OpenGait release(pre-beta version).

2021-10-18 14:30:21 +08:00
commit 57ee4a448e
41 changed files with 3772 additions and 0 deletions
@@ -0,0 +1,42 @@
+import torch.nn as nn
+from ..modules import BasicConv2d, FocalConv2d
+
+class Plain(nn.Module):
+
+    def __init__(self, layers_cfg, in_channels=1):
+        super(Plain, self).__init__()
+        self.layers_cfg = layers_cfg
+        self.in_channels = in_channels
+
+        self.feature = self.make_layers()
+
+    def forward(self, seqs):
+        out = self.feature(seqs)
+        return out
+    
+    # torchvision/models/vgg.py
+    def make_layers(self):
+        def get_layer(cfg, in_c, kernel_size, stride, padding):
+            cfg = cfg.split('-')
+            typ = cfg[0]
+            if typ not in ['BC', 'FC']:
+                raise AssertionError
+            out_c = int(cfg[1])
+
+            if typ == 'BC':
+                return BasicConv2d(in_c, out_c, kernel_size=kernel_size, stride=stride, padding=padding)
+            return FocalConv2d(in_c, out_c, kernel_size=kernel_size, stride=stride, padding=padding, halving=int(cfg[2]))
+
+        Layers = [get_layer(self.layers_cfg[0], self.in_channels, 5, 1, 2), nn.LeakyReLU(inplace=True)]
+        in_c = int(self.layers_cfg[0].split('-')[1])
+        for cfg in self.layers_cfg[1:]:
+            if cfg == 'M':
+                Layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
+            else:
+                conv2d = get_layer(cfg, in_c, 3, 1, 1)
+                Layers += [conv2d, nn.LeakyReLU(inplace=True)]
+                in_c = int(cfg.split('-')[1])
+        return nn.Sequential(*Layers)
+    
+
+