The images for both training and test can be downloaded from the following link.

* [Kaggle Fall 2020](https://www.kaggle.com/jeffheaton/glasses-or-no-glasses)

The files are named face-##.png, where ## is a number that corresponds to an **id** in either the training or test set.  Each of these faces was generated by a GAN.  The vector that generates these faces is contained in 512 values labeled v1-v512. For example, the following vector:

[-0.55926	-0.20733	-1.29214	-0.22838	-0.03262	1.84912	-0.86665	0.33701	-0.40007	0.13552
-0.0876	0.81677	1.07995	0.43476	0.48689	0.65321	-0.38508	0.45877	0.08921	-0.39396	-0.97739	
0.04854	0.85768	-0.56874	-0.26351	0.53307	0.41915	-0.12844	-0.62554	-0.00997	1.02039	-0.59179	
-0.01051	0.48258	-0.79316	-0.29616	0.83112	0.31366	-0.3678	-0.67272	0.41977	-0.75309	-0.78372	
0.5175	-0.57599	-0.36012	-0.10666	-0.28171	-0.19364	-0.15171	-0.13408	1.03574	0.95128	0.01968	-0.03844	
0.748	-0.651	-2.10949	-0.06374	0.28596	-0.79341	0.45714	0.03466	0.21496	0.43507	0.61734	-0.43913	
0.24809	0.58706	-0.59568	0.45103	0.44342	-0.90193	-0.38185	-0.90107	-0.17118	0.74643	-0.07329	-0.1376	-0.41076	1.38113	-1.69444	-1.01962	0.69776	0.47324	-0.12014	-1.46088	0.08403	-0.10276	-1.10913	0.18485	
0.44253	-1.17546	1.20787	0.32629	-0.83784	-1.17487	0.15613	-0.27245	-0.36242	-1.12636	0.18154	
-0.53197	-0.50726	-0.42396	-0.65869	0.06019	-0.06251	-0.93979	-0.48632	-0.34695	0.92979	-0.16431	0.30237	0.46385	0.99965	-0.58884	0.05136	-0.36326	0.06114	0.33942	0.16473	1.18047	
0.58073	1.66903	-0.61573	0.76318	-0.00588	-0.59657	0.40065	-0.55528	1.39563	0.25776	1.59448	
-1.10765	-1.03675	0.48527	0.25848	-0.70003	0.54126	0.17122	-0.09052	-0.75948	0.01516	0.24869	0.04846	1.64624	-2.03306	-0.26295	0.40156	-0.38796	0.01676	1.10148	-1.17593	-0.59604	
-0.263	-0.33273	0.56767	-0.61877	0.43002	-0.10499	0.08673	-0.81155	1.08194	-0.21834	0.66393	
0.81804	-0.28327	-0.59441	1.43944	1.65081	1.09617	-0.36487	-0.78852	0.86423	-0.86296	-0.15037
0.60829	0.81225	0.96226	-0.36085	-0.68099	-0.49707	0.32404	-0.73742	0.44142	0.52196	-0.15134	0.18324
-0.11527	-0.18826	1.25747	1.07251	0.16978	-0.05053	1.37065	0.18094	0.6674	-0.99306	0.47525	1.12158
0.0988	-0.27198	-0.59775	1.45585	0.05478	-0.62791	-0.74036	0.93286	0.2663	0.25377	-0.1836	-0.6417	
0.64422	-0.98398	-0.16704	0.13459	1.51624	-0.66526	-0.75975	-0.39811	-0.96169	0.47481	-1.77691	-1.23853	
-0.68444	-0.15371	-0.25483	-0.03863	0.27687	-0.52205	0.5704	0.10513	-1.20207	-0.55063	
-1.20865	0.88466	1.25258	0.48504	-1.11255	-0.27051	0.21492	-0.09698	-0.09689	-0.65618	1.02504	0.2276
