[04.25.20|08:55:50] Load weights from ./models/st_gcn.kinetics.pt.
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[04.25.20|08:55:51] Load
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基于时空图卷积(ST-GCN)的骨骼动作识别python源码+项目说明(高分毕设).zip个人经导师指导并认可通过的高分毕业设计项目,评审分98分。主要针对计算机相关专业的正在做毕设的学生和需要项目实战练习的学习者,也可作为课程设计、期末大作业。 基于时空图卷积(ST-GCN)的骨骼动作识别python源码+项目说明(高分毕设).zip个人经导师指导并认可通过的高分毕业设计项目,评审分98分。主要针对计算机相关专业的正在做毕设的学生和需要项目实战练习的学习者,也可作为课程设计、期末大作业。 基于时空图卷积(ST-GCN)的骨骼动作识别python源码+项目说明(高分毕设).zip个人经导师指导并认可通过的高分毕业设计项目,评审分98分。主要针对计算机相关专业的正在做毕设的学生和需要项目实战练习的学习者,也可作为课程设计、期末大作业。 基于时空图卷积(ST-GCN)的骨骼动作识别python源码+项目说明(高分毕设).zip个人经导师指导并认可通过的高分毕业设计项目,评审分98分。主要针对计算机相关专业的正在做毕设的学生和需要项目实战练习的学习者,也可作为课程设计、期末大作业
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基于时空图卷积(ST-GCN)的骨骼动作识别(python源码+项目说明).zip (88个子文件)
ST-GCN-maser
logData
AddEdgeWeight_2.txt 502KB
tools
__init__.py 19B
get_models.sh 624B
utils
__init__.py 70B
visualization.py 5KB
openpose.py 1KB
video.py 2KB
__pycache__
visualization.cpython-37.pyc 4KB
video.cpython-37.pyc 2KB
__init__.cpython-37.pyc 235B
openpose.cpython-37.pyc 1KB
ntu_read_skeleton.py 2KB
ntu_gendata.py 4KB
__pycache__
__init__.cpython-37.pyc 162B
kinetics_gendata.py 2KB
feeder
__init__.py 19B
feeder.py 2KB
feeder_kinetics.py 6KB
tools.py 6KB
__pycache__
feeder_kinetics.cpython-37.pyc 5KB
feeder.cpython-37.pyc 2KB
tools.cpython-37.pyc 5KB
__init__.cpython-37.pyc 163B
processor
demo_offline.py 11KB
demo_old.py 5KB
recognition.py 8KB
io.py 4KB
demo_realtime.py 11KB
processor.py 8KB
main.py 943B
resource
demo_asset
pose_estimation.png 6KB
attention+prediction.png 8KB
original_video.png 6KB
attention+rgb.png 6KB
media
ta_chi.mp4 134KB
clean_and_jerk.mp4 212KB
skateboarding.mp4 1.44MB
kinetics_skeleton
label_name.txt 6KB
kinetics-motion.txt 408B
reference_model.txt 57B
NTU-RGB-D
samples_with_missing_skeletons.txt 6KB
info
S002C001P010R001A017_w.gif 673KB
pipeline.png 1.13MB
S001C001P001R001A051_w.gif 408KB
tai_chi_w.gif 1.75MB
hammer_throw_w.gif 1.13MB
S003C001P008R001A008_w.gif 436KB
S003C001P008R001A002_w.gif 504KB
S001C001P001R001A044_w.gif 355KB
juggling_balls_w.gif 1.96MB
demo_video.gif 5.2MB
pull_ups_w.gif 2.5MB
clean_and_jerk_w.gif 2.18MB
DrawLine.py 2KB
net
utils
graph.py 12KB
tgcn.py 3KB
st_gcn.py 8KB
st_gcn_twostream.py 789B
ISSUE_TEMPLATE.md 167B
torchlight
__init__.py 204B
setup.py 197B
gpu.py 750B
io.py 7KB
__pycache__
io.cpython-37.pyc 7KB
__init__.cpython-37.pyc 338B
gpu.cpython-37.pyc 996B
requirements.txt 79B
models
OriginSTGCN.pt 12.17MB
AddEdgeSTGCN12345.pt 11.33MB
kinetics-st_gcn.pt 12.17MB
pose
coco
pose_deploy_linevec.prototxt 45KB
work_dir
recognition
kinetics_skeleton
ST_GCN
log_1.txt 424KB
log.txt 9KB
config.yaml 1KB
tmp
log.txt 645KB
config.yaml 1014B
JustTest.py 3KB
config
st_gcn.twostream
ntu-xview
train.yaml 674B
ntu-xsub
train.yaml 668B
st_gcn
kinetics-skeleton
train.yaml 748B
demo_offline.yaml 252B
demo_old.yaml 238B
test.yaml 441B
demo_realtime.yaml 252B
ntu-xview
train.yaml 653B
test.yaml 436B
ntu-xsub
train.yaml 648B
test.yaml 433B
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