEybaQmODnQwBDIzMTMVJ6+3CV+PrbwaIapBzhmRnfP8aiP1b2hj7tvp6asJOqGSPV42H755+ua7b95/9Is0Bapnm28+Gnef5yHuwgixn7I7h3D/qz/Lu1/7mruL340P+9Xzv8ppv7u7ysOoGXWMOeaUcs40jUVAk2IZwIeIQICgZkAxAY0bnYpUS9XKBa+dE89unLLTkQnY+/2qpNHCjMK8YiSEXEoCGRHRKIyKwNwGmp+Hes4qOA2bMm51uVxcPA2VBitxt/ZTzgzd6WkdvASN4+RwwLZ2oV08/cHy0bsme5eT7n9FMz/tbrh9nGPCcKdkoV0Om2LuOOZt2d/sXn60ffb1frXFjPvNGq3KGUcxMdxvSr+FQU3F1iOdns/X9/efXOu6wGUFT5dweeLOFjSvrGrD4qhzx/U4xt0uTcOQwVd1QAdgeyPb7+Lnv7re78vT920+3FUOQrUsTLVbrvpVVS+AGV1jMEtxHeoFRdO7a5SYSp+U8lDlUYZeYtR5QMypsuqiS4T9ns4IAx58twcOORiLEh+MbkyIIiKgogqvhqHoHDIhHv7nRBWlALhDVwdfVUKGgO8/uni33VbTF9c//et8/auYw7jdnbz/nXHsiWZVdQlOF8fHafONyPBwuyvj7mSEvL/aPbzISiUDJJScy5DKpDlrTjCNkBKWRClrDUykYiiR4h6GXbnvaSsp8x0EX82r+cJXla/8bNyuWAfvChUOXpeBfF2HptI8YnmVyPf17LTroOzibs/k6HTmuJ76aXe/G3fbMk2+QT9f1s2pG0e/Hw59feTGxJt0tDiuG6q7k0yZga06x8sPZXcNNFp9aoKyWRXKYzGToDBMd59sXn5y/9WvhpshDhKH5BsvxYooAkyjTSPti20j3E18++v+jSfzffEv+/z+MfzkrfD4aXPW8vGCuKLNdj/pkLNfrcacCrM5T3F/TczeppQjQokTf/aLF1fP9x98/+LRUYHqxrw1j354tFjGKUnalTLGFM3NjUEa9Scbu45l06QSGo5DLtOEzFWoElEhLbO2qSq9GuJOqoOviZCY6QBOPaChpJTyGq0B/1EU51uFz6vKGoABnGm2g6jJQIzOA74DN35zbd1ch12UWXP05OjodNxfFcvL8w+hmmnfT7v99vbrsHxDeZanb64/W+UUTaWIqQUQkKmkEeIoUkAyDgP0vdmBjhXFkd0N7malmE0J8xIpNEeda4JnbsDqqAxldBV2zbJpm6pmgt7haDgUKcxc+YrY+eVpBUrbh7jb8lCo4nbWGlscNXSOHJsUBd7u1vPZrHvjrWG74bCA5hyrhQsrajAcPyIY1KCqLzQOafNlzqI887N3KTwSnmUVKwFDpenhi3/733/2b/7n5SM/7Ke4TVKQuIkJh34c90UL9Tscs2wjfj3gTdQ6jS9fIOT8Jz+ef/jd9vFl21QCumcnm+00ZVtPpWzXko3Zk5Wyn4ooIIiWnIsoWgHNdvXVw92L/jvvzn7wfjfz2G/+Ahdn9eyCu4tJUNmHbknB0dEj62oefrW92mSBfdT1kFKZMQJ4MF8hV4wsRMtmkBgKtYwekcS0iEhWRHzVBiJEQEVDRGL+tq4+8KZf7/qIFXP+0AEiRqLaptndZ6vV/eW7P1nOT3N7Rv5h2t7u17/K49Q8/XE4fmfzzb9Pm1urL9mXuP9s2nxpWeJw4J1ZThlVtVDJNvaSRyyCcYKUIGWMGQvRLNqiU+eVlz4hhMq33psPcwZer4scNJ7d4vxp1zQmExJpxd7NK2Yra8WRmRTNN3XTtbC+2V/fmLCpTRux6Q6X7dDHXHQ+Oy2Yy7BFv6zeePud3/nJ2ZOz9uI9ZkjTA6ZVNX+PQm0pel5IoVyGA85LtaqOnpr5uL8zd8a+Hh5+ffXRP3/x8c9ykt0OU48p0xQz6FSiGIKS66Ot9prJqtq+45gGw7oK1fF7v/34yRsXbvw19LdJQB1Pvex2OiQuRUt+ZXpPEfptBDFASABiiIQiOA6aIoxj/jc/ffiLT/s/+F71/jn7TapOtj7uwuKcqsY5AE3sEJaP86Mrd7fiTdzdTtsBB03UADUOQo3BK6kHmTk0uVmVyyhsll4tCr2uZBSUgRX0lZz+tVvulZvQDFQO8Ff03ikDHepxkssazuuuRsd1G2Ohti3pBY630+bezd/MfX97/z/qNEzjpps9ZuGXX34yjWO38CJqpWSVkjBFMYE84ThgP8B6hyZQxGJWOGzpB1ssHJt2J8uu6pSRCYlrlhLGvQ2jCbSLxez4XPO9WiFkxMpcbe2cywzzmoM5Tg5Ed3ey7/NEJqAGwJZzhF12RaltofOP3vnBez/+yex43pwt28aLDGBrHHuXk2veRGYd74BCxKzD10zBz95O2ytX+ayUpr4ohrIabp+vvv73q69+DVTa89BvxtSXaYJpJJ1ETcVjUdwOJbESIQOa1995b/Zbv3n+znvv+jDB1b+Pea2uTgmnbONQYoER7MBezRktlrE3HakkNa9YGXsCoThAmjBl2GX7cgdffBn/9a/kT35j8Y9/UzRfQWEaxC/mWM3AiAKU0pur+I2zsd89TLA1KoqzOiA5QEArToOGqkJCNEz9zQARHMEr3ryZCSghFRU4ZJQFlf6m0XPQ8AKoYwreI7LLBUFNWWeyOZtnz4u0+Tpu76vF0e1XPw3pboq9WhOnycaPfT0T8SHMpvVNv7sy1BB8jiC5SLI4ghQrapJ12uHtDax6FNDWI7xi44OIqoKZImJCnc+aKrgqBEQq4vd5SuOzBFSXab967klEsgsOiJEi4DEv3mR6ojapbiTdaRnAe3+2sChTP6IP9dkZGz/6wQfH73//8rsfzo5mTFMaHkCTTYPKwC5wvQRfcXUeNRIvQKR/+RVbas7eJ27JghqWUiwN6e6Xm/tn119+OmzjuB8k6jSkPGlKMPYWJ5JiudB2Dbsxh0BNx6i6aPGdd4+XpBfVaOtPo40eUx9x2vQ541SsZMyKSR0WzlmLoCbMk96sYBjt4thqhwIYJ9tsbBtpXeQuwVUEBnjI8n/+D6uvbuv/6ve68922f3g+P1vU58vF04voK5AIQorzzbh/GETZfMWhYjqwXqGSQhgAwBrf+srQbZ/vl2oB4BVaA16jeYnQ9JX+4sBwNgNmDiE4h2qSc1bNztQEwCG04/Xu+ut8/tbj7/0uUb795pca77cZrp8PcRqao12onEgvJeU4xKKAYAJQKCmYgCTNYQahnu5XuZc4KBgEBwVQTV/TkA6nCDJCNDEpNZaGXVRMMUNa+bzrFo1s4up2fWSYnAAWnz2ZxpgtbZ2fcVXXvhUflM5gvPbOu/NW4vjOH/69s/e/383nJOPlW8fg66ppND3o7s5xQAiFGuePUIrmUjQK7l04lTyUvE3bOw6OpmywylIQtYy3m5e/vP30r3cvrve7vmQywxJjGkqKFCOUBFPSLDT0MmWrKlwu8KTlueM3LmeV1zz2aTdpMg62S5JjiVG1UAbI4EQxTyUnAcCSLY222cOXN3IUSIoNO8gGm1HvBthmywCoMHO4AWMzAvzZizz8T/0fvYHvzyNXCAzOaEqinrd9vxpxmqIJikGoob8ftKXsjUNh59wUiak4jwgziY9Rb0vMUDNWYKiv4qIMgMCvMIwK5p0PwR8iOSmLmRE5AHZEBIRQxuGbF6FB7Ke4fkbztkzT3fMXsU9jn0ktbQU6l2E7JS3l1Wha1XJRA0+zN7v3f3R6/p4afvX/+m9xf183zsB0sD5rEgAzhwfBvAWHOWExAsB91CHLPAyPwnASNsdvLObvvD8W/vTnX3z8i69TKeygbjyoIZUSe4CbxdHcn13OTx+17enRyY/O3npvfrzMw9Xi8p3Ke8DioEDeG5g9vJByg3xk2BTZQ9u2szfS7mFafZps9A0bzLIkcvPq4kPTOMV9mXbl4ctxf7u6usqb64er/e4hG3jLJU0RCaVQSZYT7QZc91rMEGF2xO+/0T098lVKmtO02w6l1B31++xGYIeTWCmKRqJUzLKBGJhyyZpzkcw52X4iQZg1EAXXA/bJBkFRI9RF5ZfBMRXysGjwqIWzWX12UpNPdXdiNU1lGL55ngcah5iovsm2uR/JURPYkxU1U6yrOilIkYAgU0TdIxAQLGm/ME7FZ2rMsBioWcwWeYbdMYWmaWrPpJC1JBFGct+2GxHBAQCrZcm9tm9cnJ89Prv59M98xfu7B1+3LjRuhBwzBtvtoyGUEXJhrrNghe1FePKOO36jWz7y1QIdyX5lmH3nECHMiLeaHrDogVblvStoJIa52CDQQ3IJv3OBP3w7tG1jdtycnPN81qZp/ruPHz9yz77cff757d31tBv0g59859Hbb7z75um7785C69kfFbD5xfd58SbjJvdS0haMmGrMhdxc40PJG3anxXUSh6Ia1MVpHeN9lATcao7T/ooXl6re+2rY3k+br7fPPprubvox9qtex7RbbWMspRQRTVGJQ0rUT/rsVlf9gZyDTx5Vv/2j40fHweIwbTOC6VhKtMkMisIBmfN6+0GsRMBcLBmqggqURCVCAWi8PlrStth4j1lAHZ0u3eURzmd4ftbOW4U41V1dB2eg4GvPFdaMbSVTIWrz0A993o3Qg79ar1+skbw2TslhVwVXBe98cGieqyqoKmkhIjVQKWilNmEYXrGjFaB2udybbaeh9lKH7TYN03oveXbqP/jQQsCDQwrBlSIEgCnH7vSXn301bZ6N+9z3/dmc2PlpSoOwW9Q5j+OuGCKiH0PNiyfV/GJ+/i40c2TORUz3QBpXV5VPzXHrPbsxgk4PayLUIsaVNQ0hUC6iamKUcjkJ+cO3FqdvP3KzY2aWMmi8xZgwzJ/88IenT+6//3vf3Yyzk6fv/OB3fhBgNWsWnG7S+s7spVanBMk7J1PEWGpQyj1rVGwtr1V3Rh5dzaDYzEuaTDSvXmZkt/gAuTbQErP0aynR9tf3X/989fK5FIWMuaQYp/UqXj+Xps6MJgXHAcXkdgsPe8gFnQcTO+ncb/+oauTh5teJBFztiFnFAGkoYNHqcKgfQA2zkZrFYmkyUQAEMVQhMezFVsVWowWP77zZHB/B6ZJOl9T4yYVAsy6Pk3NVuDh1HDQl9o1v2pwmidEact1897BZKXz+sgxTP7pUCGc1+oCHVzlgUtPgPAViS47Q2JjMeadKlaukZAX0VbCUaIgIuaornQbOu5K1zzH2knsYhzWGVN75LXPh0Dt0AGZWAAyqZmPdx79+XlehZeqLy7tBTPy8zUX3D2VKToOnxdLmlxhOSwnTzT25OyRv5JBQNbtp8/T97znaLI9PcJru73/lGBCIgzkH6Cg4k0GKIapeLPhH77jlkyO/OGqWZyJG0Obe88lsNnvsfEcsoaq64ycYEHe3JILdkUH0Z0HyVahnBsWGKwRk50ET+tOiO7Bi0ltOrp6Bc0DHIMLNHLgSY+87AJezxLTVcVdy3Lz45f2nf7V+6OvZ22ZjGVZT3K/up3EQoFISxgzD3saI62SbAbyDxgERCdJ8BsMAu/vCQrXHJCqiCGQMxqBIqmhgolYyJjETzklLEUUTxqyQkl1tbSN4eRR+/F1+/61qOde6cS7K8HLbD6U9FhxGSWDsQhsiCFGFmjHUoLGenRC77d1XfsHH79P7j8LN87simrMmQHBMLlBgxwJgUjKAClpV13xA35OEismA2DHXrqnztAYQRiCvZiBoUDksYDLNziqvuJlWICN6PuS7nNnhOgAl5KPjgWy3eTipDLI1jDGXOI1TClNZSF1rcGSetz3uR0RPzpNDYkfsCU3LcNrg2XuXdX1S+xD7dPx0ffXsRQB0Dc/mNJ/XlsW5Mu6NK/5bv/nuuz/87vzNH3G1qMp+lPvZ2Xv45MhXnYB6NtEeNRrtfHVB/g1J82QTN62jmu1YlIhqYKfgqJpZWYsC4ALIsH0Dq2g5Gs0yIqgCSup3atlyzNMU96vt1RdpWI/TcPXrT2UYCzQGq5Jv0z6WqNNDVgWIsu0xjiiIk8L1ICAUSAwJzJhw9aB3q/1ZBZcdSxFmIc/gCMEQFRAnQRPTYjlrLpAzZDEkUsIkELOU4s/P3O+9tzg/xjAzR0E1k+O42U5RiVkMq6Y2EgLKRVwVXFUDq2jGquXlWZl2rq7r83eCDqHvm2PcrDZaOMVcEIGdMAK51+s6qCZABiKHM8REHFozG6c9bQZTQYFCmAsaNZmKACRPuQGczR15npxW1WscJjnQYmKqaowutDSHwtVu2K+2g6bhwPAkj+j4YIgCUUAjAGAxUVFkyo6mopKnWHdV2+rRow/K+kZ8Ons8m80xJwgER6fNfMYPV/umqS/e++C9H/zo8dsX7mjuZk8dN+PVX4AfyZXQEmhfV/NStn5+4ZBz3FrMpYxomT2BPzHrGQhxljWSsaFlTawIVYM5EQUjl1MkZYlDyX3arZh8SlFynzbrabPb3j3fXF/FKMloHCMAT/v1/n6bSiJXl8GmPm/3uNtg0/j5EZDX2wcj5GQGQmoGbExQTM1gk7Ai7dAAOFTQzoEDRzHNpmIGIBnzBDnDJJrUAJyo+grPLprHT2dH54E9akHicMA1R0nYhtl3uiKigCMod8Ch5aPTUiKgka9tfmIl5e2zDILzuTFIKuxDfXwm7MTADykh5KJ0QB6ICTB75xBFRAkMzNKUjWzayBRLyY7IVUcFKh23AJHRo2sVRChb0xaqUk68eFu4AjNiZCZ3cDQ5dmZszMyOQ61NmyVJ7DWNAEYgaCYHA/ih+CYyOwzuQQxEUERKzCmK52hpnaeX6eq2zuX4uBqGRKTtvJsvwjTS+7/5m4+fvmG+qY5mefO5BlfAQ0vt8kkIrUNnDkV6A2VJasRUiybJY2iPyTWl/wZJsVoo1Woc057Ja0H2Z5ZTgYpFbVpL3FmWMo399j4+3JrEfv9cCynR5n6zvrqNm12hBnxThpxTKfFQakO0uNlqmqyMcLTg40ckVjYPWiKoqKiKHXyiBu6VEF0EVkl6Bj/SPIIUDa0pmwowsZrlqOOkAtxnKwpVjZeP6vkCz54e+ePu0OmlWtSE2Bs7NEausiTwVC/OSsnSr8TTOE0gUyEDhVHuEBlNhNTQ8rDLMapxLJAKplIQfXkd20sqVjKiquZDV1BEpJTDnqFMEWJG75Io6kTOQUY0NA/EaODNNySikEWSApsdpKNgZk5yUQDHfACck/fmEIJzObumMxUzMy0maiWJjMmEDUiLATIxIsMBUY1obOOkefUCZ6fehd3L5/uN16htQBXbv7xp6NH7333j6Xcehfnj5vKdvLltjz7AwtPu1qh3lx9YVWUphzQKGKcy+TCDNJoWVQY/Q66SZCecSuQmqbmSJh9qg8V+c0/TDpqubG+oDDb2MY5lt7779Oe53w2pz6LUnKbidps+RrQUxriN0xjHrKrjSCkpgjOwlNxuo2SGM4gF0qj9aIMCAZZCE5kZsEAlUNeIpOxBGbIjkUKF8gROzREhQAJIaBmRFi2mvGj15PFy+bgNbKnfqVcjB5LYETKr4ZSTY1ewsD+sV8hmdQNIKsgmmHpTRefRAGOfpgjIiihFECxLMfKiZAY5G7um5FFVET0AgEMAMuOsCczQnAIkQoe1IaghJCmlAGyIyIqE5jQV9eMgoaYwS/utxb0hZ0BTOmjs0LJTESISVUQUUET0SEho6A7NY0R0BKBScpIyFElmigom+vqBqkRqYOyIkMlc8F3Ru5g4jf4IU7Pk3hhrP+WpOzupl4/H/l5vjfubCJ4IAqZw/FSUKAuYGSFhMLFsRYYbRFTwzru0uysmDo+yxlKy17VOWYaXaN/INOb+3qwUHCCNU78FOOrvn5X1+u6bZ5JAHSni7vplFr++