更新CNN参数

tools/TrainCNN/backward.py

@@ -54,7 +54,7 @@ def save_para(folder, paras):
         save_bias(fp, paras[7])
 
 
-STEPS = 20000
+STEPS = 100000
 BATCH = 30
 LEARNING_RATE_BASE  = 0.01
 LEARNING_RATE_DECAY = 0.99
@@ -152,7 +152,7 @@ def train(dataset, show_bar=False):
 
 if __name__ == "__main__":
     print("Loading data sets...")
-    dataset = generate.DataSet("/home/xinyang/Desktop/DataSets/box")
+    dataset = generate.DataSet("/home/xinyang/Desktop/DataSets")
     print("Finish!")
     train(dataset, show_bar=True)
     input("Press any key to end...")

tools/TrainCNN/forward.py

@@ -29,20 +29,19 @@ def max_pool_2x2(x):
 CONV1_KERNAL_SIZE = 5
 
 # 第一层卷积输出通道数
-CONV1_OUTPUT_CHANNELS = 6
+CONV1_OUTPUT_CHANNELS = 8
 
 # 第二层卷积核大小
 CONV2_KERNAL_SIZE = 3
 
 # 第二层卷积输出通道数
-CONV2_OUTPUT_CHANNELS = 10
+CONV2_OUTPUT_CHANNELS = 16
 
 # 第一层全连接宽度
 FC1_OUTPUT_NODES = 16
 
 # 第二层全连接宽度（输出标签类型数）
-FC2_OUTPUT_NODES = 8
-
+FC2_OUTPUT_NODES = 11
 # 输出标签类型数
 OUTPUT_NODES = FC2_OUTPUT_NODES
 

tools/para/conv1_b

@@ -1,7 +1,9 @@
-6
-0.25190517
--0.064696774
--1.1652193
--1.3264673
-2.689583
--1.1748564
+8
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+0.71153855
+-3.1710217
+-0.13555647
+-0.1106117
+-0.67361253
+0.8526688
+-0.5431338

tools/para/conv2_b

@@ -1,11 +1,17 @@
-10
-2.339627
-1.8759418
--0.70012397
--0.13009475
-0.17396869
-2.766548
--1.4850869
--2.6339962
--0.12728444
-0.14405365
+16
+-8.03951
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+-0.13434531
+-2.9315674
+-0.19703378
+-1.5522652
+-2.032869
+-3.2706444
+-0.21717867
+-0.19119318
+-0.15644628
+8.05552
+-1.1173456
+1.5701971
+-0.081088655
+-0.1808035

tools/para/fc1_b

@@ -1,17 +1,17 @@
 16
--1.0079371
--0.21348575
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-1.3191578
--0.18780966
-7.9113836
--0.07285687
--4.019421
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--1.286887
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--0.2319671
--5.739259
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+-2.8522294
+-0.097452246
+1.2676659
+-0.038555548

tools/para/fc2_b

@@ -1,7 +1,12 @@
-6
-7.672486
--2.1727772
--1.6976244
--0.39480045
--4.701963
--4.060234
+11
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+12.141608
+-9.4490185
+2.2703283
+-5.419338
+-7.4511914
+0.31088707
+-2.521978
+-4.9146705

tools/para/fc2_w

@@ -1,98 +1,178 @@
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--3.8421887e-34
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--4.5119606e-34
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