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GaitGL_GREW supported

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Noah
2022-04-19 17:12:10 +08:00
parent e714fa9075
commit 3c71141b3e
5 changed files with 174 additions and 15 deletions
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opengait/modeling/models/gaitgl.py
+23 -12
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@@ -3,7 +3,7 @@ import torch.nn as nn
import torch.nn.functional as F
from ..base_model import BaseModel
from ..modules import SeparateFCs, BasicConv3d, PackSequenceWrapper
from ..modules import SeparateFCs, BasicConv3d, PackSequenceWrapper, SeparateBNNecks
class GLConv(nn.Module):
@@ -75,8 +75,8 @@ class GaitGL(BaseModel):
class_num = model_cfg['class_num']
dataset_name = self.cfgs['data_cfg']['dataset_name']
if dataset_name == 'OUMVLP':
# For OUMVLP
if dataset_name in ['OUMVLP','GREW']:
# For OUMVLP and GREW
self.conv3d = nn.Sequential(
BasicConv3d(1, in_c[0], kernel_size=(3, 3, 3),
stride=(1, 1, 1), padding=(1, 1, 1)),
@@ -135,12 +135,19 @@ class GaitGL(BaseModel):
self.GLConvB2 = GLConv(in_c[2], in_c[2], halving=3, fm_sign=True, kernel_size=(
3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))
self.Head0 = SeparateFCs(64, in_c[-1], in_c[-1])
self.Bn = nn.BatchNorm1d(in_c[-1])
self.Head1 = SeparateFCs(64, in_c[-1], class_num)
self.TP = PackSequenceWrapper(torch.max)
self.HPP = GeMHPP()
self.Head0 = SeparateFCs(64, in_c[-1], in_c[-1])
if 'SeparateBNNecks' in model_cfg.keys():
self.BNNecks = SeparateBNNecks(**model_cfg['SeparateBNNecks'])
self.Bn_head = False
else:
self.Bn = nn.BatchNorm1d(in_c[-1])
self.Head1 = SeparateFCs(64, in_c[-1], class_num)
self.Bn_head = True
def forward(self, inputs):
ipts, labs, _, _, seqL = inputs
@@ -169,12 +176,16 @@ class GaitGL(BaseModel):
outs = outs.permute(2, 0, 1).contiguous() # [p, n, c]
gait = self.Head0(outs) # [p, n, c]
gait = gait.permute(1, 2, 0).contiguous() # [n, c, p]
bnft = self.Bn(gait) # [n, c, p]
logi = self.Head1(bnft.permute(2, 0, 1).contiguous()) # [p, n, c]
if self.Bn_head: # Original GaitGL Head
gait = gait.permute(1, 2, 0).contiguous() # [n, c, p]
bnft = self.Bn(gait) # [n, c, p]
logi = self.Head1(bnft.permute(2, 0, 1).contiguous()) # [p, n, c]
bnft = bnft.permute(0, 2, 1).contiguous() # [n, p, c]
else: # BNNechk as Head
bnft, logi = self.BNNecks(gait) # [p, n, c]
bnft = bnft.permute(1, 0, 2).contiguous() # [n, p, c]
gait = gait.permute(0, 2, 1).contiguous() # [n, p, c]
bnft = bnft.permute(0, 2, 1).contiguous() # [n, p, c]
logi = logi.permute(1, 0, 2).contiguous() # [n, p, c]
n, _, s, h, w = sils.size()