Welcome to our Support Center
-
SOTA
-
Accelerator Toolkit
-
Deep Learning Toolkit
-
-
- Resume
- Add
- AlphaDropout
- AdditiveAttention
- Attention
- Average
- AvgPool1D
- AvgPool2D
- AvgPool3D
- BatchNormalization
- Bidirectional
- Concatenate
- Conv1D
- Conv1DTranspose
- Conv2D
- Conv2DTranspose
- Conv3D
- Conv3DTranspose
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Dense
- Cropping1D
- Cropping2D
- Cropping3D
- DepthwiseConv2D
- Dropout
- Embedding
- Flatten
- ELU
- Exponential
- GaussianDropout
- GaussianNoise
- GlobalAvgPool1D
- GlobalAvgPool2D
- GlobalAvgPool3D
- GlobalMaxPool1D
- GlobalMaxPool2D
- GlobalMaxPool3D
- GRU
- GELU
- Input
- LayerNormalization
- LSTM
- MaxPool1D
- MaxPool2D
- MaxPool3D
- MultiHeadAttention
- HardSigmoid
- LeakyReLU
- Linear
- Multiply
- Permute3D
- Reshape
- RNN
- PReLU
- ReLU
- SELU
- Output Predict
- Output Train
- SeparableConv1D
- SeparableConv2D
- SimpleRNN
- SpatialDropout
- Sigmoid
- SoftMax
- SoftPlus
- SoftSign
- Split
- UpSampling1D
- UpSampling2D
- UpSampling3D
- ZeroPadding1D
- ZeroPadding2D
- ZeroPadding3D
- Swish
- TanH
- ThresholdedReLU
- Substract
- Show All Articles (63) Collapse Articles
-
-
-
-
- Exp
- Identity
- Abs
- Acos
- Acosh
- ArgMax
- ArgMin
- Asin
- Asinh
- Atan
- Atanh
- AveragePool
- Bernouilli
- BitwiseNot
- BlackmanWindow
- Cast
- Ceil
- Celu
- ConcatFromSequence
- Cos
- Cosh
- DepthToSpace
- Det
- DynamicTimeWarping
- Erf
- EyeLike
- Flatten
- Floor
- GlobalAveragePool
- GlobalLpPool
- GlobalMaxPool
- HammingWindow
- HannWindow
- HardSwish
- HardMax
- lrfft
- lsNaN
- Log
- LogSoftmax
- LpNormalization
- LpPool
- LRN
- MeanVarianceNormalization
- MicrosoftGelu
- Mish
- Multinomial
- MurmurHash3
- Neg
- NhwcMaxPool
- NonZero
- Not
- OptionalGetElement
- OptionalHasElement
- QuickGelu
- RandomNormalLike
- RandomUniformLike
- RawConstantOfShape
- Reciprocal
- ReduceSumInteger
- RegexFullMatch
- Rfft
- Round
- SampleOp
- Shape
- SequenceLength
- Shrink
- Sin
- Sign
- Sinh
- Size
- SpaceToDepth
- Sqrt
- StringNormalizer
- Tan
- TfldfVectorizer
- Tokenizer
- Transpose
- UnfoldTensor
- lslnf
- ImageDecoder
- Inverse
- Show All Articles (65) Collapse Articles
-
-
-
- Add
- AffineGrid
- And
- BiasAdd
- BiasGelu
- BiasSoftmax
- BiasSplitGelu
- BitShift
- BitwiseAnd
- BitwiseOr
- BitwiseXor
- CastLike
- CDist
- CenterCropPad
- Clip
- Col2lm
- ComplexMul
- ComplexMulConj
- Compress
- ConvInteger
- Conv
- ConvTranspose
- ConvTransposeWithDynamicPads
- CropAndResize
- CumSum
- DeformConv
- DequantizeBFP
- DequantizeLinear
- DequantizeWithOrder
- DFT
- Div
- DynamicQuantizeMatMul
- Equal
- Expand
- ExpandDims
- FastGelu
- FusedConv
- FusedGemm
- FusedMatMul
- FusedMatMulActivation
- GatedRelativePositionBias
- Gather
- GatherElements
- GatherND
- Gemm
- GemmFastGelu
- GemmFloat8
- Greater
- GreaterOrEqual
- GreedySearch
- GridSample
- GroupNorm
- InstanceNormalization
- Less
- LessOrEqual
- LongformerAttention
- MatMul
- MatMulBnb4
- MatMulFpQ4
- MatMulInteger
- MatMulInteger16
