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opencv-wasm

dnn_readNetFromTensorflow1

Deep neural networksfunctionOpenCV 5.0.0
import { dnn_readNetFromTensorflow1 } from '@banou/opencv-wasm'

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

ARGUMENTSbufferModel, bufferConfig, engine, extraOutputs
FUNCTIONdnn_readNetFromTensorflow1
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_readNetFromTensorflow1(bufferModel: ucharVector, bufferConfig: ucharVector, engine: number, extraOutputs: StringVector): dnn_Net;
4 available overloads
dnn_readNetFromTensorflow1(bufferModel: ucharVector): dnn_Net;
dnn_readNetFromTensorflow1(bufferModel: ucharVector, bufferConfig: ucharVector): dnn_Net;
dnn_readNetFromTensorflow1(bufferModel: ucharVector, bufferConfig: ucharVector, engine: number): dnn_Net;
dnn_readNetFromTensorflow1(bufferModel: ucharVector, bufferConfig: ucharVector, engine: number, extraOutputs: StringVector): dnn_Net;
bufferModel

buffer containing the content of the pb file

bufferConfig

buffer containing the content of the pbtxt file

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.