135M/QhjVC0TIhE7UwRg55QQDtmDMepmMIjeEoqamYkas1fNauYOrtrDNQTGcPjFxBEgF/BmprZXt40iBMczvZzFo7OqaaGaYZjPDfVoVnPbVrOjaf2ilEgHo1zO0dTAyHxWiSlJQSZfDFzAQ484BCc5wiusBIsauaDoSjFDOdQXqiiaSymiSkQiSVWZvPcBrRITYMoFLEZzRcUMUMFhCMxeikDqU4meWK0K7aMYR6rLNKXkukIeRcDoAO9w6PgAh4YDhhEQiA8wByQieI1pJfRohkdQSknRTEQFVUDLK2GMCXJwjdWz05Li1Ofu7Ps+34+r9eX5ogRzp0148rQ+bvrbX9nU988/6k7OuqPvrF78RUXZl97FYf74zcpVJae4uTHMHKpSFNiI6zwVx1gK5pwtralbAGS5uY6f/3Q7PSOem8K027cnR6uHzeph5RdPhocXbDIaT4aQqUxT30uf5GFFmx2mgpVzXSUHiilSATAhJ6qxQCwGgDlj3E0moEIgpmqOhABN7NUiHgOyoYFEOOQ+gXFQy5EEpJ9yUWo7euvd7p3vnLRdk3OOcWq6ilm1cHA0bm7zuFEBKUVES5aSwdgZoKETrVX0UHexKhqC2jBFQCRHBiCaCFlSBGQ7kCetSJkUgnAxIMkTghwCJ6GuraiqIbIUEQM06ofeciaD0J1QXYMkhqE0DajFnMi8Sz1ZHvIk7JQ8+so59URquY/ReVRiMnOiepA+GSASIQAzA8JrqRPTAfyBYKZgYiZSMqga6MGqqFLUWUx7t72dn7+zevlz5yaeBWRzKdq9pIefl6OPfXBuuQiL05K4H6+1nY8Rynbn8sfp7mOBBKqBsgEyLazEnDYqvjt902TIUwQ2m1aL07fvnn2ZeITVOD7s2nfeKv1tf7+eBry5u01KtP0GNI1UTZmmPqVoKdp+r6sIwwSdx4tjJVBwUBBVrBSXUnml+EMEwlJgylAlCw4IDAy6ikXMe1TjLBpNWYmMTK1MRowAIGa7ZGMxj3jc4tmF+94Pmqffe5dn3bheEUigCnlSlZziuNlLyUVBMseopUg2FGFANcvgGJlByVSyKjs1Y2I2AgNAgW95YIflZURAMjUTldDMAVH6BzFmZhU0QFUSEQADM0nRRFSSlIIA1hy72YXkbd5vbNqR66xtVLRIirfPCKAAEzWhOi3eQ5GkyRiByb0KM5MhIRgd4nGHF98hRMTEeMhQv8aAIKJjRkIDMdODDNhUQcVUJwhh/dn++aetss4Wvl3CtNb9OGUhD7qJRBlKQREvQyFpz9616oL3z9LXfz7tts354yy23ewJdNjeaxxLFk1A7V9Ube27E3aVj3lcmQ+zUrV04lI/7j77VdWQ+XayQrNF1x3v766Gdc4iIrZb5annMVNzfH5+6XMaHWOJe8mCrkGuNBdNkyFpgZysABhBAYtiCdyiUTHACYJRMgE0MwOCSQ5qCfBk6IwUDbAk00gmMDv2v/F9e/Luwh/VJQ+y3sdpBCFUyeNUptL3fclQiohqyapKgE6MTckcZ5E8DiF4QBQVME6CahlNq7o1IiZUM1V1jhWglIwq6FCRMhBqLrlkSUS1FpBiOUeRLKIGCGAyjmhwgMsnLZUv47DS3UOKkyhBmViLgANzHAKRKxLELc0dSz8ivToBhOQUQF5XMwgMIOgYEF4F4QGZmPwhzIiE5BzTtxk0Rudf7fGjAQGSdypf7F+MmMUvLo9//Ef755+kb361Wt9X7VGRXrNOTL442Kwl74JaAoT8sfX3vN/Kdq9xgwp1O7Om4trV80fToHEah01UaJr5Yto8YDu3Ucbd10WsPlr2Uy8gEE4gTuhcmWT/cJtG222x35ccHfran8+Xl0dHjxb9w8P2IVoI1k+6T6YRkEyzmBhCOZhpAQxQDXO2Usi17dz3Y7KHvZpZQZdUhMwx7YsVs9ZjIAJANUBnXqVu/R/84fLRaTaMZiVOY5xiiZoTSIGCdZGSBQCrUgoAqDoTUVEwNRAxOHyEpQIAJmJEQA5RraQsOjgf0ustr5xLToLE7CjvJwDMYtnf2cEz5zIZWC4x53GIZpB7RUTHxszkUESmKZVxNbq+jEWt5JyRrFBVPX4ndEvnWc0VAUUiAAYDQiBCIgBwIHqoWwHJzEwF1IgYtRirOhYwl9EZAZERQgHnEAkPOCpAx+4QXkXnXF3VcAchtFIF6Toog0GRtLVEo/QpTeSgOq8pBOSa/axs+9J/6satbxoBKo5NEbM15igmx8lXXjpKPBP3XoEGrDCerG9v0+0LmxQXc3t5U3KqLy6nweke4rTrV2OKOvYYR+TKzS8QKi4w5fH+6qv1q1aE9M6ZEOeiOY+qCsVQjc08YYwH6QyoQoxC88XM1zmudkMeM5KZR0JER+aCxQI5WuugccAADsC8e+s79eM3Z5YH1ZxHmJJOY8kp56LANZKlDKWAoQqQARIxqOUiAKpKaYpI/GoDEBGRhI2zSM6mQgqpH4E9V1XJJeesxUJogCwlWa1lv0si6itXiqKD0Pg42ThOhBjQnIojAPcKgylqgEokuYw5kwsoRahtFm9+gM1yEoFih64hH4LKRK+AU4cfgjtEgZiQyBT1IE8lcI4cuwOamtExOXLucA8x86t2ELEhiuqh1C5S+n3f5CIGY9+X3ctZdjisJSUwE8kHjJGCGaH6SqigYtfMmXIcExKHpgEEc8bdKXTn8dM/1+yo87K65TPyZ2+H5Vv2Rlc9XOfNW5brtF3df/HN+nay65tYcBwzGKUJyVszd11j7A2gQFQZLWdVR66p6+M5gU4p4mEX0AwQKXDlwzgmIyijHMbsZjaO5e5+9/Zbs7rl4DJkBJA6cFHJogJIiMVoFAWymsExLE/Dk3fPBNl8D1DfPu9LQuaQLcQSoYDqKIVzLgamjgwYLEnKpqqMTFVSUTFU1SKvgV+GkAzMQGOf8yTooqsmIPO1UyAE88TtUd2dN+OQ7263NzfDsC/EOq7yJponmjutWWuHNRhlzPYKfWnOmEkAigEkI+Q6dMLVMERi8p6Q7Fvzzrdfh/rLxSzEBGrMcDhbRIciEgzk1S8ASFFjATMzBLBC5gwcgIIZOjbig7WZPPdf3snDOm1XeHICDfMoVHXOl5QligJBmLJfzEQLpnLw8WhRwGJiNDvKMmgZi3MaH7huuKniZi+bjLwt+QsZR/BVc3zJ83mYHU/b3l8czV+8vL/aDS92AkIkzRw52H4w9uazHn76TOaISjHpR+jq0DWj5VRsjBKzGWCzrKNiP5CZJoV8uIIAkuDV1abxWB5EChWzw965d1yMTEyZQrCcbUigzqrAH3730fFpM25v2Lvbh7jbKhGwowKU1YmCqlqxXIAcE7gsKlJkKgLsqmBVSDmVcYJU5MB9BgITAANC9oiEzls1b8Oiy5IcAyBWdUNE7M3XdPbo+O1367jZbe77m7t8Mzi3i7tdnpKpAzBEgspQzZICsStFyLCYmQGjAYBWbQFj1Nebrq8VTQf3Mn17gMwZ4MHOoqLEr7jk7BgOvMTXL7DXNxYi2qFgMgWjwx7kQfFDzOR8JVgDO/KNSOHqKFfrnPIkkMGw9vV8Pua9TxIqZ2JZIharQjelgcAjd2RmNBVIpcRqGWy9dn2EqlIicK3kbCX5rpLNpr/1sYSSJ174y/np8dtH02Rp5M3NizwMvhjkyRCQ2AxjAhEiACOJ+8jOm1GKOkbdTWhghWQcimIZB5FMRJgJVAHQ4gBffbU9a5FrjBEYUUAEzAjUYJdtWYH3NI0qhgW1iKCDBNyv82Y9ElVqlmJJoogsEFS1iCp6LGApJ0tSKA62TyUlAx2lJA8WPFUNOYchBGJhB4dfcUaTkpm1riFQ7Rw77w198LVhVBiRquXyKS92F4uX776RwdVDobuN3F2P93fTdpumVMyZmRUDT5ANtAioEVJdATddmM3BvqVw/M31A/xKCEdEB4KrK5IPaF56fUBUzZIKF+eADmv7r44fHKhEzEx4IAsdIEXkGA+sIWbw7/zQfRmn1V94Tdoc8WKmjrTzLAhWYtk7T8HjtOtDRT4w6JAkGwQDjnm0NCm4cdh5V6mW+o03ZDeV+zsVccR+vrCcti+/BrWp1MQ+5ZwlkykgHT15Z/7WDzfPf4Xg+93m9rNPUh9hjON+lARipkiaGYZUd4WIVcUHpmg52/p+aBa1EU5bADNC0AN73bAo9SMul56C6iYd1miyACKoAZsSegIjB0nBCmS1lMq+n/rdaAIxCxgDcspFtRhkYi+AeRIo3GeZxB56e9hrKqIlB4XGWcMYajOGiqDyTI1zVQghABpozqMgKGFumpbDHD0iO+8b5jng5L2r2242P9cGx+GOoQlTf3p2/OMfvVO3xy+//uirj+8++Xp82MSsMKZCzKUIIXiHYuC7E2QP8CrSc0j3GJqSHYL1B8K4muVcHIDY6zArHvTRhq9aCvBq3vEaCVMAFYANwaNJsdeyFQMTwtcdgWaG1bJdzFRz//xXibJ2oa2bPkUYNnXTeV90HMZ16ona87dCvgkuAlTFTO/u0NUApvu1+hrm8/V+P0Zpzh9VbZWLYbVQt8PUOl5M21W/uXbVMasTNH/2Zvv4x+urj1Lcz07fbDw8/fH7dfd4d3fV393s7/e7u3X/sE8FdcC0HaMJqMsFCNQBmuc+63onOWFwwAxZyezQYwSv2o8aiwRyBqrCqOY9eQbHVqQgoqKJQtO4+QzTEEtKJsUUiqAWUNMsgkQ5aUm5ZFuNuoq4VUgFktghQ2MeVCGrTQWaCdWsEyWaujDT4rBuyANjCihgGdEcY7dYKguCEkOoQ+U77yg4bRbHxQo6MDNFIBLvoW3bJ48vl2771tPmF5/0Vzu9Xo3DIIiGnkUIqJ6F9v8v7W5gZOCRKufYuaK2HxISEKGTw2oTHPLkhkBIaGasdmiffctFJHpVOaOSHkh4BKYFCoNxQSEDZXLGEqHqQqKwevaNm3GEpOCay2XaczU7k7zdf3E1XAtm8/4eWEuefOWmlC2n0KUyFXYA81Jqx27pWk+dp6qSNLbL4839ShXX/QqJsnLarsPsXFWh36ZxlYedGg63txr3RQdVCzOqwuLs6TL4d/cvXtx+9XLMTITDQ45Zhx5SUjGarOx3ltSRGRJkUEHMBRSU0dTgfpsOQ0+zg2XrsD2MYoetczACZGi9ybQrrl4cncf9cykACjGmGEWAVDVPmifJhn2xIdsAjGAOtRDbwTrBmBWzaFLQEVVBtMS0q8OQh1jPwuxoUZ0sVCaY9lr2ebqeHV26Zgkknq1t5hwY2aU4UAi0uDTUduExxbqbUdW51FaLs2Z9/+Gb1Y+PjjeD/OwX11frtFc0cOpnBuCY6fDPe41LqEIgxKySsykQOh+8c44dIh7wQQDIxPrKFYaor64eI/v263A/2WHcQXxYazRAAIRDMkxBiTNZ4OBy2b14OTaLAceo1GVHdT1t79FQqKF6cjM2ijqrdV+ZqsaCk8mUUxE/Y17W6JphteM6UNUpqgjvt1esNo07tIaai5oXu2efyH5D5EuOEr7MUx42d54ZStKS0/bGt4sq+KkfymJ+8v3vzR6fD8N+3PTzx+3xZnr5LD77etruYZ80GTkvNVJQLEwJYTQjAzgAHciQDEAIiejgcXv1zxcxAjQCYu2aOk3WNLZ/WMe9DT3EXPaiJaHKIVlggmgMHmjJGjNkMwBgINWDIQLBkRAmtbXoOEFXoE3SVZrTduih325PHp1UXXDOeWaQInFdzRyS17wV5lAft4snIjH131jakuTm5C0+OnKurrrlREpMw22P61vo/dms+e0fduuXfDPQ9ZQTSSlFDfkVoYx9CEQHFxkhEjpqfO18dfB5OVA94DhMVTWjUyMHSAoIaq96Q2oihojM9C17/mDC+zZqYYdYyEFT183K2k/bHv2irbrdFZbd+OybB7pYsIdZ7TjU4RGD5e1UPMSqmzMie+9NEaBSrw4SwKw7VRxUc8kyITX1pU79tNuaIgVW3SEj1Y3GmItpoXLzrApNYF90dM5bSanfx8hT8K4LlqY4aqGulF1O6kN1+bg+f0JvfWfse7i9zQ+rabUeUy85GxhUqORBjItqBlNDNmCCA3nr8FMANTz4sRBUQY22Q769889frPbblBSTgDu03QCYFBCVAAhLAkRgII/2ahoHRnyYSMKrNREC9ZCNdqZjLLsE7aTLzmaSNrf39UBN5XkxYwORhIXnR6fTPubtc0n3zrfN0WVov8c0jlcfWX5w7YXjEYRmp2cAA73/4fr+z7cvbsFRomYcp5bsCcMAbiNZS65nDTkHzAoEwI6Dd549++BdqH2o+GBEkFxM1HvvnDu8F1ULIQsQm8EhRQ9wCLoSooIdlKlmCuAQyIwE1B0iRWZUii3ejs++lOH5/L3f075vjq63g+1ebvXlQ2JsHodmQRWUWUuhcmnSbMVXoarOcNkBgRXlJpRhF4UTkIrl/VhfPMH2aNpN41TQt+gCSym5VHULVIzrpCLjLg47BUyTJBwQDbhhz1JS2eVMPMZv2Pvcb3JMbTtTAcGwWODp05N3fyh1Ravr9fphd3/P1w+DJJBcru/H9WBRTdWA4G9SvgCvAF4KB9EkGqji7U5ut9usEA2aio68VoczA3CYVmkxtcOh0SKoYge5lnv9rRFRDx4/AGIGJgAw0aGU3ZQ3SY4ynlmZJ9QO1PazRaMqDFdEpakbkRbUKN2n3X5x9q6jk9wdQ96DZg4QHJSys7SuZuHkyTkJ3N1ut/1uO0nJRIjsxqOWcqRpdGGx9MzsK8feOeeDdz6EKrhQMztm571zcvhIz1lfX0V8UMgTAhiYgoJiIUBV/Ja0eCiJVJWIzJTUQMBQTQEBoa71aHnSvo1hO4072T7gONUoyVmf7f4rc8tgZVwGujim2cJX3k9jKWUdh62YIaNvKvaVbncik0Pj+TzM5qpREbFeqJKoxn0vJgQEjutF68wmK0273K6G3ctfgyVih0yu7tmjb2oMjWI6gCioCkIqKYdu3hy9rcTdLMh4c/bGO298p4Ey3r98kVNUgvWD/fJnLz+/SqtetUAGAVZPB9K6MpKqFrMoSIBEaABZ7PARUIr2pMhABkzIr3oeWNQAQBUAwBPJAf79alMP8ADqIQJkdu5AhFICZ6ZFypRv4jTcprOWF1NpY4kxd8Gn3TCN29nR8WzWzedHedpiyRMXF5bd7NisQ1YUyP22SGw4bG9eDC+fxyTgPIAxmDE2nQPAIj1v90n6UpHzJwj0LYSKgsPg2TnvvDt8dfNZjPHVQOM1xRfNkT8YC9AxISGBARw2AQ6xxb/JugIiG6BgwYKGgGRk7tH37OauvPiruMmNuTlnaWEV4SpBBMV1f3a5fPTBu+XqKg8RLVMDOkjxlVWMU8y7yZj9rCYCU51l3Aw/haqGEDA0rqpTiupc6YdQLyxUMWcVISaZ9lT2vgEOnXOeOUxjn8ZJS/GNVAs/9HsRIUcAZoCpJFtfdUcn+92gQx9mjQtUtjeKew48nz/tFttusfhbdPbiLr68Htb3083VTouws4PMlphEYBRriAhN1URBCwOpog2RUa2tEZEB5JXuEVTNRE31UGocGi3kvRMwMI9kSACEgOYYmA+TMKQAUlvRVlO6nab7h3g8wPEOHrAA49liPLssdqlVd25MnkCwwzgyFFd552YWQhnWZRxVht3uOQIg1jJsncOuoaLaNt4IhwJ5SC5N081LD1WeeRWRUtiq2nEwI0TnXNM0bdu6tmmaqkop55TsVdsIxFRzMVX1XgGDHQyXxO4VBI+YXreYDhhrVAATYARVETMJzUbmYUqAGD3s2/Z5Ti9ElTSYkOff/4PvffiTd4bpvTjw9sUvx/VDXO8yZGZf+qiloPfiW1QRiXEUY2e6zqUcXZw3bYvzRX3yRmgHdt7YWYwOeAhJhtF1dPnBYtw9pJSNbHH0yFIPeWBHEjecSghhGEYgF7pFjH1JUZGQxDnerW6G9XVg7Edp25OHdY9cZufv1SEcXUwf/uCiiPvyq6tffvTy+mWcxigKagAADGAKRUHUirBDWLYsgog4a4hJVRVMRVDLqxcJAYKYBw1gphYqOlm04PztzSpZAADU7JiCedIMELDpKHgAEPW5NFNsy5huY1ylxAD7SZ7epv12c3+1268380XXzlvZDeS8a2ZM2tR7V9d52pokTbFqzpuj5wopL7W25mGdPWGeRggUuMqeSha7fxiwzmbkQ/B1jcDeifdUW91UTdcebJikCHXb+CrkcQJ49cFFZKBmAgo2UWYwn82ZOMfonBkBMKAh2QHpycgEwIQmBZHQSnr8oxQa2O2iNKY1fvbLunw1RVGF73349Ce/+aHWbeBc1YPLyx3lsQ1xGnMUAScIaZgGHsHXaDUlC5YFEnq3vluN9bpJsSPP7ZFJwhypast+8D6kSrKVrq4q1Wpmata2R1V1LMPGzBCMARzIiy+uYxokKwfPbVdSEjOwxGxGXIqlwjoMOWVqZ5Bg2F05EqTadUfvfufp+aP27mbYrIpZdX272jz0wy6L8XacxlHMyvmyenMm02jJ0LP5wH2fqrbJueyLETOSsXOhaM5FDcghAY7r4ezyaGMaYvQBfEBH7FRAJBWRXFMIlXcZsJi15GLrU+VzSrnEQHg7WbzVi6hDujlf+mXLnrE5eeTaOVKZnx6F+UUd5qk8mHAxbZbH6GOWKQtAdbrZ7m1KplasEHLJJZvJ2Jd+7aoWgFx05iuqzSMioYDzrnF4KJxFPBHVVc4FiyIZHpy/Coxmh4LITFVVydQURCwDEBxQ1UbK4JDBDp9hhqrqvJ7+IM3EZevyeB5TJdN+u/3+b33/Rz9+g2R0zbnr2NaTHS1dO3ebB7p/6YOG0EqRoceMpjri/ImbP05JUUvpV8P2hjZjtb1b3W2bo46rQOyBB2dABaftOm5WWleLswtDI1GL2yyZHBO3wQWW+7xZd2fzSiEloTqwx2IRVYgc+C7nlPLI1KYiZmQxJRxyAse+brxMiQKy4ydPz975TtctjsGFUoywUsP1Znt3tfv0oy/i6tbnyKHoepQdFANwdDRv1NJ+GEKoZouq5EQZm9pZTGZQgIpp6nfLmTdlJHWi88Y/7FMREAMvkaZ48ugYoPTbDVIQX08Ak8Nt5VPx5t0g5cWkeyn9KI9O/dKX1dWXTaD2rEvTrlqsyNni/Dvd0fub8aPiX+Ksbs5PdAczqszSWGKatJBT5KQqAKJAsXgU5VSY80Q9WKjb7rht6oUPwaVh76oGRImMvAODlCZQMFV2fBh8HBaDCA5CMmIkx+Tca7EUOURngALEBsAoUlQNjeygxrSsYN3xiea3T4+/+eCdY1c2QhakTQmwIUxa1a1aDg7MoY5Tjmm3349DZF9P6YH3OzTPR++2T/72er3eP/vl3csvJa7rCmfHTXM893XnHYNFTZmMTSGPCSjWzvumKhnIBwLWPKWs3J7NTxYZnWBhLWAoRUQFoTbAYdyTFpGIptw9NvJFkiFlEYwJpuhbRUKlyNUixk1t7aM3vlN19X79cHrRfPiTd3/zb78bhyHuhv39+uFmvVkN06j3V9dlHNOQUIRi7LhNU8IM8+OlsIhqEijoPJKvuB+iJzeMwkGAyBRUTUSJYL/tQ0UgENDqQNRRethtE8S625OPSqPpvVT7QVdSjjucQ/BTOtbdvETRhJU3+zqqg3CuwJq3VLyz6LlJ/YNVkJPLvSiOJUPCyhQDclWFEJxp2e03ynw5m7XdzIfAwbkyro2DI0o5k5n33kKIKZqCpEIEosamrHIwrKIZqJmBGZqJcwCoKhkVCZmZtKipITgAMy0CksEKmqu77vK9WUy2+0SKto/fBdnTsAG3PDr7YRq3UHZcvTW/fGtcPRs299XRsH54DtiEVKmkRejY71df/Ut5GK+/2mhMmnSajF7uLp/QbFaYpald1Va+acHXuRCjQHBZSi7YhFNgyvsVY2shQL2YHz1CHcfVN6Fpq6btd/ucC0JoZm/v1rclFTArZWdMZKYliZYUOXRLGRNw4sqPm01o23CyZF+tr5/l3a2o7ADZN8756pirqjl9gvXyx93xe7v99u7ZV6ubh/XV9uarF5iKuUaVT966fPnpkMc8X7auqe5udykBGkqxWDT3cnQ0K/uBDaVkFGAxb+q9Y1HMaX56vBmmdjedSx8ZR4eTwr49gjAzKzuVXgQt3+ymCygXtOuOZhp3D7d/6tv5/Pxt7h41lXD1MA2bZrk0cbs42FQIKISwL1CF0LQtOydaDImr9vzRm6dnF03XVnUTqsr97T/6g3//Z38K1TkRW5FUCoXQ+LaknFPJUgTMgR0IRAhQ4MBpYWQkO7zCBJ0xshlmQzVgJDo8NIiBvUdatPVJNdZeandB2loqKY0EO9aS9l+m3Y2q+OC741odhdO30Xfb649nTR2nePTkbXTBt2fZSs5b629i199GxRpdMEDa3o0P172B5qyLZX1+OZt1VAWogsUHMVREi7sHrDoGr9Kz4xDOuuZkHG9o8SZDFuJq7jmNKUk7P4YKNcN0/RCCJESi4J3bre9STlwxIU/7dY5Q1YU07UMlKbvA6gJOfZz6kl/alF3VCTkIHBZsal3TunfeuHzr0qY+4W/U4TRu7r7+7OPd1R3A4/X1namSpEAwJbWsHHzHmMRA0Uzz68WgnNL52YyNdptx3JWTU2vqmiKCgeyno0XjmrTnaUQrzqfQoXNohFauUny4mc7H7HHluZw8aotojYECZh/N9oWc65p2kiI6ThY8u+C4qRRBwIjINbMnT99//93vHp1ehKZBdKqI33z07/79v/rv/+2/+OfoWkBQ0WIWQvAAImUsJmav9c3eh+Bf6X6C8yEE5x2xc8iOkU0BAZxzhIAmpofAmJ53cNLpyYW36X5c/ZK5A+vAdiaDbx49PPs651Qtjmn+GLCd1l+3p2+n/WZ7/YWqGrnlWx9Uy/M45v7utgy7/W59/cWzuy+vg2+p5s1uigODNyKLo6we8iRQNYcNS53XNp/jvIOuwqZ2PG9n8yM1o+7MHZ+Rb2zcsOPm9AJobKo5IOq0LQxqnHd7MwHfVKEuauvrZzLsYxwITCRaETRHPlBVIeHZoyfg2EpR1GFzO+32ClDPjpuzd7vzc8gD+6PTJz/aba/KeGWqPizAgZUY97uU07jZff2Xn331l5/d30yTgRl4R4Q2JIMQcpGsAogeofVYBTo5mpfcx5SPlq0D7rdpP2hO2sw9QTmucJdhMjXv0skFLs8rHyC0RACqVkbrd87WT946X7bgnFMF0wwYdutd3KxA8eF6e9fDKszC8ryZLeqqqufHb7z7wXvf+eFicYzMAHT4xHG//Mu//tt/759aiv/mX//Lwo6gUrUYo4Xgq7p2klNCAkIjMDMrxRABSZBjEUUKIMBASofNWFRVOOzOMgYoreVHj95eXHTe7SB6H9TGTVZx7kzNTdub9nQm+wEsWd5gDc5T2v46J51fPC1YxxhtnPYPH+Wpl5zD4vLi+P3Nzf3xWROa2dEbT16+GD/5s18cn4fZccOuOzvZj0Py8+Xd4L789d3e/Of3iQnmLZx0etTl40VsF67exSpN3M3j5np+dEFHT/f3L20mVDeQswGpqQVfz88lJQLDMiyOT93503G3TsMmT9s8DUQsmvMwuhDuXnxJjPOTt6tZV/SB6kXtoemWIdTrZ5/kMl6+9XtGjMDIddHewVg3Z1V1+SBfsPNdCN0fcXcan3+0fvlyOD1vdnfD/e2kZKCZ4ZC3Uuc4FjXyx2+/FXd34/ZBc1ImNHQIJVhKExncjEZEzqPgqH0PzQzYBQdNO/dVTT4U0ZKnTdysb7c+baHsjs8vZrOKqVdgkdzUoFsj17Xdyezk/Pzy4vGTdx49elp1C0FiwG9H9e75toaffv4H//l/jaH71//T/zPFyYcG0UopzrkQAjNP0/Q6PyLo+GDcPajmX7HPVBUQwBQQ1QCAiZ2Vi7lfHB8vTxY67UXu2+UREkYP8fobKcnN32zf+I308Ckev6eqeViLRTefx+tPFRpopDt9smyPhvtneb/RtAnVrPQPWNLF08s4D0Whmnfb1bbloPusFbWP2tnpJeQ0bXce4vw7c39yulr1X3/zcL2LL1agSDMeThdwspyOF9v5HEPNkIukvVpkuZCVxs0tVp0ocN3k/aSxdx5dVTtfY3D+6Ii81S2noQJkNFDJRqgKQICU4urBpr0BCPtp2pKroEzBtyXGq2d/JTHXNRNx1Z74epHL6EJolmdpe5/Gh8eXJ5fnj/cPaRH2Dy+/+OJZ+9U3cbUuBc2UZwsvJZViJxfnHF7RNdg7LeXkjTfuHtbx7oG8lyLA4B2qgxJc8Q5SHMAyFiIXvA/OLectVcEAiormaONkkNYSdykpV8aQgp5enLx1+e7F47fmp2fdbF63nQ8VHl5R/Dd2b/evfvrxH/32j/Fnn/zB//KftU33P/4P/9eYc5i1IppSMrNvdbvBMREaqOVU1IExgx2UnMCKSOwQzAiA2Filsy2NpX3akq02N2vSXbNYFhMLrQBCHH2nOt6QYwqA0JUywrCSPAm3lvNw/bUI+W5JdR0ePZLrEdLo6o5rt5id0sUR+2q/3//W757zb7j1y6uHTQ4kzoox17O2drtFN6K/eefD86ePaHO7Hwb46nZYD2X1ALZKgXIVqKvtuNtdzt0syNny5fyogeCpaCqZx3a8ucpppDpUdeO9WahCPWNUtDw7PhE3NyCyvF/f6biHErdf3esUDxO9UJ35KgBOVXDAHIfr3EszPwerHQYCcsi+PXJYl5IMHaA0TRW4Pbt8a3Pz63Zovn8U3rjUj/7D3aergk3gppJJvJj3cP3VVzr1TA69A2er1QsTrToqqiogCloEmSzMgcJhe7SkuNvcxWl/4d85Ob5wbUVEIVShqoBIRLSYftcIfRUqrKuqqZkrADByhy36g0njMAE8HAkAcB/99X8Q2f+dP/pj+g8f/+Yf/ucK8q/+H/+3EpOfz1BUVIsIEqkZoB3cmYRODk+vnA/NIWZmIWfs2AEialmEUPdr1MTxcr25KptrX1e3v76aPX4XrQvzx9LMpFrEq18SCtA9dY8aOhllcKGpF2H78nMMznmP03ZcfUrkQ9PSYskVG4APnkpM03q+nF+cvRN3XXO6PAc2rMrYT9u1TTwvNA6qOXNeXXTu0fGS0L17G67vN89u8XqT+6Jj0nWEr9foIDaejqr9shnPz/2jpa+dBdc3J7OmXSiTC7Mce0YQLAWyqWWd6nnjqqoME04DO0Hnoagjh865brY4e+J8MEhMiMSxxBnNjLNMkXyVvEcfZvUjcyTT2HRnMmxUehz64pqC5upTBfJzmh/nk/HhOk/rTawDec9xv1FUKyB5JIdV7UrMpOocI0ISE6KMHMkjOEfog3eOkZh8tTw5O3l02SzmVVWHEJgp56JmjjnUdQgVkSfixHTYtGAi5FcH6HBi8LXS6RVc4Ze/+kswbLrT8JPvlb/85Y//+E8c2L/4H/67uNfZ0WkgF2PK01RKcS45H4iYyMAACA65BTmkOQ9DEKfmDHWa+UFlDFU73r/sr5/PFlSGz3NXwz0ROuag0zTlKZboAxE4irkKi7B4VIrGOICDcPxOPX+UxxWXTsrkKzc7PtvffJ6ktCdvat41JOKKn4cY0bVchRnTbJ1uZnOAhuLoT97+YJrG+PCiRQqzLmd1II9PZ997p9/s43asnl8Pd6vYzdrl7AB5oSnbx8/tp58OtZNlC28+SW8+6tAmH5yi06RN66E21yw7blfPv/a+yiUhFUIOEPhkgRbQcjh5Mxy9EXxIw7XknVgRk3Z2TD6IFqKQpnVOGyoRfYtEJY8cONAb/fjFuL5CdJkwjvvtCle7nTqomfqxVDXXrc8yMYNjcc69ynGpZaVgbMg95kxsHKiqXKi5Dr5pFovTk9Pz+enTs7Oztm2dc6qoZmoUquZgw1VwABDBwISViRiYDivM9CrHg6+3pF+NQc0M2/kxM73//vf/1u/+4R//L/7oiUs//J0fffmzf/3P/y//xwGqdvlIVXJOMUaTPGvbuq7ATI3IeecCIAHAax/vgZiPXWVP4Db4RXAe850Bst8TP7hqZmAxK4bTafcSyMi3BEWrRagWpQxUCtVLkYymWM8pp7h7Sd6hZ7asZYy3d1qd1POnefuiWbaqWp+9p+bi+np/96XjCpvOh9Np+3Xar8LikqGe1i9KyuxDjHsZhhA6FU3THlyVjcpgGlwgn4tIyWO/6fd0tYOHge7Xu9V28s5OKzxyuuzqGoVd8W2oZrXvahd81XZUkWr2rvZN52fH9XwhZSJ/XB+f+kB13aT93di/7Lon3dl7cXtTdCBsEHxMd6DQHl86ak3z7uHXXrS/eb69u4KmMUm3z765+vX05bP4UMwYS6Ic7WThmUuovaqmAsk45nyYbwfvipKy4yr4qmubtprP58cnp0+enF48XS6Xbd3Q4dNKFcl77533hKhqopKADmE0Zib0AEjOsXPE/m+WoxHtP/oqpTjNuUS9fvnNJx/9cj9s/8F/9o/Sv/vkR3/r7/yT/93iX/x3/4fbh2tenCLXoXKiqc/FiBpEOpTMqOgO+j1QFUQBNBSeaaXWZijS35mt0/6qXTg/X+76javaUszGTb9ZMVT+7E3BfX72DXJlACVuISX23i1OGDN7byScBNkj1jLuDbNzPhy/5Y/eGG5+5oNXHQsiOOvm53G4ahYftJff5Vvv1l+TiKuo8ClMpenO3Hi3u/5G0KpmkaFoym0zz5RmT7+TdaQ8QD0vRcvD/gMuon4/DF9//vLrq7KfbKugMc9r36DTSbfrva8G37nQjqFyAGOoK3Ohqu7aWVdUqnqm6bJezLFvQlXz8imYG7dXKW1BindYyiDjBgk0L9AHR+zRmdw1XWfwaBzvYsasMAFFAiBUdQlpK9N+I8FTmAqwVyD2wc2Ou7YLde2ruu5ms+Njalpmns+72Ww5mx3P5p33dNjDKVIOvRgABwDFVAABHRySx99+SL0aOngGh8jf5ngOf/vt6VFVrKu5D8HAunm3nB//8X/6D/7wj//uEQw/+OG7Mn79p//3//YXX925+blz4aDLRNPOezBTBCBPFNgfpGPmHAZX1aj1/ub4ZDkPU1r/UvqvcxzQtzA7T1J8c6TABpSmO6KZb49FY97cmAoio2/Es3ddHThNLyks2+P30rR2OmjeE5fu9E018vVxiaPKcPr+75OntP50WN06v9ApMgMvLkFSXH9hOdXNCTenOY55uGM3H/pd7NcmlPrBzTtXH40Pz7FqfUWOkKoZcFfEBMVhIyXnzXV39v6wG9L4YAgAKnFn47h92Li68oxlv9+sdlPmYSoq2dcUquAqXzehmtVh1jbdHNnNTp9WVVBwqjHF0bu6lH0gX82OAHBx+W6OU9xeB9NSYum3D1e/2g+y3+W7q/yrzx56dbuBbHlWnZyYKHvnK982bVM3oa7ny+Xy6NRXbagCe3LeOfaH8EwVgmevKqLlIG4nIkMQETNEJENkxweHoRzMuHhQFnoAJPSO/WGF8tsDpKqHO0xVidDNjo5UdBr3Dzc3u83Dn/3P/6Lfbf/O3/+T+LMvv/dG80f/9L9Z/um//emf/2nR47qdkUPVXBAYDUVQy4Egbs6zYyIvCsoUaAz75wID5huVvWQrakY6ylSVUShozjln4h2X5NAbNyn1qgJWSJIFKplykm5+2r7xB7x9ubv+67