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machinelearningzuu/
emotion_detection_cctv

Name: emotion_detection_cctv
Rating: 2.5 (6 reviews)

generated_from_trainer

microsoft/conditional-detr-resnet-50

finetune

apache-2.0

endpoints_compatible

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emotion_detection_cctv

This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1520
Map: 0.9392
Map 50: 0.9998
Map 75: 0.9948
Map Small: -1.0
Map Medium: -1.0
Map Large: 0.9392
Mar 1: 0.7807
Mar 10: 0.9616
Mar 100: 0.9616
Mar Small: -1.0
Mar Medium: -1.0
Mar Large: 0.9616
Map Nf: 0.9236
Mar 100 Nf: 0.9523
Map F: 0.9547
Mar 100 F: 0.9708

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Map	Map 50	Map 75	Map Small	Map Medium	Map Large	Mar 1	Mar 10	Mar 100	Mar Small	Mar Medium	Mar Large	Map Nf	Mar 100 Nf	Map F	Mar 100 F
No log	1.0	90	1.8304	0.0733	0.1801	0.038	-1.0	0.0	0.0738	0.117	0.4402	0.5369	-1.0	0.0	0.5399	0.1099	0.6468	0.0366	0.427
No log	2.0	180	1.3214	0.1882	0.3323	0.2001	-1.0	-1.0	0.1882	0.2849	0.6302	0.6873	-1.0	-1.0	0.6873	0.3155	0.7319	0.0609	0.6427
No log	3.0	270	1.1104	0.3338	0.5621	0.3832	-1.0	-1.0	0.3338	0.3734	0.6759	0.7053	-1.0	-1.0	0.7053	0.5266	0.7375	0.141	0.673
No log	4.0	360	1.0762	0.3481	0.6067	0.3563	-1.0	-1.0	0.3481	0.3946	0.6117	0.6466	-1.0	-1.0	0.6466	0.5588	0.6875	0.1374	0.6056
No log	5.0	450	0.9652	0.3807	0.6111	0.443	-1.0	0.0	0.3815	0.3975	0.6352	0.6545	-1.0	0.0	0.6578	0.6101	0.7259	0.1513	0.5831
4.5043	6.0	540	0.9340	0.463	0.7541	0.5336	-1.0	0.0	0.4652	0.4403	0.675	0.6853	-1.0	0.0	0.689	0.5897	0.7167	0.3364	0.6539
4.5043	7.0	630	0.9507	0.4406	0.7489	0.4748	0.0	-1.0	0.442	0.411	0.6556	0.6616	0.0	-1.0	0.6633	0.568	0.7042	0.3132	0.6191
4.5043	8.0	720	0.7813	0.5193	0.8038	0.6507	-1.0	-1.0	0.5194	0.4466	0.7254	0.7274	-1.0	-1.0	0.7274	0.6451	0.7324	0.3936	0.7225
4.5043	9.0	810	0.7608	0.5436	0.8306	0.6426	-1.0	-1.0	0.5436	0.4949	0.7161	0.7166	-1.0	-1.0	0.7166	0.6642	0.7366	0.423	0.6966
4.5043	10.0	900	0.7774	0.5606	0.858	0.6495	-1.0	0.0	0.5619	0.4995	0.7321	0.735	-1.0	0.0	0.7367	0.6378	0.7329	0.4833	0.7371
4.5043	11.0	990	0.7060	0.5533	0.8493	0.6853	-1.0	-1.0	0.5533	0.5187	0.7171	0.7174	-1.0	-1.0	0.7174	0.6789	0.7583	0.4278	0.6764
0.8542	12.0	1080	0.7088	0.5999	0.9146	0.7448	-1.0	0.0	0.6031	0.5423	0.7027	0.7043	-1.0	0.0	0.7081	0.6665	0.7435	0.5334	0.6652
