{ "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 }