update

pdseg/models/backbone/resnet.py

@@ -85,7 +85,7 @@ class ResNet():
             depth = [3, 8, 36, 3]
         num_filters = [64, 128, 256, 512]
 
-        if self.stem == 'icnet' or self.stem == 'pspnet' or self.stem == 'deeplab':
+        if self.stem == 'icnet' or self.stem == 'pspnet':
             conv = self.conv_bn_layer(
                 input=input,
                 num_filters=int(64 * self.scale),
@@ -256,8 +256,6 @@ class ResNet():
             return input
 
     def bottleneck_block(self, input, num_filters, stride, name, dilation=1):
-        if self.stem == 'deeplab':
-            strides = [1, stride]
         if self.stem == 'pspnet' and self.layers == 101:
             strides = [1, stride]
         else:

pdseg/models/modeling/deeplab.py

@@ -229,37 +229,6 @@ def xception(input):
     return data, decode_shortcut
 
 
-def resnet(input):
-    # backbone: resnet, 可选resnet_50, resnet_101
-    # end_points: resnet终止层数
-    # dilation_dict: resnet block数及对应的膨胀卷积尺度
-    backbone = cfg.MODEL.DEEPLAB.BACKBONE
-    if '50' in backbone:
-        layers = 50
-    elif '101' in backbone:
-        layers = 101
-    else:
-        raise Exception("resnet backbone only support layers 50 or 101")
-    output_stride = cfg.MODEL.DEEPLAB.OUTPUT_STRIDE
-    end_points = layers - 1
-    decode_point = 10
-    if output_stride == 8:
-        dilation_dict = {2: 2, 3: 4}
-    elif output_stride == 16:
-        dilation_dict = {3: 2}
-    else:
-        raise Exception("deeplab only support stride 8 or 16")
-    model = resnet_backbone(layers, stem='deeplab')
-    data, decode_shortcuts = model.net(
-        input,
-        end_points=end_points,
-        decode_points=decode_point,
-        dilation_dict=dilation_dict)
-    decode_shortcut = decode_shortcuts[decode_point]
-
-    return data, decode_shortcut
-
-
 def resnet_vd(input):
     # backbone: resnet_vd, 可选resnet_vd_50, resnet_vd_101
     # end_points: resnet终止层数
@@ -299,10 +268,8 @@ def deeplabv3p(img, num_classes):
         data, decode_shortcut = xception(img)
     elif 'mobilenet' in cfg.MODEL.DEEPLAB.BACKBONE:
         data, decode_shortcut = mobilenetv2(img)
-    elif 'resnet_vd' in cfg.MODEL.DEEPLAB.BACKBONE:
-        data, decode_shortcut = resnet_vd(img)
     elif 'resnet' in cfg.MODEL.DEEPLAB.BACKBONE:
-        data, decode_shortcut = resnet(img)
+        data, decode_shortcut = resnet_vd(img)
     else:
         raise Exception(
             "deeplab only support xception, mobilenet, resnet and resnet_vd backbone"

pdseg/utils/config.py

@@ -194,7 +194,7 @@ cfg.MODEL.FP16 = False
 cfg.MODEL.SCALE_LOSS = "DYNAMIC"
 
 ########################## DeepLab模型配置 ####################################
-# DeepLab backbone 配置, 可选项xception_65, xception_41, xception_71, mobilenetv2, resnet_50, resnet_101, resnet_vd_50, resnet_vd_101
+# DeepLab backbone 配置, 可选项xception_65, xception_41, xception_71, mobilenetv2, resnet50_vd, resnet101_vd
 cfg.MODEL.DEEPLAB.BACKBONE = "xception_65"
 # DeepLab output stride
 cfg.MODEL.DEEPLAB.OUTPUT_STRIDE = 16