0.8542	13.0	1170	0.6888	0.6113	0.9251	0.7798	-1.0	0.0	0.6128	0.5378	0.7202	0.7209	-1.0	0.0	0.7227	0.6805	0.7486	0.5422	0.6933
0.8542	14.0	1260	0.6578	0.6267	0.931	0.7653	-1.0	-1.0	0.627	0.5623	0.7258	0.7272	-1.0	-1.0	0.7272	0.6656	0.7375	0.5878	0.7169
0.8542	15.0	1350	0.6039	0.6602	0.954	0.8066	-1.0	-1.0	0.6604	0.5807	0.7465	0.7474	-1.0	-1.0	0.7474	0.71	0.769	0.6104	0.7258
0.8542	16.0	1440	0.5776	0.6653	0.977	0.8311	-1.0	-1.0	0.6653	0.5896	0.7402	0.7407	-1.0	-1.0	0.7407	0.7063	0.7623	0.6244	0.7191
0.6835	17.0	1530	0.5971	0.6577	0.9538	0.8235	-1.0	-1.0	0.6577	0.5731	0.7449	0.7478	-1.0	-1.0	0.7478	0.6995	0.7619	0.6158	0.7337
0.6835	18.0	1620	0.6152	0.6566	0.9211	0.8114	-1.0	-1.0	0.6566	0.5949	0.7604	0.7615	-1.0	-1.0	0.7615	0.6964	0.7657	0.6167	0.7573
0.6835	19.0	1710	0.6240	0.6666	0.9503	0.8598	-1.0	0.0	0.6811	0.5829	0.7345	0.7363	-1.0	0.0	0.7532	0.6962	0.7569	0.637	0.7157
0.6835	20.0	1800	0.5781	0.6854	0.9693	0.8822	-1.0	-1.0	0.6856	0.6025	0.7605	0.7605	-1.0	-1.0	0.7605	0.704	0.7625	0.6668	0.7584
0.6835	21.0	1890	0.5097	0.7255	0.9829	0.9169	-1.0	0.075	0.7321	0.6342	0.786	0.7862	-1.0	0.15	0.7918	0.733	0.787	0.718	0.7854
0.6835	22.0	1980	0.5694	0.68	0.963	0.8484	-1.0	-1.0	0.68	0.6075	0.7613	0.762	-1.0	-1.0	0.762	0.7047	0.7611	0.6554	0.7629
0.5958	23.0	2070	0.5036	0.7132	0.9856	0.8779	-1.0	0.0	0.7152	0.6227	0.778	0.7802	-1.0	0.0	0.782	0.7326	0.7884	0.6939	0.7719
0.5958	24.0	2160	0.5662	0.6767	0.9519	0.8501	-1.0	0.0	0.6787	0.6025	0.7635	0.7635	-1.0	0.0	0.7653	0.7101	0.7708	0.6434	0.7562
0.5958	25.0	2250	0.5620	0.7029	0.9719	0.9007	-1.0	-1.0	0.703	0.6149	0.7708	0.7713	-1.0	-1.0	0.7713	0.7112	0.7796	0.6946	0.7629
0.5958	26.0	2340	0.5236	0.7173	0.9638	0.9165	-1.0	0.016	0.7187	0.6328	0.7883	0.7886	-1.0	0.4	0.7895	0.7285	0.7907	0.706	0.7864
0.5958	27.0	2430	0.4734	0.7433	0.9886	0.94	-1.0	-1.0	0.7434	0.6431	0.8014	0.8021	-1.0	-1.0	0.8021	0.7472	0.8042	0.7395	0.8
0.5447	28.0	2520	0.4826	0.7364	0.9868	0.942	-1.0	-1.0	0.7364	0.6417	0.7931	0.7941	-1.0	-1.0	0.7941	0.7555	0.8083	0.7172	0.7798
0.5447	29.0	2610	0.5002	0.7229	0.9827	0.9309	-1.0	0.0	0.7279	0.6386	0.7812	0.7812	-1.0	0.0	0.7856	0.7501	0.7995	0.6957	0.7629
0.5447	30.0	2700	0.4752	0.7529	0.9831	0.937	-1.0	-1.0	0.7529	0.6405	0.8089	0.8091	-1.0	-1.0	0.8091	0.7639	0.8093	0.7419	0.809