-0.24731	-0.12659	-0.03984	-1.01807	0.18496	0.13316	1.0786	-1.16123	-0.22407	1.00485	0.54495	0.8212
-0.69779	-0.08266	-0.48438	0.27907	-0.09521	0.47647	-0.48756	0.50196	-0.58657	-0.27258	0.31544	
-1.39389	0.18129	0.31196	-0.01288	0.53183	0.76408	-0.3465	0.25764	-0.01421	-0.15301	-0.41479	-0.60236
-0.22056	-0.13504	0.48002	-0.06034	-0.41553	1.89815	0.5354	-1.14202	-0.05988	0.5871	0.80645
-0.5891	-1.13178	0.74642	0.80718	-0.11391	0.23378	-0.47099	-1.83704	-1.02783	1.68635	1.01085	0.48308
-1.07751	0.94989	-0.33616	0.32549	-1.12068	1.22684	0.36639	-0.57707	-0.26259	-1.08217	0.37958	-0.52526
0.66739	-0.25119	-0.7627	0.56048	-0.44399	-1.27831	0.73645	-0.11753	0.12293	0.37985	0.21462	1.33803	
0.41479	-0.64162	0.53266	0.44582	0.64365	0.7663	-0.762	0.61857	1.29125	0.58307	-0.80578	-0.45266
-0.11846	-0.23861	1.06505	0.26138	0.2013	0.12204	-0.58944	0.71368	0.35456	0.96514	-1.1537	-0.59783	
0.12722	-0.1277	1.43542	0.02969	0.83573	-0.20911	1.11169	1.26405	0.84054	0.53883	-0.72351	0.81381	-0.21274	
-0.59365	-0.4708	0.06207	0.74468	0.6139	0.21953	-0.18422	-0.3824	-0.1775	-0.08006	0.68739	-0.46215	
-0.64412	0.2283	1.34255	-0.16432	-1.28273	-0.92972	-0.6185	-0.63282	-0.08797	0.32133	-0.61304	0.9057	
-0.3328	0.48851	-0.38836	0.18423	-0.68775	-1.7567	0.36365	0.21895	0.76382	-0.71521	-0.01022	-0.10426	
0.93098	1.56881	-0.31508	-0.28614	0.53532	0.29426	0.84214	0.83179	0.25683	1.25251	-0.25487	0.46894	0.11251
-1.04095	-0.57498	0.11962	-0.85589	-0.18063	0.29523	0.39305	-0.53294	-0.25926	0.61311	1.84867	
0.81227	-0.28142	-0.53187	-1.4725	-0.70215	-0.49954	-0.17932	-1.63248	0.2963	0.22053	-0.08999	-1.74954	
-0.49601	-0.65011	0.03819	0.27455	0.73916	-0.05471	-0.48517	0.63685	0.22994	1.15323	-0.76813	1.13336	0.7235	
-0.24698	-1.36999	-0.70875	-0.91499	0.66953	1.00963	0.41527	-0.88611	1.06057	-0.72131	0.04229	-0.41981	0.8583
-0.1578	-0.89734	0.66187	-0.32045	0.45145	1.04427	-0.4757	-0.77762	-0.41776	-0.53054	-0.23224	-0.50766	-0.10755	-0.49217	-0.36307	-0.0226	0.33514	-0.54778	-0.25886	-1.12581	0.33799	-0.11024	-1.24602	
0.85179	0.88054	-1.47489	0.47365	-0.11417	-1.39515	0.44279	0.4207	0.56119	-0.6556	1.26861	-1.50648	-1.32667	
1.27086	0.28026	-1.01843	0.16453	0.07431	0.54955	-1.15398	1.61052	0.5456	1.18347	0.47984	-1.84489	]

Produces the following face:

![Sample GAN Face](https://s3.amazonaws.com/data.heatonresearch.com/images/wustl/kaggle/face-60.png)

The image and/or GAN vector can both be used to predict if the individual is wearing glasses.  Images from the data set are at 1024x1024 resolution.  You may wish to downsample to a lower resolution.