GstInference/Example Applications/Classification: Difference between revisions
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== Building the Example == | == Building the Example == | ||
The example builds along the GstInference project. Make sure you follow the instructions in [GstInference/Building the Project] to make sure all the dependencies are correctly fulfilled. | |||
Once the project is built the example may be built independently by running '''make''' within the example directory. | |||
<syntaxhighlight lang=bash lines=1> | |||
cd tests/examples/classification | |||
make | |||
</syntaxhighlight> | |||
The example is not meant to be installed. | |||
== Running the Example == | == Running the Example == | ||
The classification application provides a series of cmdline options to control de behavior of the example. The basic usage is: | |||
<syntaxhighlight lang=bash lines=1> | |||
./classification -m MODEL -f FILE -b BACKEND [-v] | |||
</syntaxhighlight> | |||
;-m|--model | |||
:Mandatory. Path to the InceptionV4 trained model | |||
;-f|--file | |||
:Mandatory. Path to the video file to be used | |||
;-b|--backed | |||
:Mandatory. Name of the backed to be used. See | |||
== Extending the Application == | == Extending the Application == |
Revision as of 06:12, 22 February 2019
Make sure you also check GstInference's companion project: R2Inference |
GstInference |
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Introduction |
Getting started |
Supported architectures |
InceptionV1 InceptionV3 YoloV2 AlexNet |
Supported backends |
Caffe |
Metadata and Signals |
Overlay Elements |
Utils Elements |
Legacy pipelines |
Example pipelines |
Example applications |
Benchmarks |
Model Zoo |
Project Status |
Contact Us |
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This example receives an input video file and classifies each frame into one of 1000 possible classes. For each classified frame the application captures the signal emitted by GstInference, forwarding the prediction to a placeholder for external logic. Simultaneously, the pipeline displays the captured frames with the associated label in a window. Not that the image currently being displayed not necessarily matches de one being handled by the signal. The display is meant for visualization and debugging purposes.
The classification architecture being used by the example is InceptionV4 trained using the Large Scale Visual Recognition Challenge 2012 (ILSVRC2012) Dataset. A pre-trained model can be downloaded from the GstInference Model Zoo
This examples serves both as an example and as a starting point for a classification application.
Building the Example
The example builds along the GstInference project. Make sure you follow the instructions in [GstInference/Building the Project] to make sure all the dependencies are correctly fulfilled.
Once the project is built the example may be built independently by running make within the example directory.
cd tests/examples/classification make
The example is not meant to be installed.
Running the Example
The classification application provides a series of cmdline options to control de behavior of the example. The basic usage is:
./classification -m MODEL -f FILE -b BACKEND [-v]
- -m|--model
- Mandatory. Path to the InceptionV4 trained model
- -f|--file
- Mandatory. Path to the video file to be used
- -b|--backed
- Mandatory. Name of the backed to be used. See
Extending the Application
Troubleshooting