0.5447	31.0	2790	0.4524	0.7208	0.9756	0.9124	-1.0	-1.0	0.7209	0.6312	0.7916	0.7933	-1.0	-1.0	0.7933	0.7589	0.8157	0.6827	0.7708
0.5447	32.0	2880	0.4278	0.752	0.9906	0.9451	-1.0	-1.0	0.752	0.6536	0.8061	0.8066	-1.0	-1.0	0.8066	0.7781	0.8255	0.7259	0.7876
0.5447	33.0	2970	0.4699	0.7509	0.9883	0.9441	-1.0	-1.0	0.751	0.651	0.8109	0.8114	-1.0	-1.0	0.8114	0.7505	0.8014	0.7514	0.8213
0.5069	34.0	3060	0.5125	0.7178	0.9529	0.9109	-1.0	0.0	0.7277	0.6415	0.7884	0.793	-1.0	0.0	0.8041	0.7346	0.7917	0.7011	0.7943
0.5069	35.0	3150	0.5031	0.7323	0.9687	0.912	-1.0	0.0	0.7407	0.643	0.7889	0.7906	-1.0	0.0	0.7994	0.764	0.8148	0.7005	0.7663
0.5069	36.0	3240	0.4753	0.7423	0.9856	0.9226	-1.0	0.0	0.7445	0.6481	0.7989	0.7989	-1.0	0.0	0.8007	0.7594	0.8056	0.7252	0.7921
0.5069	37.0	3330	0.4264	0.7617	0.9804	0.9631	-1.0	0.0	0.767	0.6575	0.815	0.815	-1.0	0.0	0.8195	0.79	0.8333	0.7335	0.7966
0.5069	38.0	3420	0.3995	0.7762	0.9927	0.9628	-1.0	-1.0	0.7762	0.6747	0.8279	0.8279	-1.0	-1.0	0.8279	0.7764	0.8233	0.776	0.8326
0.4669	39.0	3510	0.4286	0.7475	0.9772	0.9464	-1.0	0.0	0.7553	0.6506	0.8057	0.8057	-1.0	0.0	0.812	0.7851	0.8293	0.71	0.782
0.4669	40.0	3600	0.3864	0.7726	0.9889	0.9608	-1.0	0.0	0.7774	0.6696	0.8235	0.8235	-1.0	0.0	0.8281	0.7991	0.8505	0.7461	0.7966
0.4669	41.0	3690	0.3316	0.8136	0.9983	0.9729	-1.0	-1.0	0.8136	0.6932	0.8572	0.8572	-1.0	-1.0	0.8572	0.8231	0.8639	0.8041	0.8506
0.4669	42.0	3780	0.3657	0.7848	0.9762	0.9601	-1.0	0.0	0.7936	0.6833	0.8424	0.8424	-1.0	0.0	0.8518	0.8105	0.86	0.759	0.8247
0.4669	43.0	3870	0.3636	0.7887	0.9952	0.9636	-1.0	-1.0	0.7888	0.6778	0.8408	0.8408	-1.0	-1.0	0.8408	0.7958	0.8491	0.7816	0.8326
0.4669	44.0	3960	0.3760	0.7813	0.9871	0.9434	-1.0	-1.0	0.7813	0.6789	0.8321	0.8327	-1.0	-1.0	0.8327	0.8005	0.844	0.7621	0.8213
0.4227	45.0	4050	0.3942	0.7916	0.9925	0.9407	-1.0	0.02	0.7937	0.6846	0.8419	0.8421	-1.0	0.1	0.8438	0.7844	0.8315	0.7988	0.8528
0.4227	46.0	4140	0.3440	0.8051	0.9979	0.9767	-1.0	-1.0	0.8051	0.6948	0.8578	0.8578	-1.0	-1.0	0.8578	0.8053	0.8537	0.8049	0.8618
0.4227	47.0	4230	0.3353	0.8129	0.9836	0.9605	-1.0	0.0	0.8172	0.6903	0.8543	0.8543	-1.0	0.0	0.8591	0.8318	0.8727	0.794	0.836
0.4227	48.0	4320	0.3638	0.8048	0.9915	0.9616	-1.0	0.0	0.8069	0.6896	0.8514	0.8514	-1.0	0.0	0.8534	0.8003	0.8444	0.8092	0.8584