J/6Zkl3xiR93fs22qxLCWFujOoDYxcHS4/gLiReCeyCVVN1ZJdExpynp1VcdwzSrs8kzTMzi+Vj+K4b86fqiSu66aqTaSYtrUrxYgIOq9V65fBtTDer8kF9k5Lk4fd4mI+O327lDHt78+HSaZ0+2L9/NnWRCEZNR59UOH11c0qP/NVtb+9aZoWUABRUUIIVdXp7LhMPZEbxyFvb0lTtikPO0DvqIKyr+p55ada7zZZjO34bPHouz+gULGjuqqqUHnvDqukB/iFY0QEMg0MVR0cu9f0BR+oOjx3yiscGgOjGSA5VTxssx2IBwiO2R1uGmQWgv+47jl8k1fbmGo5FZezAigYhlCBwUcf/3y32+73u7//T/4Z3aSnR/53/t5/efTk8U//1f97N+2a+TE7MhMoRc1MCoAGYoeO3StWfmHiWae7rzQ+zypphHHSglOZHrg7FjeL+7XkbFac80pglWdHqqmUTCS274vdHzbWBnq5Of2yDKtx2FnOqhyHFTFODKFdoFs+fPHX5Mw1DbrOzIimglHJA52Rr0NYVB5TfGYExpRlmtJQdUc8X1B7FJqLKp+l3KNiu2xKf1tyquolmolO1dHTYXVFUhMMjgc+bq3knHsfPLMXIJ4xy6w9Ojab9nfP3rs8fv/3j1KGcXOrJVezU9/NdpuH/d09ainT0E8P7AwQUHIhyt2szrnynh1bTj7UosksxvVL355Qu4C7B80eIjlgx0xIJedxt3YhhFDlLFCVEnzx3ntPxMzsnauqwM4bQEpJuDB7QiqlHITuzEzEh+SNoCHRAVl4eJMbMxIyOrNXC4MHD9grFRjit0dH1XJOKYkKuOPjy83u4fTpRb9+KFNfV/WLl8/6/Xba7/+Tf/xfiH9z/OzlG+/+ZLmof/5v/93zF1fV4hSdV0RjQhHLOaXRVB1kVkehIqu2dObpTeq/VBjjGPajKikvAmAYXnyhYyyGWHkEQaL2shWBw50IRZQqyRpcxbOj2O9Xn/47V81TvzHxiAHauWvPZffS6vPES2LMq6/8kI0MdeU3t+y9qzviJqM3jWmMlpJHD0RIEGbHgETMznnSO3bzevkEdZ+H51IemOZsRaY9MJbdC4JSLx8b6JRWVd3mKeeSna95flZ1p0gKeTSJWqaq8VX7yNqzJsPJmx/02+u0W4tMi+NH85Nz2V6XcZdLrGfHLsxXzz7t19upvx9vVqHtXFvXs93ht9e3jZ8dubIuDw+akoFPWZMimx6IRLvVQ/A+VSFVFVcVVaFyofahrhvfzpi5xCilwKs8MfvDBeWD8xUiAXoiBkcH1RcA2OvWDiIROqJDh/D1xjcaoDI4VBCyw1X0iuaRhZjbWe18gDeevnPzcBuCZ6tKESbXD8P/59/9i6urb/7kn/yXP/rhT/Yf37799sXv/sN/fPrTP//sZ3+ZXMfdcTAVyeZJk5pqKcUQ0PlcMiHe+jd98zvx4dM8bqdRIXjcjLSPJU4yZnAeBKoKJcZyd13VteZJzOp66V1Iq+sSEQIQhLhdQcgSe0QpVJNwkYKuA63zuBZLUARDKOPAAEUl1NWQhsCDpL2v5q6eOXH7/ku16LALdU2h9aEylPjw62rxNNBxGp5j3rGKymq/X9WzEyRC08XRI0Pfb56rWs4x5+yIXLdsj96q6lmOL1KeTNS3l93sKergqrnVlmXyFeXdngTjuAVQkeLbqq3noT2byogN+oSVfzytNqsvb8U7c6Wuwryr2qO56zpOm3i/KetYTMY9xlTAMTuHxDFFKSXm5FPycXSeoapD1ynmUfbbogXZ+5pDU9d1VVWIeKh7kJAPQDpiY3wVfyBCZnjtcYJXbDz9m9cWIpgqHIRKmEuZpimXbIreh7pp1NR988XH73zw4ePLi0/++i/rtmtmy5ImlRIlffbFJ+v/0//+7h/+s9///b8TvypPT/0Pfv+PZ4vms7/82e3q2s3m3jcOsGCKcdKiygFEDBS9R/bx9Ie5e3fsV8P6pqwfZPWQhl1JJqXMGqyPHPmAanGzl35CD65ZQKhznkoeypScFQBGUghLNa9TwkryGAmEgfuHZ1BXgIZq6E2NiyQSoHYZqoXKZODylEVTQp9iQ/WRoNE4WI4+BlAtubfNy1gEtl8TpqwmWrg6JYiq1rQLku1mu5e0ZQjTtHFchXDsGcimJKipADjumvrkh3Fcpf3XZbgvJsjoYCLsixWz7Kn2oaLaY6jNdTJGH46iTnGz3t7uVnepSKSaq4rGGejNru3CctmiuYKyXe3T6BFAiLVqs2RJYJX3FkiBAQMxmG622/UGAPBws/pqCvVENvfeM7FzFbvA3hM7OMAPXncDAdE7B99Wx4LfFjqHAwQiSAhYxEqOmmJOWti5UNXOu36/mu5/jVVdo6svTi4vHr/5/Pk3UxzTsEpxypDb5pSZNI7f/cGH//R/+9+89eitpd68/c5Sxs2v//xffvHsSt2iqhcAkGIqRSgEdFh5Dt57YiIugCWLiYimlFPcPfSr1W67jeu1xh6leCsqhZlCxd1x2x13rMkZKFFztCADncb5yRKI8vYWDByzqTbLZZIJXCD2ZFxXMwiuaPYqzdlb6CskBCgmk2s69vM83LMl9M5ZJkQpWW2w1JtmAHREgAleuSOUHDHP2XkpI5gBCEGtBL6aIWBoF+iDb0902itkBHKzJ3kaS1yn/taF07B4M/Uv48NXUmKcJijmXK1gyK4Q5v20evFyvNtv1sPdCjSKqcIhmlj7duarmtrGiZZhKEOf9iM+DLZlP/LS13UVqrqpva/ZeXAI7oD8cgjo0DMTIbL3zaxbLI9my9Pl8qjt5s4HDo6IER0igTkkMH5VFcF/tGt6SCJ/O+diIgAoIqUUKWAA7J2vG81pevhKVl+vXn6CoZnNF4ths53NF2++/f4k8Kuf/4eu6VzdTDExYO18TLuj4/N/9M/+6x/+5EfL+PD4rDk7wptvfv7FLz++3xj4hZFTyYQSiELlvQtArMwGfHCyGhhIQQAFkiIlpXHo+8162myH/TruNxoHkIlJWc0BknfsyTG3bTi9WMwWNcIk0xiQq6ZNaUICV9VIjsgBO9+2AFpiT95X8yVRhYZcV+ScC0HRqEQKHTEjiA4rdKHIaDKYZURHVADIMWOZTIsVBcsYKkeKlhCCb458dyxlIk8ImVytOSG50BwZUZoyIIglxgDUybSnaUs47FYvpQBXs3HK0o9gIhY+/+vnEGVSd/1g0xgRTaWo2hSh7cLJRVcRjsM+Rk2Cg+A+YY9Ow4zqml3lXcXesX8d1HLO+9c+NjJkapr50fHx8uionR91s3mo58459o6J4RA5JkSiA2DxMNUyJREFPEwUDAAcEAJmBVE9TBrYBfYBAeLmdrr9OD68+OzjX/z0rz7Hi8fvOcfb1f009m3TvPnu9wxhsxlMFUl26/tp6AGsqRdN2/zh3/u7v/fHf3LWumMYL06B5Ormqy++/OyrbQnoGq+xIiIG4gpCY94DOkJCCqYCJqqqoICAzAqgQFQ0Z4n9pu+3qV/H/UPeDzoNUjJKySlaQiaoWxdqciRnp0eh9ahD1fjZck5AjC5LyiU77w8PWV/PqtmJlEIwIQdVc8GDb9m3PngrAxMBYC69pHuzidl719bHbypQWX8JANJvtQzNyZsqxeLWdKxmx83yAjUqiUlWY6rnjoAhqxUAAp4jt1oGkdGyoGnZfS13L1VNXDOOmHZ9jjrkbj3muNrljNtod6v0irdoZsnAxLdhfnJsVvrdNPRpn3Q7gbVz13RYOfYh+BDqKlSV9z6EcChxDm1iQw1NfXL69OjsYrFYNHXnQ+BQHfA89AoKhvLaQHh4VZmZCgEAYDnAfcwMippqMVIDInTOGwcZNuPtF/3Lnz//4rOf/+LFp9+sV1PByyfvx9incSglN+1pkfH87OTx5XtfP/9qs7slZg+cYqqqOqdEWk4uL//R//q/+sGHvxmm1TFv3njrLK6effnJX14/X4H5qgtSkpoX8uAqcoFD4311+GhFQjE90BgPfxAS4sHEqapFp5SnOE2bNOynYZeHIY19GnqZJilZJaEBMnjE4Hl5Ui1P2vmiI7ZZE0wSgCJ59jX5OnSd5ggCBkoMyAF9gwiOmKtWZUQTSfdMIAZVd9RdfH/KiuODpl3cXDfL89nF9/vbL1V7TRvTEUEYVbkiroCdmy2dC2hiXEHqzdR1j8wUxk2J90ABdUrPP4u7QSsfk61vx2mfNmubEhi4YlqEV5tUiprzIgpGVAQIXHDNycntalzdbCejPYVqVoe6rurah1BVVQgVV94FH9ix83B4gyNWzfz4/OL07GK+PKrrln1FxHRYW0cCRGMkALJDMhsOLpXXyANg55xjVZJSTO0AlVKuibBM/bj6arz51e0Xn/3sZ1/+4vOr+yENQMkUl8dP++HhaPmYyCHiFPf99sE79+TN90RgN01FBiolT0mm0WrnnAPRv/Of/cP/9E/+Vy3TscW333nq4eXN5//m6quvx/0IEIjaKD4aqPcUuiqEw6uSmY1edx3MXjUbDj1RRDsEqM0AFIvEkjTlaRpTP8Z+PU29DH0ZhylPljPkXEoGEO/UBz5eNLVXBOjms9OLRZJxMT/3dW2+imPPkHNOCOB91cyOCqsnLzHKeBsWF+QD193i8ifAoV8/l+HK8v7kjR/79mz74qfT3echb8t+nW2iuk1WAwYMPnQzYld1F7x4c9xeS3/lmpP549+K/e24/bWHCk2n3ZepX8mY01j6fb+/3/U7k0KlUCq22+eYFRCnQmoIQBhLU+O+GC3fhMun+80+C4iRWgQr3rnDrRNC4Cq44AMdZO6OHTft/OTs8eLsbNG1lffsvJE7vMIQkZCJWQkAgBVMzcCI6NAnZOZXoFSznOyww+OcRyJN4271Il796v6rX3306bNffH57dTduS5wAilpOE/7+H/z9IeWHh7Vzfhw34+YO1ERFVY+Ozn/wG390d//iy0//auz7qq7JNXUVdpt7RH3znff/5L/433zw4YduNz1ZdpenrPr1/Te/uPn8q91myjAvVKt3gh6JHDM7B54DB2ZGx4hIpq86ngiHDgS9ilQjHhavAc1MVCAVLXkc+5yTxDGPQ077MvZlmGLaxjhYjCZFiyFo3VLj7Hg5d7VvTk+ckyqgY9fNj3y7EBRkCLxAdnH9DNXIUXv+9vzyxzlv9vdfqU6oOVRt1R6nzefT9RcQe9tvTTJWrlQLCDNjB64B15lrmvlpnu51WvvmaPHot4rJuHluaaLQ6HhreYgPD9M45hLHfp92KU/c92kcbbcpgjIpirD3PmctMXmGrbBw+95/8ifmaiwipinnHHspmYCCq6omhDqEqnO+IkZ2VFfNbLacLY982znmQ/F7YDUzudfbFwjIh8oHXuN/jA94ZxYRETUwpgOFN4gMZXM/3nxy9+KrTz559tEnz57fr7a5xCJJbcqSU1JVPDk6e+c7PxbTq6uXJe6BXBr3h1F9SrFuqpOTR+zDarPuludAPG1upv0mpp7ZLbqjn/zOH/z+3/2HF7OOy/jW46OjdsLhy7uvfv7119d9z1othaqSjRDJO6xCqOoQAnmHSA74bxiXpACv3gXfZu+/fQ4crlnVQ/q6FMmSo8WYpzzEPk69xlGmfRljTrHkAXKWnFQTiLqgoQmMdHK8aJeN9zafdcvjRXP6tGTVtErDXaja5vRdQkq725S2vjkO4ci5CDBK6iEOmicVLWOPiMYeQvv/LezKdiQ3lmtELiSLtVd3Tfd0j0aSr2RZsiAJ98qAfGEbNuAX/72fbFjyzPRMr9VrrSQzMxY/ZPVIujBsvhZfigxGnIg8cY4p6gSVgKO0QnAGAdEaZ03ZR1sZV40OPleO3fLD4+V/cmhENHSBmjYG2W3jbg0Pd40KNgRosPC+Y2GWxNI0SAon333n+hNrnC2ctRasRURf9Or+oD8cllXPl6XzhTHGOV+UhffOu8K6AgBwr/PtAOB5Bx2MsVmMFxBU1TmnoEkiMakYUDDWWuessUQpLhftw7vHm+u3v5z/8vbq/Pb+qela4ShMRCEwPXN4cDI6DDGcfPbpbPby5nKxWT8idiTKKXEkX1ZgDHA8Pn09PHx9ef6editU7WLs9fsUQ7dbz+bzP//Lv33749+PCztEmg9oWq3C5s3Th8ubh3bVWMZaoTAOjbO2LKFw3hfOOosFImrW3LMMkBGb2StP557hNxyUrJC9R0+ioCqixCTMnBKFNoWGU5Kwo7YNzY66poub0AYKMZvFkCQLUJb2YILD4aAcjsseCHXO2frwyFgvm0cD7fj0G1+Nu/ayKApQdAiAiYU4BeAkOXEWfTVj43uhW1PXltVAQZkbEAZje/1pOT6KsWmu/ovCylifElAXU4gUKUVu1nq7WLc7IPApJUBMBkVN6HjbMLmqPpj4fr8oS1sUxjrjvfXFeDo/Pj6dzOf1YFiUhbXOoDHGmWweh2hs1vhARcimZoCKAEafx80GGVFFmCER5cMKa5yxHo0Cx7R+2t6dPZ6/fXN2++7q5v3ibrlpQ0xBMYqklChlPSN4DqDxYUpJAAaD+utvf7o6e9dwXN1fozHGl85Z71zcbsVwfzidHbxcrTbCulrdlpUNbRvbTliG4+npJ5//+A///MXX39QkPWkOB83AXBSyvbu9Xtyn+41xWHvnE1gocgdaoK+MMeCstRazbFUuyXtwvZ+df4whg5inXs9xtM9MACh5gsHKKsQJUqLQSRfasOl2DbfbGEIMXQwdx5ZS1NCJMDIhiiAgonfgrC28L0qcf/ZpVdrShZSCxLaqB9Za70zR76GzwARMWnhXzjhF750aoCSKqEoQGs2kl/HcFHVY3VG3Bg0inlW6ppFd07Ztt6OulfVStkFDJ5SIvWGx20ZaxnI6601GVV2VvlDnAY2g6fV689PXL05ezaaHvXrgs3BHJl/85kvbS6YgCO4FaBDAyJ6zRUxdiiwCmilcFo1VcBg2YfvQPl5eX1y8Pzt/9+bq8u52FXYtmyDKzDFms2aB3184mrxsm1VV1orgvan84Oj1681y2YSoKpoCpxS6HUtg4n5/MnlxdHLyh4uri9ubM+52YJzx9WQ0Wj/dIcJX33z/53/616PXr23XjGg5H7Xjfls6vr+9ub5Yr5Zd0rrsTSiDZu/UlaUviqKwxqJBtJjLWe5MVcGiQcjPALIXda5pAAiqiMYoCCrnYz80++M/zWuPAsKUkoRAHEPXhK6ldhdDR3EXQsvdLsUEKVJKQsyUtUnEAoED762qKBuPgEaLqvQFOI/OojMGKz+bHxlIoKkajKx3AKxEKa6d9cbVzNwfHTNyXN8Dtb5XU5KYQlg9NvfbFJOq7xgXi9BtqU0cBCJjBw7Hk+F01h/0q6pwzoLxxhVFXc/nLw+OXw2n00G/n5GNMXtD1o+1/rlamX2OwCyah6CoqiTZ/viZJmadcuDNQ1ovnu6u7q6vz86u33+4vF0uV7uuYQpiWDFSSinJsxTiXwbQcHKIWBS9Om2fmDhRVKTJ5PRvvv/p5sN/X31447wHlNB2vhqCk65ZeVsen7wyvrp6/6HXq0cvPum263Z53bbbLsaj01dffPPD93/66Wj+0qVtFa5P+83BgSCk9erp/mq1fIQWKuxPfFl0pEqS+wvnnC1zUXfPbgpoUQyomrxarQoC2YkgPykwFo0iMHBG3MZkMaf9jpHNMBw4Yy0REYrMRCFwShJCipFSF0Og2MTQpW5HMQp1wsSSNIsAsKgYUc2FXxVFNTusW0BUreqyPypLq44TAw2n82LQF9pC6iSq1VgM63LQZ+IUgjYhNsSJVVwnvHwK6224f+LHJqove4eTweSwquqyLH1VFlVVDybD4WR0MBtNjur+wPucsH9NOb+t8vtU/cx4VxFmJhHCTBCy1jprSlXluEuru+b+cr28Xlzcvn13dnn/sHxqVqFrGCNDBEmJKNGvlOX/7cKDw0+EwuHpl4uLnyk1rqy9cW2zQ2NOP3ntfHX2y89lVRjXO/nsiw9n/9FtNiKtcYP+cNSr+97ViU0Mm2ZzXxY+UBAmDjScTX/4u3/86m//OJ1N7eppKKv5pJ3PtCq0Dc39zcPdYkc4kOqFdY4Rhfbv3zpbFKUxFvcaWGIdWkVnLaIaawAQ9nZ5gnnV2hjZD8qeZfaeiXMGUVVFBRAdWEVQ86v2rBEQkSTZlqShFEPXphgkUoqRYmDKZulJmBIlokgp7ne3TXa9IQAWVhBmUVFQJoPonbWIAsKx7Zfl8dHEFhFTF0NARlPU2ewrRk4pPT3u3l+G1g0GL4+G00m/HpT1aDge98aT4WgyGIzqXu3K0rvCWvurRc8zv/1jt5HVm/MGWSRKJCyK1uWwca5EMMoUdsv24Xy3ePtwebm4urm6W12uVk/bponcJYxgk2hKKVLS/zN09gH0+V//cfP00J8e7paPXbPyvYFVjSHE2KjI7MXJ8enrtuOzn/+9HvSGs+OHxSULzWavHu7OQ9rVZX82O53Oj+4f7xBM23bN9kHSVo0d9Kb9enD65R+++u5PR4cnpm2GtDio29mA6zKi1WbTrDe0a4VxbKphshWT7jmWiGq8tc46NAa9RedMJssZRGcdICMq7i3xssDX79L48//bmxko5D5O8hxKNds6QZamg6y5r8/3sqho0sRCyIoCLCmlyClwSkIEogoqIimlGNuYiJkl+2GyKEvW7VYARjVgS1G0DMigChwJnAEBARSkRE0rG18P5qfjw9lgMB4Ohr3BoNeri6r0ReGsN79PMPvJmTEfD9vzTyLArETMRJBFoLxHXwJaZZJu1a1u2vvz7d3V4sPi6vzq4mH5sN1sSVuSIFZEg5hERCmKCGQDqf83gMbT+cnpX6mpFtdXRkNZVm3Ypd0ucXJlD5h6vWr+8pPddoNiyLoY29F4xk13ffNGqAWwzpeAMj959elnPzRNuLh487Q4Pzn9nGLYLm937Xo8nXz57Y9ffP3Di6OTkgMuF/14eXxkDo+Gvcq0bfv4sF6vY3IHtpqor0FRmBMLqyJYa60vvLX51aM16K11Foy1gKhorAGEPbhTUAuKqpwBtvnYwWV1UHA5AYGCRc5lTvINCIia9TNVEXPHywatBQOoIqLCzCwsTExCrKIsnIhFWBVUmJLmWYMwqgqg7EGusa4w1llrVJUElBWcNaZQBWN9UfWMN4VzzhXWWffsq7VHe7//NvapJoeOQUBgVmZlIlXA/IS8BYuKSKFL67v28TzcXa8fns6vF9eXi9uHzWO33ZB0oiyOAEmUKYXEyvwRIfzF9dtzVsX9h/c/LKN/Gm80P/QAAAAASUVORK5CYII=\n",
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"text/plain": [
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"PILImage mode=RGB size=192x144"
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]
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},
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"execution_count": 3,
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39 |
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"metadata": {},
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"output_type": "execute_result"
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41 |
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}
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42 |
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],
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43 |
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"source": [
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44 |
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"im = PILImage.create('fries.jpg')\n",
|
45 |
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"im.thumbnail((192,192))\n",
|
46 |
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"im"
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47 |
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]
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48 |
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},
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49 |
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{
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50 |
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"cell_type": "code",
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51 |
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"execution_count": 4,
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52 |
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"id": "27b2776b",
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53 |
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"metadata": {},
|
54 |
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"outputs": [],
|
55 |
+
"source": [
|
56 |
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"#|export\n",
|
57 |
+
"learn = load_learner('export.pkl')"
|
58 |
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]
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59 |
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},
|
60 |
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{
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61 |
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"cell_type": "code",
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62 |
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"execution_count": 7,
|
63 |
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"id": "e8b445cb",
|
64 |
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"metadata": {},
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65 |
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"outputs": [
|
66 |
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{
|
67 |
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"data": {
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68 |
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"text/html": [
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"\n",
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"<style>\n",
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" /* Turns off some styling */\n",
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72 |
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" progress {\n",
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73 |
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" /* gets rid of default border in Firefox and Opera. */\n",
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74 |
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" border: none;\n",
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75 |
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" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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76 |
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" background-size: auto;\n",
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77 |
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" }\n",
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78 |
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" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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79 |
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" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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80 |
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" }\n",
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81 |
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" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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82 |
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" background: #F44336;\n",
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83 |
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" }\n",
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84 |
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"</style>\n"
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85 |
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],
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86 |
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"text/plain": [
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"<IPython.core.display.HTML object>"
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88 |
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},
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"metadata": {},
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91 |
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"output_type": "display_data"
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92 |
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},
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93 |
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{
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"data": {
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"text/html": [],