- MatMulIntergerToFloat
- MatMulNBits
- MaxPoolWithMask
- MaxRoiPool
- MaxUnPool
- MelWeightMatrix
- MicrosoftDequantizeLinear
- MicrosoftGatherND
- MicrosoftGridSample
- MicrosoftPad
- MicrosoftQLinearConv
- MicrosoftQuantizeLinear
- MicrosoftRange
- MicrosoftTrilu
- Mod
- MoE
- Mul
- MulInteger
- NegativeLogLikelihoodLoss
- NGramRepeatBlock
- NhwcConv
- NhwcFusedConv
- NonMaxSuppression
- OneHot
- Or
- PackedAttention
- PackedMultiHeadAttention
- Pad
- Pow
- QGemm
- QLinearAdd
- QLinearAveragePool
- QLinearConcat
- QLinearConv
- QLinearGlobalAveragePool
- QLinearLeakyRelu
- QLinearMatMul
- QLinearMul
- QLinearReduceMean
- QLinearSigmoid
- QLinearSoftmax
- QLinearWhere
- QMoE
- QOrderedAttention
- QOrderedGelu
- QOrderedLayerNormalization
- QOrderedLongformerAttention
- QOrderedMatMul
- QuantizeLinear
- QuantizeWithOrder
- Range
- ReduceL1
- ReduceL2
- ReduceLogSum
- ReduceLogSumExp
- ReduceMax
- ReduceMean
- ReduceMin
- ReduceProd
- ReduceSum
- ReduceSumSquare
- RelativePositionBias
- Reshape
- Resize
- RestorePadding
- ReverseSequence
- RoiAlign
- RotaryEmbedding
- ScatterElements
- ScatterND
- SequenceAt
- SequenceErase
- SequenceInsert
- Sinh
- Slice
- SparseToDenseMatMul
- SplitToSequence
- Squeeze
- STFT
- StringConcat
- Sub
- Tile
- TorchEmbedding
- TransposeMatMul
- Trilu
- Unsqueeze
- Where
- WordConvEmbedding
- Xor
- Show All Articles (134) Collapse Articles
-
- Attention
- AttnLSTM
- BatchNormalization
- BiasDropout
- BifurcationDetector
- BitmaskBiasDropout
- BitmaskDropout
- DecoderAttention
- DecoderMaskedMultiHeadAttention
- DecoderMaskedSelfAttention
- Dropout
- DynamicQuantizeLinear
- DynamicQuantizeLSTM
- EmbedLayerNormalization
- GemmaRotaryEmbedding
- GroupQueryAttention
- GRU
- LayerNormalization
- LSTM
- MicrosoftMultiHeadAttention
- QAttention
- RemovePadding
- RNN
- Sampling
- SkipGroupNorm
- SkipLayerNormalization
- SkipSimplifiedLayerNormalization
- SoftmaxCrossEntropyLoss
- SparseAttention
- TopK
- WhisperBeamSearch
- Show All Articles (15) Collapse Articles
-
-
-
-
-
-
-
-
-
-
- AdditiveAttention
- Attention
- BatchNormalization
- Bidirectional
- Conv1D
- Conv2D
- Conv1DTranspose
- Conv2DTranspose
- Conv3DTranspose
- Conv3D
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Dense
- DepthwiseConv2D
- Embedding
- LayerNormalization
- GRU
- LSTM
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- MutiHeadAttention
- SeparableConv1D
- SeparableConv2D
- MultiHeadAttention
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- SimpleRNN
- 1D
- 2D
- 3D
- 4D
- 5D
- 6D
- Scalar
- Show All Articles (22) Collapse Articles
-
- AdditiveAttention
- Attention
- BatchNormalization
- Conv1D
- Conv2D
- Conv1DTranspose
- Conv2DTranspose
- Bidirectional
- Conv3D
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Conv3DTranspose
- DepthwiseConv2D
- Dense
- Embedding
- LayerNormalization
- GRU
- PReLU 2D
- PReLU 3D
- PReLU 4D
- MultiHeadAttention
- LSTM
- PReLU 5D
- SeparableConv1D
- SeparableConv2D
- SimpleRNN
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- 1D