0.4227	49.0	4410	0.3310	0.8218	0.9982	0.9699	-1.0	-1.0	0.8218	0.6972	0.865	0.8662	-1.0	-1.0	0.8662	0.8209	0.8694	0.8226	0.8629
0.3807	50.0	4500	0.3393	0.8108	0.9796	0.9528	-1.0	-1.0	0.8108	0.6952	0.8515	0.8515	-1.0	-1.0	0.8515	0.8227	0.8648	0.799	0.8382
0.3807	51.0	4590	0.3205	0.8225	0.9941	0.9719	-1.0	-1.0	0.8225	0.7047	0.8631	0.8631	-1.0	-1.0	0.8631	0.822	0.8644	0.8229	0.8618
0.3807	52.0	4680	0.3399	0.8078	0.9886	0.9539	-1.0	-1.0	0.8078	0.6925	0.8535	0.8535	-1.0	-1.0	0.8535	0.8261	0.8722	0.7894	0.8348
0.3807	53.0	4770	0.3614	0.8174	0.968	0.9492	-1.0	0.0333	0.8223	0.6938	0.855	0.855	-1.0	0.1	0.8614	0.8171	0.856	0.8177	0.8539
0.3807	54.0	4860	0.3446	0.8135	0.9906	0.9588	-1.0	0.0	0.816	0.6978	0.8651	0.8651	-1.0	0.0	0.8671	0.8183	0.8639	0.8086	0.8663
0.3807	55.0	4950	0.3518	0.8203	0.9867	0.9516	-1.0	-1.0	0.8203	0.6975	0.8615	0.8615	-1.0	-1.0	0.8615	0.8355	0.8736	0.8051	0.8494
0.366	56.0	5040	0.2746	0.8359	0.9998	0.9705	-1.0	-1.0	0.8359	0.7175	0.882	0.882	-1.0	-1.0	0.882	0.8422	0.8875	0.8296	0.8764
0.366	57.0	5130	0.2882	0.8351	0.9847	0.9698	-1.0	0.0	0.8392	0.707	0.8763	0.8763	-1.0	0.0	0.8813	0.847	0.8875	0.8232	0.8652
0.366	58.0	5220	0.3049	0.8414	0.9945	0.9679	-1.0	0.15	0.8426	0.7083	0.8776	0.8776	-1.0	0.3	0.879	0.8481	0.8833	0.8348	0.8719
0.366	59.0	5310	0.3217	0.821	0.9892	0.9743	-1.0	-1.0	0.821	0.6989	0.8643	0.8643	-1.0	-1.0	0.8643	0.8278	0.8713	0.8141	0.8573
0.366	60.0	5400	0.2654	0.8564	0.9996	0.9797	-1.0	-1.0	0.8564	0.7286	0.8941	0.8941	-1.0	-1.0	0.8941	0.8585	0.8972	0.8544	0.891
0.366	61.0	5490	0.2880	0.8637	0.9998	0.9787	-1.0	0.1	0.8662	0.7285	0.9	0.9	-1.0	0.1	0.9018	0.8521	0.8898	0.8754	0.9101
0.3186	62.0	5580	0.2817	0.8638	0.9955	0.9703	-1.0	-1.0	0.8638	0.7322	0.9086	0.9086	-1.0	-1.0	0.9086	0.8572	0.8958	0.8704	0.9213
0.3186	63.0	5670	0.2560	0.868	0.9951	0.9807	-1.0	-1.0	0.868	0.7366	0.9099	0.9099	-1.0	-1.0	0.9099	0.8672	0.9074	0.8688	0.9124
0.3186	64.0	5760	0.2785	0.8516	0.9831	0.9709	-1.0	0.0	0.8539	0.7251	0.897	0.897	-1.0	0.0	0.8991	0.854	0.894	0.8491	0.9
0.3186	65.0	5850	0.2623	0.8618	0.9891	0.9501	-1.0	-1.0	0.8618	0.7315	0.9035	0.9035	-1.0	-1.0	0.9035	0.8642	0.9069	0.8594	0.9
0.3186	66.0	5940	0.2568	0.8695	0.9895	0.9607	-1.0	-1.0	0.8695	0.7368	0.9079	0.9079	-1.0	-1.0	0.9079	0.8728	0.9102	0.8663	0.9056
