Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
openvinotoolkit
training_toolbox_caffe
提交
789ff8dd
T
training_toolbox_caffe
项目概览
openvinotoolkit
/
training_toolbox_caffe
上一次同步 1 年多
通知
0
Star
49
Fork
21
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
DevOps
流水线
流水线任务
计划
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
T
training_toolbox_caffe
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
DevOps
DevOps
流水线
流水线任务
计划
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
流水线任务
提交
Issue看板
前往新版Gitcode,体验更适合开发者的 AI 搜索 >>
未验证
提交
789ff8dd
编写于
9月 09, 2019
作者:
A
Alexander Dokuchaev
提交者:
GitHub
9月 09, 2019
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Use relative paths in scripts arguments (#16)
* Add os.abspath * Fix readme files * Remove CI status
上级
bc22a4bb
变更
9
显示空白变更内容
内联
并排
Showing
9 changed file
with
26 addition
and
28 deletion
+26
-28
README.md
README.md
+0
-2
README_AD.md
README_AD.md
+8
-8
README_AG.md
README_AG.md
+1
-1
README_CR.md
README_CR.md
+5
-5
README_FD.md
README_FD.md
+5
-5
README_PD.md
README_PD.md
+2
-2
models/evaluate.py
models/evaluate.py
+2
-2
models/mo_convert.py
models/mo_convert.py
+1
-1
models/train.py
models/train.py
+2
-2
未找到文件。
README.md
浏览文件 @
789ff8dd
# TTCF: Training Toolbox for Caffe
# TTCF: Training Toolbox for Caffe
[
![Build Status
](
http://134.191.240.124/buildStatus/icon?job=caffe-toolbox/develop/trigger
)
](http://134.191.240.124/job/caffe-toolbox/job/develop/job/trigger/)
This is a
[
BVLC Caffe
](
https://github.com/BVLC/caffe
)
fork that is intended for deployment multiple SSD-based detection models. It includes
This is a
[
BVLC Caffe
](
https://github.com/BVLC/caffe
)
fork that is intended for deployment multiple SSD-based detection models. It includes
-
action detection and action recognition models for smart classroom use-case, see
[
README_AD.md
](
README_AD.md
)
,
-
action detection and action recognition models for smart classroom use-case, see
[
README_AD.md
](
README_AD.md
)
,
-
person detection for smart classroom use-case, see
[
README_PD.md
](
README_PD.md
)
,
-
person detection for smart classroom use-case, see
[
README_PD.md
](
README_PD.md
)
,
...
...
README_AD.md
浏览文件 @
789ff8dd
...
@@ -37,7 +37,7 @@ cd ./models/templates/person_detection_action_recognition_N_classes
...
@@ -37,7 +37,7 @@ cd ./models/templates/person_detection_action_recognition_N_classes
### (optional) Prepare init weights from PD model
### (optional) Prepare init weights from PD model
1.
Run docker in interactive sesion with mounted directory with WIDER dataset
1.
Run docker in interactive ses
s
ion with mounted directory with WIDER dataset
```
Shell
```
Shell
nvidia-docker --rm -it -v <path_to_folder_with_weights>:/workspace tccf bash
nvidia-docker --rm -it -v <path_to_folder_with_weights>:/workspace tccf bash
```
```
...
@@ -59,7 +59,7 @@ On next stage we should train the Action Recognition (AR) model which reuses det
...
@@ -59,7 +59,7 @@ On next stage we should train the Action Recognition (AR) model which reuses det
```
Shell
```
Shell
cd ./models
cd ./models
python train.py --model person_detection_action_recognition \ # name of model
python
3
train.py --model person_detection_action_recognition \ # name of model
--weights action_detection_0005.caffemodel \ # initialize weights from 'init_weights' directory
--weights action_detection_0005.caffemodel \ # initialize weights from 'init_weights' directory
--data_dir <PATH_TO_DATA> \ # path to directory with dataset
--data_dir <PATH_TO_DATA> \ # path to directory with dataset
--work_dir <WORK_DIR> \ # directory to collect file from training process
--work_dir <WORK_DIR> \ # directory to collect file from training process
...
@@ -72,7 +72,7 @@ To evaluate the quality of trained Action Recognition model on your test data yo
...
@@ -72,7 +72,7 @@ To evaluate the quality of trained Action Recognition model on your test data yo
1.
Frame independent evaluation:
1.
Frame independent evaluation:
```
Shell
```
Shell
python evaluate.py --type ad \
python
3
evaluate.py --type ad \
--dir <EXPERIMENT_DIR> \
--dir <EXPERIMENT_DIR> \
--data_dir <DATA_DIR> \
--data_dir <DATA_DIR> \
--annotaion test_tasks.txt \
--annotaion test_tasks.txt \
...
@@ -81,7 +81,7 @@ python evaluate.py --type ad \
...
