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| 1 | +<a href="https://developer.ridgerun.com/wiki/index.php?title=GstInference"><img src="https://developer.ridgerun.com/wiki/images/thumb/9/92/GstInference_Logo_with_name.jpeg/600px-GstInference_Logo_with_name.jpeg" height="400" width="400"></a> |
| 2 | + |
1 | 3 | # GstInference
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2 | 4 |
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3 |
| -A GStreamer deep learning inference framework. |
| 5 | +>See the **[GstInference wiki](https://developer.ridgerun.com/wiki/index.php?title=GstInference)** for the complete documentation. |
| 6 | +
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| 7 | +GstInference is an open-source project from Ridgerun Engineering that provides a framework for integrating deep learning inference into GStreamer. Either use one of the included elements to do out-of-the box inference using the most popular deep learning architectures, or leverage the base classes and utilities to support your own custom architecture. |
| 8 | + |
| 9 | +This repo uses **[R²Inference](https://github.com/RidgeRun/r2inference)**, an abstraction layer in C/C++ for a variety of machine learning frameworks. With R²Inference a single C/C++ application may work with models on different frameworks. This is useful to execute inference taking advantage of different hardware resources such as CPU, GPU, or AI optimized acelerators. |
| 10 | + |
| 11 | +GstInference provides several example elements for common applications, such as [`Inception v4`](ext/r2inference/gstinceptionv4.c) for image classification, [`TinyYOLO v2`](ext/r2inference/gsttinyyolov2.c) for object detection, and [`FaceNet`](ext/r2inference/gstfacenetv1.c) for face recognition. Examples are provided for performing inference on any GStreamer video stream. |
| 12 | + |
| 13 | +<img src="https://developer.ridgerun.com/wiki/images/thumb/4/4f/GstInference-examples.jpeg/800px-GstInference-examples.jpeg" width="800"> |
| 14 | + |
| 15 | +## Installing GstInference |
| 16 | + |
| 17 | +Follow the steps to get GstInference running on your platform: |
| 18 | + |
| 19 | +* [Clone or download R²Inference](https://github.com/RidgeRun/r2inference) |
| 20 | +* [Build R²Inference](https://developer.ridgerun.com/wiki/index.php?title=R2Inference/Getting_started/Building_the_library) |
| 21 | +* [Clone or download GstInference](https://github.com/RidgeRun/gst-inference) |
| 22 | +* [Build GstInference](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Getting_started/Building_the_plugin) |
| 23 | + |
| 24 | +## Examples |
| 25 | + |
| 26 | +We provide GStreamer [example pipelines](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Example_pipelines) for all our suported platforms,architectures and backends. |
| 27 | + |
| 28 | +We also provide [example applications](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Example_Applications) for classification, detection and face recognition. |
| 29 | + |
| 30 | +Our [smart lock](tests/examples/face_detection/README.md) example can get you started with a real security camera application. |
4 | 31 |
|
5 |
| -Please visit the official documentation hosted at: |
6 |
| -> http://developer.ridgerun.com/wiki/index.php?title=GstInference |
| 32 | +We also provide example trained models on our [model zoo](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Model_Zoo) |
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