0.2959	67.0	6030	0.2528	0.8736	0.9982	0.9643	-1.0	-1.0	0.8736	0.7344	0.9082	0.9091	-1.0	-1.0	0.9091	0.8793	0.9148	0.868	0.9034
0.2959	68.0	6120	0.2517	0.8736	0.9983	0.976	-1.0	-1.0	0.8736	0.7375	0.9102	0.9102	-1.0	-1.0	0.9102	0.8713	0.9093	0.8758	0.9112
0.2959	69.0	6210	0.2818	0.8636	0.992	0.9578	-1.0	0.2515	0.8717	0.7353	0.9003	0.9003	-1.0	0.25	0.9078	0.8607	0.8972	0.8664	0.9034
0.2959	70.0	6300	0.2222	0.8915	0.9998	0.98	-1.0	-1.0	0.8915	0.753	0.9261	0.9261	-1.0	-1.0	0.9261	0.8826	0.9208	0.9004	0.9315
0.2959	71.0	6390	0.2597	0.8699	0.9868	0.9517	0.0	0.25	0.8733	0.7353	0.9094	0.9094	0.0	0.5	0.9124	0.8745	0.9097	0.8653	0.909
0.2959	72.0	6480	0.2019	0.9087	0.9992	0.9992	-1.0	-1.0	0.9087	0.7603	0.9382	0.9382	-1.0	-1.0	0.9382	0.9001	0.9315	0.9172	0.9449
0.2565	73.0	6570	0.2035	0.8993	0.9997	0.9927	-1.0	-1.0	0.8993	0.7602	0.9331	0.9331	-1.0	-1.0	0.9331	0.8908	0.9269	0.9078	0.9393
0.2565	74.0	6660	0.2539	0.8807	0.9987	0.959	-1.0	-1.0	0.8808	0.7367	0.9145	0.9145	-1.0	-1.0	0.9145	0.8803	0.9144	0.8812	0.9146
0.2565	75.0	6750	0.1972	0.8966	1.0	0.9729	-1.0	-1.0	0.8966	0.7539	0.9299	0.9299	-1.0	-1.0	0.9299	0.9008	0.9306	0.8925	0.9292
0.2565	76.0	6840	0.2068	0.9105	0.9995	0.9936	-1.0	-1.0	0.9105	0.7648	0.9411	0.9411	-1.0	-1.0	0.9411	0.9042	0.9361	0.9169	0.9461
0.2565	77.0	6930	0.2286	0.8966	0.9996	0.964	-1.0	-1.0	0.8966	0.7543	0.9271	0.9271	-1.0	-1.0	0.9271	0.8868	0.9227	0.9064	0.9315
0.246	78.0	7020	0.2135	0.902	0.9899	0.9561	-1.0	0.0	0.9083	0.7514	0.928	0.928	-1.0	0.0	0.9332	0.901	0.9324	0.903	0.9236
0.246	79.0	7110	0.2176	0.9115	0.9894	0.9795	-1.0	0.0	0.9196	0.7649	0.9424	0.9424	-1.0	0.0	0.9478	0.8957	0.9319	0.9273	0.9528
0.246	80.0	7200	0.1864	0.9307	1.0	0.9827	-1.0	-1.0	0.9307	0.7734	0.9528	0.9528	-1.0	-1.0	0.9528	0.9082	0.937	0.9532	0.9685
0.246	81.0	7290	0.1990	0.9179	0.9927	0.9802	-1.0	0.0	0.9222	0.7646	0.9468	0.9468	-1.0	0.0	0.9511	0.897	0.9329	0.9389	0.9607
0.246	82.0	7380	0.1954	0.9117	0.9882	0.9734	-1.0	0.0375	0.9212	0.7632	0.943	0.943	-1.0	0.15	0.9489	0.8915	0.931	0.932	0.9551
0.246	83.0	7470	0.1765	0.9221	0.9979	0.9831	-1.0	-1.0	0.9221	0.7683	0.9483	0.9486	-1.0	-1.0	0.9486	0.9169	0.9477	0.9272	0.9494
0.2126	84.0	7560	0.2004	0.9092	0.995	0.9729	-1.0	0.0	0.9131	0.7576	0.9378	0.9378	-1.0	0.0	0.9399	0.9078	0.9384	0.9106	0.9371
