R2Inference/Examples/TensorFlow-Lite: Difference between revisions
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R2Inference | R2Inference provides several examples to highlight its usage with different architectures and frameworks. The models used for these examples can be downloaded from our [[R2Inference/Model Zoo|Model Zoo]]. | ||
== Preparation == | == Preparation == | ||
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For example evaluating this image: | For example, evaluating this image: | ||
[[File:Plane example input.jpg|1800px|center|thumb|Inception example input]] | [[File:Plane example input.jpg|1800px|center|thumb|Inception example input]] | ||
Revision as of 18:51, 28 August 2020
 | Make sure you also check R2Inference's companion project: GstInference |
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R2Inference provides several examples to highlight its usage with different architectures and frameworks. The models used for these examples can be downloaded from our Model Zoo.
Preparation
To test the Tensorflow-Lite example you will need a Tensorflow-Lite C++ API compatible graph file. You can obtain the model from the Model Zoo.
Inception v2
This example is located in r2inference/examples/r2i/tflite .
To use this example run:
./inception -i [JPG input Image] -m [Tflite Model] -s [Model Input Size]
For example, evaluating this image:
Should produce the following output:
./inception -i Plane_example_input.jpg -m graph_inceptionv2.tflite -s 224 Loading Model: graph_inceptionv2.tflite Setting model to engine Loading image: Plane_example_input.jpg Configuring frame Starting engine Predicting... Highest probability is label 405 (0.704471) Stopping engine
According to the ImageNet labels 405 corresponds to an 'airship'.