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CSE515_MWDB_Project/Phase 2/task_3.ipynb
pranavbrkr ebf1f1629b update
2023-10-14 23:39:57 -07:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from utils import *\n",
"warnings.filterwarnings('ignore')\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"fd_collection = getCollection(\"team_5_mwdb_phase_2\", \"fd_collection\")\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Applying lda on the cm_fd space to get 10 latent semantics (showing only top 10 image-weight pairs for each latent semantic)...\n",
"iteration: 1 of max_iter: 10\n",
"iteration: 2 of max_iter: 10\n",
"iteration: 3 of max_iter: 10\n",
"iteration: 4 of max_iter: 10\n",
"iteration: 5 of max_iter: 10\n",
"iteration: 6 of max_iter: 10\n",
"iteration: 7 of max_iter: 10\n",
"iteration: 8 of max_iter: 10\n",
"iteration: 9 of max_iter: 10\n",
"iteration: 10 of max_iter: 10\n",
"Latent semantic no. 0\n",
"Image_ID\t1710\t-\tWeight\t0.617458014268485\n",
"Image_ID\t1844\t-\tWeight\t0.6075822274686563\n",
"Image_ID\t1750\t-\tWeight\t0.6070573195345486\n",
"Image_ID\t1400\t-\tWeight\t0.6056680791985845\n",
"Image_ID\t1284\t-\tWeight\t0.6034453335599401\n",
"Image_ID\t1722\t-\tWeight\t0.6007621954380373\n",
"Image_ID\t1824\t-\tWeight\t0.5984109879793347\n",
"Image_ID\t1446\t-\tWeight\t0.5961120049400928\n",
"Image_ID\t1746\t-\tWeight\t0.5956438913483608\n",
"Image_ID\t1202\t-\tWeight\t0.5946144775162294\n",
"Latent semantic no. 1\n",
"Image_ID\t902\t-\tWeight\t0.4728143111474456\n",
"Image_ID\t1002\t-\tWeight\t0.46041900831405763\n",
"Image_ID\t542\t-\tWeight\t0.4321682728103117\n",
"Image_ID\t6660\t-\tWeight\t0.43006737908416837\n",
"Image_ID\t7140\t-\tWeight\t0.41016099848189896\n",
"Image_ID\t7422\t-\tWeight\t0.4097197999004479\n",
"Image_ID\t1048\t-\tWeight\t0.40947159895773955\n",
"Image_ID\t5862\t-\tWeight\t0.40422818133221733\n",
"Image_ID\t920\t-\tWeight\t0.39918666593292523\n",
"Image_ID\t532\t-\tWeight\t0.39629998547607764\n",
"Latent semantic no. 2\n",
"Image_ID\t6528\t-\tWeight\t0.3855361898894576\n",
"Image_ID\t7514\t-\tWeight\t0.3582051575013368\n",
"Image_ID\t8258\t-\tWeight\t0.34639902472175704\n",
"Image_ID\t3164\t-\tWeight\t0.34339034052442163\n",
"Image_ID\t7546\t-\tWeight\t0.338559827261986\n",
"Image_ID\t6328\t-\tWeight\t0.3368802586491903\n",
"Image_ID\t5932\t-\tWeight\t0.33651755972532976\n",
"Image_ID\t3834\t-\tWeight\t0.3356941112662742\n",
"Image_ID\t3894\t-\tWeight\t0.326576952326855\n",
"Image_ID\t5976\t-\tWeight\t0.3265670285062378\n",
"Latent semantic no. 3\n",
"Image_ID\t1744\t-\tWeight\t0.7351741873912249\n",
"Image_ID\t1134\t-\tWeight\t0.7128486032496076\n",
"Image_ID\t7466\t-\tWeight\t0.698769590115999\n",
"Image_ID\t2068\t-\tWeight\t0.6926683477111293\n",
"Image_ID\t1136\t-\tWeight\t0.687502465317813\n",
"Image_ID\t1752\t-\tWeight\t0.6873052436914959\n",
"Image_ID\t1130\t-\tWeight\t0.6726394748460636\n",
"Image_ID\t6710\t-\tWeight\t0.6535155833423436\n",
"Image_ID\t1450\t-\tWeight\t0.6414894098300652\n",
"Image_ID\t2090\t-\tWeight\t0.6268387632803436\n",
"Latent semantic no. 4\n",
"Image_ID\t2128\t-\tWeight\t0.5077209986058677\n",
"Image_ID\t2106\t-\tWeight\t0.500806169746303\n",
"Image_ID\t2008\t-\tWeight\t0.43841799612309496\n",
"Image_ID\t1222\t-\tWeight\t0.41374797151946374\n",
"Image_ID\t1968\t-\tWeight\t0.41245647494147325\n",
"Image_ID\t5534\t-\tWeight\t0.40585942227940236\n",
"Image_ID\t1938\t-\tWeight\t0.40488816917923176\n",
"Image_ID\t5902\t-\tWeight\t0.39867524511561125\n",
