dnn_readNetFromTensorflow

Deep neural networksfunctionOpenCV 5.0.0

import { dnn_readNetFromTensorflow } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

ARGUMENTSmodel, config, engine, extraOutputs

FUNCTIONdnn_readNetFromTensorflow

RETURN TYPEdnn_Net

Call structure. A void return can still write to destination arguments. The parameter descriptions define inputs, outputs and ownership.

Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.

dnn_readNetFromTensorflow(model: EmbindString, config: EmbindString, engine: number, extraOutputs: StringVector): dnn_Net;

4 available overloads

dnn_readNetFromTensorflow(model: EmbindString): dnn_Net;

dnn_readNetFromTensorflow(model: EmbindString, config: EmbindString): dnn_Net;

dnn_readNetFromTensorflow(model: EmbindString, config: EmbindString, engine: number): dnn_Net;

dnn_readNetFromTensorflow(model: EmbindString, config: EmbindString, engine: number, extraOutputs: StringVector): dnn_Net;

model: path to the .pb file with binary protobuf description of the network architecture
config: path to the .pbtxt file that contains text graph definition in protobuf format. Resulting Net object is built by text graph using weights from a binary one that let us make it more flexible.
engine: select DNN engine to be used. With auto selection the new engine is used.
extraOutputs: specify model outputs explicitly, in addition to the outputs the graph analyzer finds. Please pay attention that the new DNN does not support non-CPU back-ends for now.

Returns

Net object.

Upstream declaration ↗

These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.