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1890da2c
编写于
12月 23, 2019
作者:
T
TOsmanov
提交者:
Nikita Manovich
12月 23, 2019
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差异文件
Updating the Model Manager section of the CVAT User Guide (#991)
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@@ -3,7 +3,7 @@
-
[
Authorization
](
#authorization
)
-
[
Administration panel
](
#administration-panel
)
-
[
Creating an annotation task
](
#creating-an-annotation-task
)
-
[
Model
manager
](
#model-manager
)
-
[
Model
s
](
#models
)
-
[
Search
](
#search
)
-
[
Interface of the annotation tool
](
#interface-of-the-annotation-tool
)
-
[
Basic navigation
](
#basic-navigation
)
...
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@@ -272,24 +272,42 @@ Go to the [Django administration panel](http://localhost:8080/admin). There you
![](static/documentation/images/image007.jpg)
### Model
manager
### Model
s
The application will be enabled automatically if
[
OpenVINO™ component
](
/components/openvino/README.md
)
is installed.
It allows to use custom models for auto annotation. Only models in OpenVINO™ toolkit format are supported.
If you would like to annotate a task with a custom model,
please convert it to the intermediate representation (IR) format via the model optimizer tool.
See
[
OpenVINO documentation
](
https://software.intel.com/en-us/articles/OpenVINO-InferEngine
)
for details.
You can "register" a model and "use" it after that to pre annotate your tasks.
On the
``Models``
page allows you to manage your deep learning (DL) models uploaded for auto annotation.
Using the functionality you can upload, update or delete a specific DL model.
To open the model manager, click the
``Models``
button on the navigation bar.
The
``Models``
page contains information about all the existing models. The list of models is divided into two sections:
-
Primary — contains default CVAT models. Each model is a separate element.
It contains the model’s name, a framework on which the model was based on and
``Supported labels``
(a dropdown list of all supported labels).
-
Uploaded by a user — Contains models uploaded by a user.
The list of user models has additional columns with the following information:
name of the user who uploaded the model and the upload date.
Here you can delete models in the
``Actions``
menu.
![](
static/documentation/images/image099.jpg
)
The model manager allows you to manage your deep learning (DL) models uploaded for auto annotation.
Using the functionality you can upload, update or delete a specific DL model.
Use "Auto annotation" button to pre annotate a task using one of your DL models.
[
Read more
](
/cvat/apps/auto_annotation
)
In order to add your model, click
`` Create new model``
.
Enter model name, and select model file using "Select files" button.
To annotate a task with a custom model you need to prepare 4 files:
-
``Model config``
(
*
.xml) - a text file with network configuration.
-
``Model weights``
(
*
.bin) - a binary file with trained weights.
-
``Label map``
(
*
.json) - a simple json file with label_map dictionary like an object with
string values for label numbers.
-
``Interpretation script``
(
*
.py) - a file used to convert net output layer to a predefined structure
which can be processed by CVAT.
You can learn more about creating model files by pressing
[
(?)
](
/cvat/apps/auto_annotation
)
.
Check the box
`` Load globally``
if you want everyone to be able to use the model.
Click the
``Submit``
button to submit a model.
![](
static/documentation/images/image104.jpg
)
After the upload is complete your model can be found in the
``Uploaded by a user``
section.
Use "Auto annotation" button to pre annotate a task using one of your DL models.
[
Read more
](
/cvat/apps/auto_annotation
)
### Search
There are several options how to use the search.
...
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