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"text/plain": [
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"output_type": "display_data"
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},
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103 |
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{
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"data": {
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105 |
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"text/plain": [
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"('fries', TensorBase(0), TensorBase([0.9952, 0.0022, 0.0026]))"
|
107 |
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]
|
108 |
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},
|
109 |
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"execution_count": 7,
|
110 |
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"metadata": {},
|
111 |
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"output_type": "execute_result"
|
112 |
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}
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113 |
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],
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114 |
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"source": [
|
115 |
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"learn.predict(im)"
|
116 |
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]
|
117 |
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},
|
118 |
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{
|
119 |
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"cell_type": "code",
|
120 |
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"execution_count": 14,
|
121 |
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"id": "a563b07a",
|
122 |
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"metadata": {},
|
123 |
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"outputs": [
|
124 |
+
{
|
125 |
+
"data": {
|
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+
"text/plain": [
|
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+
"['fries', 'hamburger', 'milkshake']"
|
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+
]
|
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+
},
|
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+
"execution_count": 14,
|
131 |
+
"metadata": {},
|
132 |
+
"output_type": "execute_result"
|
133 |
+
}
|
134 |
+
],
|
135 |
+
"source": [
|
136 |
+
"learn.dls.vocab"
|
137 |
+
]
|
138 |
+
},
|
139 |
+
{
|
140 |
+
"cell_type": "code",
|
141 |
+
"execution_count": 19,
|
142 |
+
"id": "8eb5ccf7",
|
143 |
+
"metadata": {},
|
144 |
+
"outputs": [],
|
145 |
+
"source": [
|
146 |
+
"#|export\n",
|
147 |
+
"categories = ('Fries','Hamburger', 'Milk shake')\n",
|
148 |
+
"\n",
|
149 |
+
"def classify_image(img):\n",
|
150 |
+
" pred, idx, prob = learn.predict(img)\n",
|
151 |
+
" return dict(zip(categories, map(float,prob)))"
|
152 |
+
]
|
153 |
+
},
|
154 |
+
{
|
155 |
+
"cell_type": "code",
|
156 |
+
"execution_count": 20,
|
157 |
+
"id": "6bc03b93",
|
158 |
+
"metadata": {},
|
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+
"outputs": [
|
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+
{
|
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+
"data": {
|
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+
"text/html": [
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+
"\n",
|
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+
"<style>\n",
|
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+
" /* Turns off some styling */\n",
|
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+
" progress {\n",
|
167 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
168 |
+
" border: none;\n",
|
169 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
170 |
+
" background-size: auto;\n",
|
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+
" }\n",
|
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+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
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+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
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+
" }\n",
|
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+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
176 |
+
" background: #F44336;\n",
|
177 |
+
" }\n",
|
178 |
+
"</style>\n"
|
179 |
+
],
|
180 |
+
"text/plain": [
|
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+
"<IPython.core.display.HTML object>"
|
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+
]
|
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+
},
|
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+
"metadata": {},
|
185 |
+
"output_type": "display_data"
|
186 |
+
},
|
187 |
+
{
|
188 |
+
"data": {
|
189 |
+
"text/html": [],
|
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+
"text/plain": [
|
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+
"<IPython.core.display.HTML object>"
|
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+
]
|
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+
},
|
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+
"metadata": {},
|
195 |
+
"output_type": "display_data"
|
196 |
+
},
|
197 |
+
{
|
198 |
+
"data": {
|
199 |
+
"text/plain": [
|
200 |
+
"{'Fries': 0.9952397346496582,\n",
|
201 |
+
" 'Hamburger': 0.0021943373139947653,\n",
|
202 |
+
" 'Milk shake': 0.0025659294333308935}"
|
203 |
+
]
|
204 |
+
},
|
205 |
+
"execution_count": 20,
|
206 |
+
"metadata": {},
|
207 |
+
"output_type": "execute_result"
|
208 |
+
}
|
209 |
+
],
|
210 |
+
"source": [
|
211 |
+
"classify_image(im)"
|
212 |
+
]
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"cell_type": "code",
|
216 |
+
"execution_count": 22,
|
217 |
+
"id": "111bbf68",
|
218 |
+
"metadata": {},
|
219 |
+
"outputs": [
|
220 |
+
{
|
221 |
+
"name": "stdout",
|
222 |
+
"output_type": "stream",
|
223 |
+
"text": [
|
224 |
+
"Running on local URL: http://127.0.0.1:7860\n",
|
225 |
+
"\n",
|
226 |
+
"To create a public link, set `share=True` in `launch()`.\n"
|
227 |
+
]
|
228 |
+
},
|
229 |
+
{
|
230 |
+
"data": {
|
231 |
+
"text/plain": []
|
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+
},
|
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+
"execution_count": 22,
|
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+
"metadata": {},
|
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+
"output_type": "execute_result"
|
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+
},
|
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+
{
|
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+
"data": {
|
239 |
+
"text/html": [
|
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+
"\n",
|
241 |
+
"<style>\n",
|
242 |
+
" /* Turns off some styling */\n",
|
243 |
+
" progress {\n",
|
244 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
245 |
+
" border: none;\n",
|
246 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
247 |
+
" background-size: auto;\n",
|
248 |
+
" }\n",
|
249 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
250 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
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+
" }\n",
|
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+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
253 |
+
" background: #F44336;\n",
|
254 |
+
" }\n",
|
255 |
+
"</style>\n"
|
256 |
+
],
|
257 |
+
"text/plain": [
|
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+
"<IPython.core.display.HTML object>"
|
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+
]
|
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+
},
|
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+
"metadata": {},
|
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+
