{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from utils import *\n", "warnings.filterwarnings('ignore')\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "fd_collection = getCollection(\"team_5_mwdb_phase_2\", \"fd_collection\")\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Applying kmeans on the resnet_fd space to get 10 latent semantics (showing only top 10 image-weight pairs for each latent semantic)...\n", "Initialized centroids\n", "Iteration 56 - Converged\n", "Note: for K-Means we display distances, in ascending order\n", "Latent semantic no. 0\n", "Image_ID\t440\t-\tDistance\t10.640763416796371\n", "Image_ID\t700\t-\tDistance\t11.159224514655602\n", "Image_ID\t654\t-\tDistance\t11.395135539610168\n", "Image_ID\t486\t-\tDistance\t11.550858382118225\n", "Image_ID\t462\t-\tDistance\t11.61044182679253\n", "Image_ID\t652\t-\tDistance\t11.818427599783789\n", "Image_ID\t676\t-\tDistance\t11.925768133017636\n", "Image_ID\t584\t-\tDistance\t11.93319861884516\n", "Image_ID\t692\t-\tDistance\t11.979693069110743\n", "Image_ID\t6\t-\tDistance\t12.137562566975056\n", "Latent semantic no. 1\n", "Image_ID\t3602\t-\tDistance\t13.563162479981145\n", "Image_ID\t2414\t-\tDistance\t14.192224338224467\n", "Image_ID\t3560\t-\tDistance\t14.205420291205272\n", "Image_ID\t3600\t-\tDistance\t14.389262503144405\n", "Image_ID\t2228\t-\tDistance\t14.4828087393621\n", "Image_ID\t3636\t-\tDistance\t14.497503774497243\n", "Image_ID\t3614\t-\tDistance\t14.591251785931954\n", "Image_ID\t2090\t-\tDistance\t14.620114150279178\n", "Image_ID\t2328\t-\tDistance\t14.69159730598465\n", "Image_ID\t2448\t-\tDistance\t14.774950728597261\n", "Latent semantic no. 2\n", "Image_ID\t4838\t-\tDistance\t12.261260721990451\n", "Image_ID\t7302\t-\tDistance\t12.880136852617754\n", "Image_ID\t7978\t-\tDistance\t13.077993711608961\n", "Image_ID\t8600\t-\tDistance\t13.305290839761437\n", "Image_ID\t7292\t-\tDistance\t13.334716062864114\n", "Image_ID\t7720\t-\tDistance\t13.37155798887382\n", "Image_ID\t7958\t-\tDistance\t13.430323190148206\n", "Image_ID\t4600\t-\tDistance\t13.45781162474979\n", "Image_ID\t4270\t-\tDistance\t13.491427681265899\n", "Image_ID\t4828\t-\tDistance\t13.539053205319615\n", "Latent semantic no. 3\n", "Image_ID\t1758\t-\tDistance\t5.030040634300718\n", "Image_ID\t1562\t-\tDistance\t5.3329050871004755\n", "Image_ID\t1586\t-\tDistance\t5.583507266395663\n", "Image_ID\t1362\t-\tDistance\t6.017196001905923\n", "Image_ID\t1626\t-\tDistance\t6.045998053427588\n", "Image_ID\t1208\t-\tDistance\t6.051540458349612\n", "Image_ID\t1374\t-\tDistance\t6.178242313742901\n", "Image_ID\t1112\t-\tDistance\t6.249956790411116\n", "Image_ID\t1710\t-\tDistance\t6.310688634541122\n", "Image_ID\t1490\t-\tDistance\t6.376123320547912\n", "Latent semantic no. 4\n", "Image_ID\t8282\t-\tDistance\t10.506907762007522\n", "Image_ID\t8348\t-\tDistance\t10.647963471647738\n", "Image_ID\t8380\t-\tDistance\t10.715093501411761\n", "Image_ID\t8228\t-\tDistance\t10.879515968086416\n", "Image_ID\t8240\t-\tDistance\t10.896279105885796\n", "Image_ID\t8340\t-\tDistance\t10.952943877775777\n", "Image_ID\t8174\t-\tDistance\t11.012538653878869\n", "Image_ID\t8368\t-\tDistance\t11.01584931675634\n", "Image_ID\t8176\t-\tDistance\t11.074708303511043\n", "Image_ID\t8386\t-\tDistance\t11.090905861600216\n", "Latent