@@ -81,7 +81,7 @@ python evaluate.py --type ad \
2.
Event-based evaluation:
2.
Event-based evaluation:
```
Shell
```
Shell
python evaluate.py --type ad_event \
python
3
evaluate.py --type ad_event \
--dir <EXPERIMENT_DIR> \
--dir <EXPERIMENT_DIR> \
--data_dir <DATA_DIR> \
--data_dir <DATA_DIR> \
--annotaion test_tasks.txt \
--annotaion test_tasks.txt \
...
@@ -91,7 +91,7 @@ python evaluate.py --type ad_event \
...
@@ -91,7 +91,7 @@ python evaluate.py --type ad_event \
### Export to IR format
### Export to IR format
```
Shell
```
Shell
python mo_convert.py --name action_recognition --type ad \
python
3
mo_convert.py --name action_recognition --type ad \
--dir <EXPERIMENT_DIR> \
--dir <EXPERIMENT_DIR> \
--iter <ITERATION_NUM> \
--iter <ITERATION_NUM> \
--data_type FP32
--data_type FP32
...
...
README_AG.md
浏览文件 @
789ff8dd
...
@@ -27,7 +27,7 @@ python3 $CAFFE_ROOT/python/gen_hdf5_data.py /data/<DATA_VAL_FILE> images_db_val
...
@@ -27,7 +27,7 @@ python3 $CAFFE_ROOT/python/gen_hdf5_data.py /data/<DATA_VAL_FILE> images_db_val
python3 $CAFFE_ROOT/python/gen_hdf5_data.py /data/<DATA_TEST_FILE> images_db_test
python3 $CAFFE_ROOT/python/gen_hdf5_data.py /data/<DATA_TEST_FILE> images_db_test
```
```
3.
Close docker session by
'alt+D'
and check that you have
`images_db_<subset>.hd5`
and
`images_db_<subset>_list.txt`
files in
<DATA_DIR>
.
3.
Close docker session by
`ctrl+D`
and check that you have
`images_db_<subset>.hd5`
and
`images_db_<subset>_list.txt`
files in
<DATA_DIR>
.
## Model training and evaluation
## Model training and evaluation
...
...
README_CR.md
浏览文件 @
789ff8dd
...
@@ -9,7 +9,7 @@ As an example of usage please download a small dataset from [here](https://downl
...
@@ -9,7 +9,7 @@ As an example of usage please download a small dataset from [here](https://downl
To create LMDB files go to the '$CAFFE_ROOT/python/lmdb_utils/' directory and run the following scripts:
To create LMDB files go to the '$CAFFE_ROOT/python/lmdb_utils/' directory and run the following scripts:
1.
Run docker in interactive sesion with mounted directory with WIDER dataset
1.
Run docker in interactive ses
s
ion with mounted directory with WIDER dataset
```
Shell
```
Shell
nvidia-docker run --rm -it --user=$(id -u) -v <DATA_DIR>:/data ttcf bash
nvidia-docker run --rm -it --user=$(id -u) -v <DATA_DIR>:/data ttcf bash
```
```
...
@@ -22,7 +22,7 @@ python3 $CAFFE_ROOT/python/lmdb_utils/convert_to_voc_format.py /data/annotation_
...
@@ -22,7 +22,7 @@ python3 $CAFFE_ROOT/python/lmdb_utils/convert_to_voc_format.py /data/annotation_
```
Shell
```
Shell
bash $CAFFE_ROOT/python/lmdb_utils/create_cr_lmdb.sh
bash $CAFFE_ROOT/python/lmdb_utils/create_cr_lmdb.sh
```
```
4.
Close docker session by
'alt+D'
and check that you have lmdb files in
<DATA_DIR>
/lmdb.
4.
Close docker session by
`ctrl+D`
and check that you have lmdb files in
<DATA_DIR>
/lmdb.
###
###
...
@@ -32,7 +32,7 @@ On next stage we should train the Person-vehicle-bike crossroad (four class) det
...
@@ -32,7 +32,7 @@ On next stage we should train the Person-vehicle-bike crossroad (four class) det
```
Shell
```
Shell
cd ./models
cd ./models
python train.py --model crossroad \
python
3
train.py --model crossroad \
--weights person-vehicle-bike-detection-crossroad-0078.caffemodel \
--weights person-vehicle-bike-detection-crossroad-0078.caffemodel \
--data_dir <DATA_DIR> \
--data_dir <DATA_DIR> \
--work_dir<WORK_DIR> \
--work_dir<WORK_DIR> \
...
@@ -44,7 +44,7 @@ python train.py --model crossroad \
...
@@ -44,7 +44,7 @@ python train.py --model crossroad \
To evaluate the quality of trained Person-vehicle-bike crossroad detection model on your test data you can use provided scripts.