"output_type": "display_data"
|
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+
},
|
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+
{
|
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+
"data": {
|
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+
"text/html": [],
|
267 |
+
"text/plain": [
|
268 |
+
"<IPython.core.display.HTML object>"
|
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+
]
|
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+
},
|
271 |
+
"metadata": {},
|
272 |
+
"output_type": "display_data"
|
273 |
+
},
|
274 |
+
{
|
275 |
+
"data": {
|
276 |
+
"text/html": [
|
277 |
+
"\n",
|
278 |
+
"<style>\n",
|
279 |
+
" /* Turns off some styling */\n",
|
280 |
+
" progress {\n",
|
281 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
282 |
+
" border: none;\n",
|
283 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
284 |
+
" background-size: auto;\n",
|
285 |
+
" }\n",
|
286 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
287 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
288 |
+
" }\n",
|
289 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
290 |
+
" background: #F44336;\n",
|
291 |
+
" }\n",
|
292 |
+
"</style>\n"
|
293 |
+
],
|
294 |
+
"text/plain": [
|
295 |
+
"<IPython.core.display.HTML object>"
|
296 |
+
]
|
297 |
+
},
|
298 |
+
"metadata": {},
|
299 |
+
"output_type": "display_data"
|
300 |
+
},
|
301 |
+
{
|
302 |
+
"data": {
|
303 |
+
"text/html": [],
|
304 |
+
"text/plain": [
|
305 |
+
"<IPython.core.display.HTML object>"
|
306 |
+
]
|
307 |
+
},
|
308 |
+
"metadata": {},
|
309 |
+
"output_type": "display_data"
|
310 |
+
}
|
311 |
+
],
|
312 |
+
"source": [
|
313 |
+
"#|export\n",
|
314 |
+
"image = gr.inputs.Image(shape=(192,192))\n",
|
315 |
+
"label = gr.outputs.Label()\n",
|
316 |
+
"examples = ['hamburger.jpg','fries.jpg']\n",
|
317 |
+
"\n",
|
318 |
+
"intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
|
319 |
+
"intf.launch(inline=False)"
|
320 |
+
]
|
321 |
+
},
|
322 |
+
{
|
323 |
+
"cell_type": "code",
|
324 |
+
"execution_count": 4,
|
325 |
+
"id": "8ca16422",
|
326 |
+
"metadata": {},
|
327 |
+
"outputs": [
|
328 |
+
{
|
329 |
+
"name": "stderr",
|
330 |
+
"output_type": "stream",
|
331 |
+
"text": [
|
332 |
+
"/home/edwin/miniconda3/lib/python3.10/site-packages/nbdev/export.py:54: UserWarning: Notebook 'app.ipynb' uses `#|export` without `#|default_exp` cell.\n",
|
333 |
+
"Note nbdev2 no longer supports nbdev1 syntax. Run `nbdev_migrate` to upgrade.\n",
|
334 |
+
"See https://nbdev.fast.ai/getting_started.html for more information.\n",
|
335 |
+
" warn(f\"Notebook '{nbname}' uses `#|export` without `#|default_exp` cell.\\n\"\n"
|
336 |
+
]
|
337 |
+
}
|
338 |
+
],
|
339 |
+
"source": [
|
340 |
+
"import nbdev\n",
|
341 |
+
"nbdev.export.nb_export('app.ipynb')"
|
342 |
+
]
|
343 |
+
},
|
344 |
+
{
|
345 |
+
"cell_type": "code",
|
346 |
+
"execution_count": null,
|
347 |
+
"id": "2d87b54f",
|
348 |
+
"metadata": {},
|
349 |
+
"outputs": [],
|
350 |
+
"source": []
|
351 |
+
}
|
352 |
+
],
|
353 |
+
"metadata": {
|
354 |
+
"kernelspec": {
|
355 |
+
"display_name": "Python 3 (ipykernel)",
|
356 |
+
"language": "python",
|
357 |
+
"name": "python3"
|
358 |
+
},
|
359 |
+
"language_info": {
|
360 |
+
"codemirror_mode": {
|
361 |
+
"name": "ipython",
|
362 |
+
"version": 3
|
363 |
+
},
|
364 |
+
"file_extension": ".py",
|
365 |
+
"mimetype": "text/x-python",
|
366 |
+
"name": "python",
|
367 |
+
"nbconvert_exporter": "python",
|
368 |
+
"pygments_lexer": "ipython3",
|
369 |
+
"version": "3.10.8"
|
370 |
+
}
|
371 |
+
},
|
372 |
+
"nbformat": 4,
|
373 |
+
"nbformat_minor": 5
|
374 |
+
}
|
app.ipynb
ADDED
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|
1 |
+
{
|
2 |
+
"cells": [
|
3 |
+
{
|
4 |
+
"cell_type": "code",
|
5 |
+
"execution_count": 7,
|
6 |
+
"id": "00cb42b5",
|
7 |
+
"metadata": {},
|
8 |
+
"outputs": [],
|
9 |
+
"source": [
|
10 |
+
"#|default_exp app"
|
11 |
+
]
|
12 |
+
},
|
13 |
+
{
|
14 |
+
"cell_type": "code",
|
15 |
+
"execution_count": 8,
|
16 |
+
"id": "ad76e8e1",
|
17 |
+
"metadata": {},
|
18 |
+
"outputs": [],
|
19 |
+
"source": [
|
20 |
+
"#|export\n",
|
21 |
+
"from fastai.vision.all import *\n",
|
22 |
+
"import gradio as gr"
|
23 |
+
]
|
24 |
+
},
|
25 |
+
{
|
26 |
+
"cell_type": "code",
|
27 |
+
"execution_count": 9,
|
28 |
+
"id": "b395a732",
|
29 |
+
"metadata": {},
|
30 |
+
"outputs": [
|
31 |
+
{
|
32 |
+
"data": {
|
33 |
+
"image/png": 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\n",
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"text/plain": [
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"PILImage mode=RGB size=192x144"
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]
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},
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38 |
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"execution_count": 9,
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39 |
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"metadata": {},
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40 |
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"output_type": "execute_result"
|
41 |
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}
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42 |
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],
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43 |
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"source": [
|
44 |
+
"im = PILImage.create('fries.jpg')\n",
|
45 |
+
"im.thumbnail((192,192))\n",
|
46 |
+
"im"
|
47 |
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]
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48 |
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},
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{
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"execution_count": 10,
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"id": "27b2776b",
|
53 |
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"metadata": {},
|
54 |
+
"outputs": [],
|
55 |
+
"source": [
|
56 |
+
"#|export\n",
|
57 |
+
"learn = load_learner('export.pkl')"
|
58 |
+
]
|
59 |
+
},
|
60 |
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{
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61 |
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"cell_type": "code",
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62 |
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"execution_count": 11,
|
63 |
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"id": "e8b445cb",
|
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"metadata": {},
|
65 |
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"outputs": [
|
66 |
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{
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67 |
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"data": {
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"text/html": [],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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72 |
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},
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73 |
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"metadata": {},
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74 |
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"output_type": "display_data"
|
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},
|
76 |
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{
|
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"data": {
|
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"text/plain": [
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"('fries', TensorBase(0), TensorBase([0.9952, 0.0022, 0.0026]))"
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]
|
81 |
