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A tensor is a vector or matrix of n-dimensions that represents all types of data. All values in a tensor hold identical data type with a known (or partially known) A tensor can be originated from the input data or the result of a computation. In TensorFlow, all the operations are conducted inside a graph.In lines 3-8, the model’s input/output names and the input shape are defined. In lines 10-13, a TFlite Converter is created by specifying the model’s frozen graph file, input/output names, and the input shape. Line 14 is a critical command for quantizing custom operations in object detection models. Some operations, such as non-maximum ...
Arm NN provides TFLite parser armnnTfLiteParser, which is a library for loading neural networks defined by TensorFlow Lite FlatBuffers files into the Arm NN runtime. PyArmNN package. fire_detection.tflite, generated from this tutorial and converted to a TensorFlow Lite model.
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Nov 16, 2019 · Thanks to this workaround, the converter can't hardcode the size of the resize nodes, since it's not anymore calculated on the size of the previous node but it is expected to arrive as data. During tflite inference, you use resize_tensor_input on the image input tensor, and in the size tensore you have added you pass the image size.