Update README.md

README.md

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 # Res-GCNN
 residual graph cnn for trajectory prediction, used in autonomous vehicles
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+
+	                   ETH 	      HOTEL	    UNIV	    ZARA1	    ZARA2	    AVG
+
+Social-STGCNN	       0.36/0.63  0.64/1.11	0.37/0.66 0.49/0.85	0.37/0.65 0.44/0.79	
+0.36/0.63
+0.34/0.53	0.35/0.58
+0.30/0.48	0.36/0.63
+0.44/0.75
+250+2txp+tcn3x1
++ all res	0.62/1.13	0.35/0.55	0.43/0.84	0.31/0.53	0.27/0.45	0.39/0.70
+200epoch复现
+3740paras	0.71/1.51	0.36/0.64	0.41/0.75	0.31/0.52	0.26/0.43	
+修高model.py184行，self.n_txpcnn-0	5.06/5.97
+0.81/1.69	4.93/5.75
+0.44/0.78	1.62/1.63
+0.41/0.77	1.53/1.54
+0.31/0.52	1.45/1.47
+0.26/0.44	2.92/3.27
+
+修高model.py184行，self.n_txpcnn-1
++188行
+model_2	0.35/0.61
+0.65/1.23	0.34/0.61
+0.32/0.52	0.29/0.50
+0.40/0.77	0.34/0.60
+0.30/0.50	0.35/0.63
+0.26/0.44	0.33/0.59
+0.39/0.69
+配置同上行,epoch由200改为250
+Model4	0.34/0.61
+0.67/1.33	0.34/0.61
+0.34/0.52	0.29/0.49
+0.39/0.75	0.33/0.59
+0.29/0.50	0.34/0.62
+0.25/0.42	0.33/0.58
+0.39/0.71
+配置同上行,epoch由200改为170
+Model5	0.34/0.60
+0.78/1.64	0.34/0.62
+0.34/0.56	0.29/0.51
+0.40/0.76	0.33/0.60
+0.30/0.51	0.34/0.62
+0.26/0.44	0.33/0.59
+0.42/0.78
+修高model.py184行，self.n_txpcnn-1
++187行	1.40/2.17
+0.69/1.41	1.27/1.97
+0.30/0.46	1.11/1.56
+0.39/0.73	1.08/1.62
+0.30/0.52	1.01/1.56
+0.25/0.43	1.17/1.77
+0.39/0.71
+改为Adam,150epochs
+Model_7	0.32/0.58
+0.85/1.39	0.32/0.58
+0.35/0.53	0.30/0.49
+0.39/0.73	0.33/0.60
+0.29/0.52	0.35/0.62
+0.24/0.41	0.33/0.58
+0.42/0.72
+打开Utils.pu 75 76行
+Model_8