To evaluate the quality of trained Person-vehicle-bike crossroad detection model on your test data you can use provided scripts.
```
Shell
```
Shell
python evaluate.py --type cr \
python
3
evaluate.py --type cr \
--dir <WORK_DIR>/crossroad/<EXPERIMENT_NUM> \
--dir <WORK_DIR>/crossroad/<EXPERIMENT_NUM> \
--data_dir <DATA_DIR> \
--data_dir <DATA_DIR> \
--annotation annotation_val_cvt.json \
--annotation annotation_val_cvt.json \
...
@@ -54,7 +54,7 @@ python evaluate.py --type cr \
...
@@ -54,7 +54,7 @@ python evaluate.py --type cr \
### Export to IR format
### Export to IR format
```
Shell
```
Shell
python mo_convert.py --type cr \
python
3
mo_convert.py --type cr \
--name crossroad \
--name crossroad \
--dir <WORK_DIR>/crossroad/<EXPERIMENT_NUM> \
--dir <WORK_DIR>/crossroad/<EXPERIMENT_NUM> \
--iter <ITERATION_NUM> \
--iter <ITERATION_NUM> \
...
...
README_FD.md
浏览文件 @
789ff8dd
...
@@ -8,7 +8,7 @@ The training procedure can be done using data in LMDB format. To launch training
...
@@ -8,7 +8,7 @@ The training procedure can be done using data in LMDB format. To launch training
To create LMDB files go to the '$CAFFE_ROOT/python/lmdb_utils/' directory and run the following scripts:
To create LMDB files go to the '$CAFFE_ROOT/python/lmdb_utils/' directory and run the following scripts:
1.
Run docker in interactive sesion with mounted directory with WIDER dataset
1.
Run docker in interactive ses
s
ion with mounted directory with WIDER dataset
```
Shell
```
Shell
nvidia-docker run --rm -it --user=$(id -u) -v <DATA_DIR>:/data ttcf bash
nvidia-docker run --rm -it --user=$(id -u) -v <DATA_DIR>:/data ttcf bash
```
```
...
@@ -29,7 +29,7 @@ python3 $CAFFE_ROOT/python/lmdb_utils/xml_to_ssd.py --ssd_path /data --xml_path_
...
@@ -29,7 +29,7 @@ python3 $CAFFE_ROOT/python/lmdb_utils/xml_to_ssd.py --ssd_path /data --xml_path_
bash $CAFFE_ROOT/python/lmdb_utils/create_wider_lmdb.sh
bash $CAFFE_ROOT/python/lmdb_utils/create_wider_lmdb.sh
```
```
5.
Close docker session by
'alt+D'
and check that you have lmdb files in
<DATA_DIR>
.
5.
Close docker session by
`ctrl+D`
and check that you have lmdb files in
<DATA_DIR>
.
###
###
...
@@ -39,7 +39,7 @@ On next stage we should train the Face Detection model. To do this follow next s
...
@@ -39,7 +39,7 @@ On next stage we should train the Face Detection model. To do this follow next s
```
Shell
```
Shell
cd ./models
cd ./models
python
train.py --model face_detection \
# name of model
python
3 train.py --model face_detection \
# name of model
--weights face-detection-retail-0044.caffemodel \ # initialize weights from 'init_weights' directory
--weights face-detection-retail-0044.caffemodel \ # initialize weights from 'init_weights' directory
--data_dir <DATA_DIR> \ # path to directory with dataset
--data_dir <DATA_DIR> \ # path to directory with dataset
--work_dir <WORK_DIR> \ # directory to collect file from training process
--work_dir <WORK_DIR> \ # directory to collect file from training process
...
@@ -51,7 +51,7 @@ python train.py --model face_detection \ # name of mod
...
@@ -51,7 +51,7 @@ python train.py --model face_detection \ # name of mod
To evaluate the quality of trained Face Detection model on your test data you can use provided scripts.
To evaluate the quality of trained Face Detection model on your test data you can use provided scripts.
```
Shell
```
Shell
python evaluate.py --type fd \
python
3
evaluate.py --type fd \
--dir <WORK_DIR>/face_detection/<EXPERIMENT_NUM> \
--dir <WORK_DIR>/face_detection/<EXPERIMENT_NUM> \
--data_dir <DATA_DIR> \
--data_dir <DATA_DIR> \
--annotation wider_val.xml \
--annotation wider_val.xml \
...
@@ -61,7 +61,7 @@ python evaluate.py --type fd \
...
@@ -61,7 +61,7 @@ python evaluate.py --type fd \
### Export to IR format
### Export to IR format
```
Shell
```
Shell
python mo_convert.py --name face_detection \
python
3
mo_convert.py --name face_detection \
--dir <WORK_DIR>/face_detection/<EXPERIMENT_NUM> \
--dir <WORK_DIR>/face_detection/<EXPERIMENT_NUM> \
--iter <ITERATION_NUM> \
--iter <ITERATION_NUM> \
--data_type FP32
--data_type FP32
...