"Image_ID\t2452\t-\tWeight\t0.39854396145813886\n",
"Image_ID\t1950\t-\tWeight\t0.39682871606211834\n",
"Latent semantic no. 5\n",
"Image_ID\t3128\t-\tWeight\t0.9323262707996046\n",
"Image_ID\t3134\t-\tWeight\t0.9288511931662002\n",
"Image_ID\t3132\t-\tWeight\t0.9257512744018676\n",
"Image_ID\t3130\t-\tWeight\t0.9206321130935269\n",
"Image_ID\t6646\t-\tWeight\t0.9034536187267997\n",
"Image_ID\t7508\t-\tWeight\t0.8994767166493532\n",
"Image_ID\t6640\t-\tWeight\t0.8958687751792616\n",
"Image_ID\t8624\t-\tWeight\t0.8949244821453077\n",
"Image_ID\t6604\t-\tWeight\t0.8870653537915141\n",
"Image_ID\t6534\t-\tWeight\t0.8745989651487901\n",
"Latent semantic no. 6\n",
"Image_ID\t7024\t-\tWeight\t0.49312095749280327\n",
"Image_ID\t7036\t-\tWeight\t0.4782214728796395\n",
"Image_ID\t8362\t-\tWeight\t0.4662358245148104\n",
"Image_ID\t7008\t-\tWeight\t0.46357467039194805\n",
"Image_ID\t7042\t-\tWeight\t0.46321550546683676\n",
"Image_ID\t7054\t-\tWeight\t0.4582577226968157\n",
"Image_ID\t4594\t-\tWeight\t0.45499885749453567\n",
"Image_ID\t8108\t-\tWeight\t0.4548808255388789\n",
"Image_ID\t4804\t-\tWeight\t0.4537641746485284\n",
"Image_ID\t7018\t-\tWeight\t0.4500954855531814\n",
"Latent semantic no. 7\n",
"Image_ID\t3072\t-\tWeight\t0.5545755342145449\n",
"Image_ID\t7754\t-\tWeight\t0.4966261995365101\n",
"Image_ID\t3314\t-\tWeight\t0.48233428979251847\n",
"Image_ID\t7940\t-\tWeight\t0.4800400108197779\n",
"Image_ID\t8512\t-\tWeight\t0.47551348229445217\n",
"Image_ID\t6198\t-\tWeight\t0.47117452506086344\n",
"Image_ID\t322\t-\tWeight\t0.4663234778213565\n",
"Image_ID\t2010\t-\tWeight\t0.46573364328793904\n",
"Image_ID\t3076\t-\tWeight\t0.4431223382983598\n",
"Image_ID\t972\t-\tWeight\t0.4405628751432792\n",
"Latent semantic no. 8\n",
"Image_ID\t5600\t-\tWeight\t0.39739725479916665\n",
"Image_ID\t670\t-\tWeight\t0.3875951018959884\n",
"Image_ID\t350\t-\tWeight\t0.3720086985545715\n",
"Image_ID\t6460\t-\tWeight\t0.36938723858403194\n",
"Image_ID\t5624\t-\tWeight\t0.364040853186806\n",
"Image_ID\t356\t-\tWeight\t0.3583579835975199\n",
"Image_ID\t7432\t-\tWeight\t0.3553306592859769\n",
"Image_ID\t7422\t-\tWeight\t0.354707905541325\n",
"Image_ID\t5084\t-\tWeight\t0.35365911426394\n",
"Image_ID\t1140\t-\tWeight\t0.3479134590934088\n",
"Latent semantic no. 9\n",
"Image_ID\t7654\t-\tWeight\t0.5679206359746548\n",
"Image_ID\t5354\t-\tWeight\t0.5064858428524615\n",
"Image_ID\t2804\t-\tWeight\t0.49614015154469926\n",
"Image_ID\t2764\t-\tWeight\t0.4860908228174713\n",
"Image_ID\t5134\t-\tWeight\t0.47600763822211256\n",
"Image_ID\t5136\t-\tWeight\t0.4611545624641291\n",
"Image_ID\t3704\t-\tWeight\t0.43021905028205043\n",
"Image_ID\t7484\t-\tWeight\t0.42015058396503724\n",
"Image_ID\t6830\t-\tWeight\t0.3890006613191919\n",
"Image_ID\t5410\t-\tWeight\t0.3846047200608215\n"
]
}
],
"source": [
"selected_feature_model = valid_feature_models[\n",
" str(input(\"Enter feature model - one of \" + str(list(valid_feature_models.keys()))))\n",
"]\n",
"\n",
"k = int(input(\"Enter value of k: \"))\n",
"if k < 1:\n",
" raise ValueError(\"k should be a positive integer\")\n",
"\n",
"selected_dim_reduction_method = str(\n",
" input(\n",
" \"Enter dimensionality reduction method - one of \"\n",
" + str(list(valid_dim_reduction_methods.keys()))\n",
" )\n",
")\n",
"\n",
"extract_latent_semantics_from_feature_model(\n",
" fd_collection,\n",
" k,\n",
" selected_feature_model,\n",
" selected_dim_reduction_method,\n",
" top_images=10,\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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