Delete CSPdarknet53_tiny.py

nets/CSPdarknet53_tiny.py

-from functools import wraps
-
-import tensorflow as tf
-from keras import backend as K
-from keras.layers import (Add, Concatenate, Conv2D, Lambda, Layer,
-                          MaxPooling2D, UpSampling2D, ZeroPadding2D)
-from keras.layers.advanced_activations import LeakyReLU
-from keras.layers.normalization import BatchNormalization
-from keras.regularizers import l2
-from utils.utils import compose
-
-
-def route_group(input_layer, groups, group_id):
-    convs = tf.split(input_layer, num_or_size_splits=groups, axis=-1)
-    return convs[group_id]
-
-#--------------------------------------------------#
-#   单次卷积DarknetConv2D
-#   如果步长为2则自己设定padding方式。
-#   测试中发现没有l2正则化效果更好，所以去掉了l2正则化
-#--------------------------------------------------#
-@wraps(Conv2D)
-def DarknetConv2D(*args, **kwargs):
-    # darknet_conv_kwargs = {'kernel_regularizer': l2(5e-4)}
-    darknet_conv_kwargs = {}
-    darknet_conv_kwargs['padding'] = 'valid' if kwargs.get('strides')==(2,2) else 'same'
-    darknet_conv_kwargs.update(kwargs)
-    return Conv2D(*args, **darknet_conv_kwargs)
-
-#---------------------------------------------------#
-#   卷积块
-#   DarknetConv2D + BatchNormalization + LeakyReLU
-#---------------------------------------------------#
-def DarknetConv2D_BN_Leaky(*args, **kwargs):
-    no_bias_kwargs = {'use_bias': False}
-    no_bias_kwargs.update(kwargs)
-    return compose( 
-        DarknetConv2D(*args, **no_bias_kwargs),
-        BatchNormalization(),
-        LeakyReLU(alpha=0.1))
-
-'''
-                    input
-                      |
-            DarknetConv2D_BN_Leaky
-                      -----------------------
-                      |                     |
-                 route_group              route
-                      |                     |
-            DarknetConv2D_BN_Leaky          |
-                      |                     |
-    -------------------                     |
-    |                 |                     |
- route_1    DarknetConv2D_BN_Leaky          |
-    |                 |                     |
-    -------------Concatenate                |
-                      |                     |
-        ----DarknetConv2D_BN_Leaky          |
-        |             |                     |
-      feat       Concatenate-----------------
-                      |
-                 MaxPooling2D
-'''
-#---------------------------------------------------#
-#   CSPdarknet_tiny的结构块
-#   存在一个大残差边
-#   这个大残差边绕过了很多的残差结构
-#---------------------------------------------------#
-def resblock_body(x, num_filters):
-    # 利用一个3x3卷积进行特征整合
-    x = DarknetConv2D_BN_Leaky(num_filters, (3,3))(x)
-    # 引出一个大的残差边route
-    route = x
-
-    # 对特征层的通道进行分割，取第二部分作为主干部分。
-    x = Lambda(route_group,arguments={'groups':2, 'group_id':1})(x) 
-    # 对主干部分进行3x3卷积
-    x = DarknetConv2D_BN_Leaky(int(num_filters/2), (3,3))(x)
-    # 引出一个小的残差边route_1
-    route_1 = x
-    # 对第主干部分进行3x3卷积
-    x = DarknetConv2D_BN_Leaky(int(num_filters/2), (3,3))(x)
-    # 主干部分与残差部分进行相接
-    x = Concatenate()([x, route_1])
-
-    # 对相接后的结果进行1x1卷积
-    x = DarknetConv2D_BN_Leaky(num_filters, (1,1))(x)
-    feat = x
-    x = Concatenate()([route, x])
-
-    # 利用最大池化进行高和宽的压缩
-    x = MaxPooling2D(pool_size=[2,2],)(x)
-
-    return x, feat
-
-#---------------------------------------------------#
-#   CSPdarknet_tiny的主体部分
-#---------------------------------------------------#
-def darknet_body(x):
-    # 首先利用两次步长为2x2的3x3卷积进行高和宽的压缩
-    # 416,416,3 -> 208,208,32 -> 104,104,64
-    x = ZeroPadding2D(((1,0),(1,0)))(x)
-    x = DarknetConv2D_BN_Leaky(32, (3,3), strides=(2,2))(x)
-    x = ZeroPadding2D(((1,0),(1,0)))(x)
-    x = DarknetConv2D_BN_Leaky(64, (3,3), strides=(2,2))(x)
-    
-    # 104,104,64 -> 52,52,128
-    x, _ = resblock_body(x,num_filters = 64)
-    # 52,52,128 -> 26,26,256
-    x, _ = resblock_body(x,num_filters = 128)
-    # 26,26,256 -> x为13,13,512
-    #           -> feat1为26,26,256
-    x, feat1 = resblock_body(x,num_filters = 256)
-    # 13,13,512 -> 13,13,512
-    x = DarknetConv2D_BN_Leaky(512, (3,3))(x)
-
-    feat2 = x
-    return feat1, feat2
-