...
README_PD.md
浏览文件 @
789ff8dd
...
@@ -13,7 +13,7 @@ On first stage you should train the SSD-based person (two class) detector. To do
...
@@ -13,7 +13,7 @@ On first stage you should train the SSD-based person (two class) detector. To do
```
Shell
```
Shell
cd ./models
cd ./models
python
train.py --model person_detection \
# name of model
python
3 train.py --model person_detection \
# name of model
--weights person_detection_0022.caffemodel \ # initialize weights from 'init_weights' directory
--weights person_detection_0022.caffemodel \ # initialize weights from 'init_weights' directory
--data_dir <PATH_TO_DATA> \ # path to directory with dataset
--data_dir <PATH_TO_DATA> \ # path to directory with dataset
--work_dir <WORK_DIR> # directory to collect file from training process
--work_dir <WORK_DIR> # directory to collect file from training process
...
@@ -28,7 +28,7 @@ Note: to get more accurate model it's recommended to use pre-training of backbon
...
@@ -28,7 +28,7 @@ Note: to get more accurate model it's recommended to use pre-training of backbon
```
Shell
```
Shell
cd ./models
cd ./models
python mo_convert.py --name face_detection \
python
3
mo_convert.py --name face_detection \
--dir <WORK_DIR>/person_detection/<EXPERIMENT_NUM> \
--dir <WORK_DIR>/person_detection/<EXPERIMENT_NUM> \
--iter <INTERATION> \
--iter <INTERATION> \
--data_type FP32
--data_type FP32
...
...
models/evaluate.py
浏览文件 @
789ff8dd
...
@@ -102,8 +102,8 @@ def main():
...
@@ -102,8 +102,8 @@ def main():
exec_bin
,
'run'
,
'--rm'
,
exec_bin
,
'run'
,
'--rm'
,
'--name'
,
container_name
,
'--name'
,
container_name
,
'--user=%s:%s'
%
(
os
.
getuid
(),
os
.
getgid
()),
'--user=%s:%s'
%
(
os
.
getuid
(),
os
.
getgid
()),
'-v'
,
'%s:/workspace'
%
args
.
dir
,
'-v'
,
'%s:/workspace'
%
os
.
path
.
abspath
(
args
.
dir
)
,
'-v'
,
'%s:/data:ro'
%
args
.
data_dir
,
# Mount directory with dataset
'-v'
,
'%s:/data:ro'
%
os
.
path
.
abspath
(
args
.
data_dir
)
,
# Mount directory with dataset
args
.
image
args
.
image
]
]
...
...
models/mo_convert.py
浏览文件 @
789ff8dd
...
@@ -75,7 +75,7 @@ def main():
...
@@ -75,7 +75,7 @@ def main():
docker_command
=
[
docker_command
=
[
exec_bin
,
'run'
,
'--rm'
,
exec_bin
,
'run'
,
'--rm'
,
'--user=%s:%s'
%
(
os
.
getuid
(),
os
.
getgid
()),
'--user=%s:%s'
%
(
os
.
getuid
(),
os
.
getgid
()),
'-v'
,
'%s:/workspace'
%
args
.
dir
,
'-v'
,
'%s:/workspace'
%
os
.
path
.
abspath
(
args
.
dir
)
,
args
.
image
args
.
image
]
]
...
...
models/train.py
浏览文件 @
789ff8dd
...
@@ -73,8 +73,8 @@ def main():
...
@@ -73,8 +73,8 @@ def main():
exec_bin
,
'run'
,
'--rm'
,
exec_bin
,
'run'
,
'--rm'
,
'--user=%s:%s'
%
(
os
.
getuid
(),
os
.
getgid
()),
'--user=%s:%s'
%
(
os
.
getuid
(),
os
.
getgid
()),
'--name'
,
container_name
,
# Name of container
'--name'
,
container_name
,
# Name of container
'-v'
,
'%s:/workspace'
%
experiment_dir
,
# Mout work directory
'-v'
,
'%s:/workspace'
%
os
.
path
.
abspath
(
experiment_dir
)
,
# Mout work directory
'-v'
,
'%s:/data:ro'
%
args
.
data_dir
,
# Mount directory with dataset
'-v'
,
'%s:/data:ro'
%
os
.
path
.
abspath
(
args
.
data_dir
)
,
# Mount directory with dataset
'-v'
,
'%s:/init_weights:ro'
%
os
.
path
.
abspath
(
'../init_weights'
),
# Mount directory with init weights
'-v'
,
'%s:/init_weights:ro'
%
os
.
path
.
abspath
(
'../init_weights'
),
# Mount directory with init weights
args
.
image
args
.
image
]
]
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录