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},
|
82 |
+
"execution_count": 11,
|
83 |
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"metadata": {},
|
84 |
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"output_type": "execute_result"
|
85 |
+
}
|
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],
|
87 |
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"source": [
|
88 |
+
"learn.predict(im)"
|
89 |
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]
|
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},
|
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{
|
92 |
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"cell_type": "code",
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"execution_count": 12,
|
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"id": "a563b07a",
|
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"metadata": {},
|
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"outputs": [
|
97 |
+
{
|
98 |
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"data": {
|
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+
"text/plain": [
|
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"['fries', 'hamburger', 'milkshake']"
|
101 |
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]
|
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},
|
103 |
+
"execution_count": 12,
|
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|
105 |
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"output_type": "execute_result"
|
106 |
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}
|
107 |
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],
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"source": [
|
109 |
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"learn.dls.vocab"
|
110 |
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]
|
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},
|
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{
|
113 |
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"cell_type": "code",
|
114 |
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"execution_count": 13,
|
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"id": "8eb5ccf7",
|
116 |
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"metadata": {},
|
117 |
+
"outputs": [],
|
118 |
+
"source": [
|
119 |
+
"#|export\n",
|
120 |
+
"categories = ('Fries','Hamburger', 'Milk shake')\n",
|
121 |
+
"\n",
|
122 |
+
"def classify_image(img):\n",
|
123 |
+
" pred, idx, prob = learn.predict(img)\n",
|
124 |
+
" return dict(zip(categories, map(float,prob)))"
|
125 |
+
]
|
126 |
+
},
|
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{
|
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"cell_type": "code",
|
129 |
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"execution_count": 14,
|
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+
"id": "6bc03b93",
|
131 |
+
"metadata": {},
|
132 |
+
"outputs": [
|
133 |
+
{
|
134 |
+
"data": {
|
135 |
+
"text/html": [],
|
136 |
+
"text/plain": [
|
137 |
+
"<IPython.core.display.HTML object>"
|
138 |
+
]
|
139 |
+
},
|
140 |
+
"metadata": {},
|
141 |
+
"output_type": "display_data"
|
142 |
+
},
|
143 |
+
{
|
144 |
+
"data": {
|
145 |
+
"text/plain": [
|
146 |
+
"{'Fries': 0.9952397346496582,\n",
|
147 |
+
" 'Hamburger': 0.0021943373139947653,\n",
|
148 |
+
" 'Milk shake': 0.0025659294333308935}"
|
149 |
+
]
|
150 |
+
},
|
151 |
+
"execution_count": 14,
|
152 |
+
"metadata": {},
|
153 |
+
"output_type": "execute_result"
|
154 |
+
}
|
155 |
+
],
|
156 |
+
"source": [
|
157 |
+
"classify_image(im)"
|
158 |
+
]
|
159 |
+
},
|
160 |
+
{
|
161 |
+
"cell_type": "code",
|
162 |
+
"execution_count": 15,
|
163 |
+
"id": "111bbf68",
|
164 |
+
"metadata": {},
|
165 |
+
"outputs": [
|
166 |
+
{
|
167 |
+
"name": "stderr",
|
168 |
+
"output_type": "stream",
|
169 |
+
"text": [
|
170 |
+
"/home/edwin/miniconda3/lib/python3.10/site-packages/gradio/inputs.py:257: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
|
171 |
+
" warnings.warn(\n",
|
172 |
+
"/home/edwin/miniconda3/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
|
173 |
+
" warnings.warn(value)\n",
|
174 |
+
"/home/edwin/miniconda3/lib/python3.10/site-packages/gradio/outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
|
175 |
+
" warnings.warn(\n",
|
176 |
+
"/home/edwin/miniconda3/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
|
177 |
+
" warnings.warn(value)\n"
|
178 |
+
]
|
179 |
+
},
|
180 |
+
{
|
181 |
+
"name": "stdout",
|
182 |
+
"output_type": "stream",
|
183 |
+
"text": [
|
184 |
+
"Running on local URL: http://127.0.0.1:7860\n",
|
185 |
+
"\n",
|
186 |
+
"To create a public link, set `share=True` in `launch()`.\n"
|
187 |
+
]
|
188 |
+
},
|
189 |
+
{
|
190 |
+
"data": {
|
191 |
+
"text/plain": []
|
192 |
+
},
|
193 |
+
"execution_count": 15,
|
194 |
+
"metadata": {},
|
195 |
+
"output_type": "execute_result"
|
196 |
+
}
|
197 |
+
],
|
198 |
+
"source": [
|
199 |
+
"#|export\n",
|
200 |
+
"image = gr.inputs.Image(shape=(192,192))\n",
|
201 |
+
"label = gr.outputs.Label()\n",
|
202 |
+
"examples = ['hamburger.jpg','fries.jpg']\n",
|
203 |
+
"\n",
|
204 |
+
"intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
|
205 |
+
"intf.launch(inline=False)"
|
206 |
+
]
|
207 |
+
},
|
208 |
+
{
|
209 |
+
"cell_type": "code",
|
210 |
+
"execution_count": 18,
|
211 |
+
"id": "8ca16422",
|
212 |
+
"metadata": {},
|
213 |
+
"outputs": [],
|
214 |
+
"source": [
|
215 |
+
"import nbdev\n",
|
216 |
+
"nbdev.export.nb_export('app.ipynb','')"
|
217 |
+
]
|
218 |
+
},
|
219 |
+
{
|
220 |
+
"cell_type": "code",
|
221 |
+
"execution_count": null,
|
222 |
+
"id": "d6f33bd7",
|
223 |
+
"metadata": {},
|
224 |
+
"outputs": [],
|
225 |
+
"source": []
|
226 |
+
}
|
227 |
+
],
|
228 |
+
"metadata": {
|
229 |
+
"kernelspec": {
|
230 |
+
"display_name": "Python 3 (ipykernel)",
|
231 |
+
"language": "python",
|
232 |
+
"name": "python3"
|
233 |
+
},
|
234 |
+
"language_info": {
|
235 |
+
"codemirror_mode": {
|
236 |
+
"name": "ipython",
|
237 |
+
"version": 3
|
238 |
+
},
|
239 |
+
"file_extension": ".py",
|
240 |
+
"mimetype": "text/x-python",
|
241 |
+
"name": "python",
|
242 |
+
"nbconvert_exporter": "python",
|
243 |
+
"pygments_lexer": "ipython3",
|
244 |
+
"version": "3.10.8"
|
245 |
+
}
|
246 |
+
},
|
247 |
+
"nbformat": 4,
|
248 |
+
"nbformat_minor": 5
|
249 |
+
}
|
app.py
CHANGED
@@ -1,7 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
import gradio as gr
|
2 |
|
3 |
-
|
4 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
5 |
|
6 |
-
|
7 |
-
|
|
|
1 |
+
# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
|
2 |
+
|
3 |
+
# %% auto 0
|
4 |
+
__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
|
5 |
+
|
6 |
+
# %% app.ipynb 1
|
7 |
+
from fastai.vision.all import *
|
8 |
import gradio as gr
|
9 |
|
10 |
+
# %% app.ipynb 3
|
11 |
+
learn = load_learner('export.pkl')
|
12 |
+
|
13 |
+
# %% app.ipynb 6
|
14 |
+
categories = ('Fries','Hamburger', 'Milk shake')
|
15 |
+
|
16 |
+
def classify_image(img):
|
17 |
+
pred, idx, prob = learn.predict(img)
|
18 |
+
return dict(zip(categories, map(float,prob)))
|
19 |
+
|
20 |
+
# %% app.ipynb 8
|
21 |
+
image = gr.inputs.Image(shape=(192,192))
|
22 |
+
label = gr.outputs.Label()
|
23 |
+
examples = ['hamburger.jpg','fries.jpg']
|
24 |
|
25 |
+
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
|
26 |
+
intf.launch(inline=False)
|
export.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1f522b178c397e32209ffddbee172bf6efc35bfc79c697f3fd9041352331fadf
|
3 |
+
size 46963489
|
export.pkl:Zone.Identifier
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
[ZoneTransfer]
|
2 |
+
ZoneId=3
|
3 |
+
HostUrl=https://www.kaggle.com/
|
fries.jpg
ADDED
fries.jpg:Zone.Identifier
ADDED
File without changes
|
hamburger.jpg
ADDED
hamburgers.jpg:Zone.Identifier
ADDED
File without changes
|