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Deep Learning (DL) has revolutionized classic computer vision techniques to enable even more intelligent and autonomous systems. To ease the software development burden for complex embedded visual Deep Learning applications, a multimedia framework, such as GStreamer, is utilized to simplify the task. The Open Source GStreamer audio video streaming framework is a good choice as it separates the complexities of handling streaming video from the inference models processing the individual frames. GstInference is an open-source GStreamer project sponsored by RidgeRun that allows easy integration of deep learning networks into your video streaming application. | Deep Learning (DL) has revolutionized classic computer vision techniques to enable even more intelligent and autonomous systems. To ease the software development burden for complex embedded visual Deep Learning applications, a multimedia framework, such as GStreamer, is utilized to simplify the task. The Open Source GStreamer audio video streaming framework is a good choice as it separates the complexities of handling streaming video from the inference models processing the individual frames. GstInference is an open-source GStreamer project sponsored by RidgeRun that allows easy integration of deep learning networks into your video streaming application. | ||
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[[File:Coral example.png|thumb|center|600px|Example of use of GstInference in the Coral. The model used was the TinyYolo V2. Video took from https://pixabay.com/videos/road-autobahn-motorway-highway-11018/]] | [[File:Coral example.png|thumb|center|600px|Example of use of GstInference in the Coral. The model used was the TinyYolo V2. Video took from https://pixabay.com/videos/road-autobahn-motorway-highway-11018/]] | ||
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[[GstInference|GstInference]] and [[R2Inference| R2Inference]] are supported by Coral. To install it, follow these guides: | [[GstInference|GstInference]] and [[R2Inference| R2Inference]] are supported by Coral. To install it, follow these guides: | ||