0.2126	85.0	7650	0.1721	0.9352	0.9963	0.9864	-1.0	-1.0	0.9352	0.7757	0.959	0.959	-1.0	-1.0	0.959	0.9229	0.9486	0.9475	0.9693
0.2126	86.0	7740	0.1835	0.9187	0.9994	0.9699	-1.0	-1.0	0.9187	0.7621	0.9452	0.9452	-1.0	-1.0	0.9452	0.9072	0.9398	0.9303	0.9506
0.2126	87.0	7830	0.1892	0.9232	0.9947	0.9738	-1.0	0.0	0.9257	0.7726	0.9483	0.9483	-1.0	0.0	0.9505	0.9071	0.937	0.9393	0.9596
0.2126	88.0	7920	0.1753	0.9186	0.9901	0.9851	-1.0	-1.0	0.9186	0.7667	0.9482	0.9482	-1.0	-1.0	0.9482	0.912	0.9435	0.9253	0.9528
0.2316	89.0	8010	0.1709	0.9268	0.9998	0.9793	-1.0	-1.0	0.9268	0.7707	0.9528	0.9528	-1.0	-1.0	0.9528	0.916	0.9472	0.9375	0.9584
0.2316	90.0	8100	0.1818	0.9206	0.9987	0.9694	-1.0	-1.0	0.9206	0.7615	0.9446	0.9446	-1.0	-1.0	0.9446	0.9197	0.9477	0.9215	0.9416
0.2316	91.0	8190	0.1847	0.9161	0.9845	0.9737	-1.0	0.0	0.923	0.7618	0.9413	0.9413	-1.0	0.0	0.9488	0.9123	0.9398	0.9198	0.9427
0.2316	92.0	8280	0.1540	0.9446	0.9992	0.9971	-1.0	-1.0	0.9446	0.7812	0.9623	0.9623	-1.0	-1.0	0.9623	0.9377	0.9583	0.9516	0.9663
0.2316	93.0	8370	0.1645	0.9343	0.9995	0.9739	-1.0	-1.0	0.9343	0.7773	0.9571	0.9571	-1.0	-1.0	0.9571	0.9146	0.9444	0.954	0.9697
0.2316	94.0	8460	0.1992	0.9212	0.9881	0.962	-1.0	0.6	0.9231	0.7686	0.9473	0.9473	-1.0	0.6	0.9493	0.9004	0.9316	0.9419	0.9629
0.2112	95.0	8550	0.1736	0.9206	0.9858	0.9745	-1.0	0.0112	0.9319	0.7639	0.9449	0.9449	-1.0	0.1	0.9545	0.9246	0.9505	0.9165	0.9393
0.2112	96.0	8640	0.1558	0.9318	0.9997	0.9793	-1.0	-1.0	0.9318	0.7795	0.9571	0.9571	-1.0	-1.0	0.9571	0.9191	0.9491	0.9445	0.9652
0.2112	97.0	8730	0.1535	0.9296	0.9901	0.976	-1.0	0.05	0.9398	0.7746	0.9573	0.9573	-1.0	0.05	0.9647	0.9253	0.9528	0.9339	0.9618
0.2112	98.0	8820	0.2102	0.9071	0.9828	0.9617	0.0	0.0	0.9146	0.7557	0.9351	0.9351	0.0	0.0	0.9426	0.9034	0.9332	0.9107	0.9371
0.2112	99.0	8910	0.1861	0.9205	0.9969	0.9626	-1.0	-1.0	0.9205	0.7618	0.943	0.943	-1.0	-1.0	0.943	0.9134	0.9421	0.9275	0.9438
0.2125	100.0	9000	0.1520	0.9392	0.9998	0.9948	-1.0	-1.0	0.9392	0.7807	0.9616	0.9616	-1.0	-1.0	0.9616	0.9236	0.9523	0.9547	0.9708

Framework versions

Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

machinelearningzuu/emotion_detection_cctv

emotion_detection_cctv

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

machinelearningzuu/
emotion_detection_cctv