semantic no. 5\n", "Image_ID\t7400\t-\tDistance\t9.07340282234228\n", "Image_ID\t7332\t-\tDistance\t9.27997555888011\n", "Image_ID\t6626\t-\tDistance\t9.490015364667478\n", "Image_ID\t7990\t-\tDistance\t9.619812101313876\n", "Image_ID\t7392\t-\tDistance\t9.640980435311661\n", "Image_ID\t7404\t-\tDistance\t9.6738734363643\n", "Image_ID\t7980\t-\tDistance\t9.710518881249477\n", "Image_ID\t7410\t-\tDistance\t9.778693486707565\n", "Image_ID\t7950\t-\tDistance\t9.785247539262517\n", "Image_ID\t7346\t-\tDistance\t9.806294880503\n", "Latent semantic no. 6\n", "Image_ID\t8542\t-\tDistance\t11.232961895055158\n", "Image_ID\t6014\t-\tDistance\t11.304802835945505\n", "Image_ID\t8566\t-\tDistance\t11.443919577851908\n", "Image_ID\t7200\t-\tDistance\t11.484387898391537\n", "Image_ID\t6626\t-\tDistance\t11.48886846539337\n", "Image_ID\t6620\t-\tDistance\t11.578369802598303\n", "Image_ID\t6636\t-\tDistance\t11.662783932711658\n", "Image_ID\t8056\t-\tDistance\t11.74943673802499\n", "Image_ID\t7700\t-\tDistance\t11.769992973787971\n", "Image_ID\t6622\t-\tDistance\t11.780162710805048\n", "Latent semantic no. 7\n", "Image_ID\t2646\t-\tDistance\t7.514711553618432\n", "Image_ID\t2260\t-\tDistance\t7.633993639248322\n", "Image_ID\t2460\t-\tDistance\t7.685809907469392\n", "Image_ID\t2660\t-\tDistance\t7.701780256364207\n", "Image_ID\t2418\t-\tDistance\t7.716363257255012\n", "Image_ID\t2240\t-\tDistance\t7.74734521250179\n", "Image_ID\t2430\t-\tDistance\t7.784825198465868\n", "Image_ID\t2264\t-\tDistance\t7.828411523843045\n", "Image_ID\t2242\t-\tDistance\t7.878806112518542\n", "Image_ID\t2196\t-\tDistance\t7.918897962650677\n", "Latent semantic no. 8\n", "Image_ID\t562\t-\tDistance\t8.552732623243445\n", "Image_ID\t796\t-\tDistance\t9.316343355329956\n", "Image_ID\t612\t-\tDistance\t9.451362646413244\n", "Image_ID\t476\t-\tDistance\t9.458717454426738\n", "Image_ID\t798\t-\tDistance\t9.853412912988212\n", "Image_ID\t460\t-\tDistance\t9.859458462429464\n", "Image_ID\t190\t-\tDistance\t10.065071186269668\n", "Image_ID\t462\t-\tDistance\t10.065893471754435\n", "Image_ID\t456\t-\tDistance\t10.099056881970604\n", "Image_ID\t828\t-\tDistance\t10.29276769283984\n", "Latent semantic no. 9\n", "Image_ID\t3124\t-\tDistance\t12.500361886870435\n", "Image_ID\t8064\t-\tDistance\t12.967833703429173\n", "Image_ID\t4270\t-\tDistance\t13.225230811650766\n", "Image_ID\t7720\t-\tDistance\t13.340802785257075\n", "Image_ID\t8050\t-\tDistance\t13.601572206798334\n", "Image_ID\t8074\t-\tDistance\t13.693355761074226\n", "Image_ID\t8042\t-\tDistance\t13.72102497292387\n", "Image_ID\t6450\t-\tDistance\t13.750626256669166\n", "Image_ID\t8018\t-\tDistance\t13.768703250806348\n", "Image_ID\t6628\t-\tDistance\t13.784107713433421\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": "3.10.5" } }, "nbformat": 4, "nbformat_minor": 2 }