- 2D
- 3D
- 4D
- 5D
- 6D
- Scalar
- Show All Articles (21) Collapse Articles
-
-
- AdditiveAttention
- Attention
- BatchNormalization
- Bidirectional
- Conv1D
- Conv2D
- Conv3D
- Conv1DTranspose
- Conv2DTranspose
- Conv3DTranspose
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Dense
- DepthwiseConv2D
- Embedding
- GRU
- LayerNormalization
- LSTM
- MultiHeadAttention
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Resume
- SeparableConv1D
- SeparableConv2D
- SimpleRNN
- Show All Articles (12) Collapse Articles
-
-
- Dense
- Embedding
- AdditiveAttention
- Attention
- MultiHeadAttention
- Conv1D
- Conv2D
- Conv3D
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Conv1DTranspose
- Conv2DTranspose
- Conv3DTranspose
- DepthwiseConv2D
- SeparableConv1D
- SeparableConv2D
- BatchNormalization
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- SimpleRNN
- PReLU 4D
- Show All Articles (15) Collapse Articles
-
- Dense
- Embedding
- AdditiveAttention
- Attention
- MultiHeadAttention
- Conv1D
- Conv2D
- Conv3D
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Conv1DTranspose
- Conv2DTranspose
- Conv3DTranspose
- DepthwiseConv2D
- SeparableConv1D
- SeparableConv2D
- BatchNormalization
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- SimpleRNN
- Show All Articles (14) Collapse Articles
-
-
- Accuracy
- BinaryAccuracy
- BinaryCrossentropy
- BinaryIoU
- CategoricalAccuracy
- CategoricalCrossentropy
- CategoricalHinge
- CosineSimilarity
- FalseNegatives
- FalsePositives
- Hinge
- Huber
- IoU
- KLDivergence
- LogCoshError
- Mean
- MeanAbsoluteError
- MeanAbsolutePercentageError
- MeanIoU
- MeanRelativeError
- MeanSquaredError
- MeanSquaredLogarithmicError
- MeanTensor
- OneHotIoU
- OneHotMeanIoU
- Poisson
- Precision
- PrecisionAtRecall
- Recall
- RecallAtPrecision
- RootMeanSquaredError
- SensitivityAtSpecificity
- SparseCategoricalAccuracy
- SparseCategoricalCrossentropy
- SparseTopKCategoricalAccuracy
- Specificity
- SpecificityAtSensitivity
- SquaredHinge
- Sum
- TopKCategoricalAccuracy
- TrueNegatives
- TruePositives
- Resume
- Show All Articles (27) Collapse Articles
-
-
- Dense
- Embedding
- AdditiveAttention
- Attention
- MultiHeadAttention
- Conv1D
- Conv2D
- Conv3D
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Conv1DTranspose
- Conv2DTranspose
- Conv3DTranspose
- DepthwiseConv2D
- SeparableConv1D
- SeparableConv2D
- BatchNormalization
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- SimpleRNN
- Show All Articles (14) Collapse Articles
-
- Dense
- Embedding
- AdditiveAttention
- Attention
- MultiHeadAttention
- Conv1D
- Conv2D
- Conv3D
- ConvLSTM1D
- ConvLSTM2D
- ConvLSTM3D
- Conv1DTranspose
- Conv2DTranspose
- Conv3DTranspose
- DepthwiseConv2D
- SeparableConv1D
- SeparableConv2D
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- SimpleRNN
- BatchNormalization
- Show All Articles (14) Collapse Articles
-
-
-
Computer Vision Toolkit
-
CUDA Toolkit
-
- Resume
- Array size
- Index Array
- Replace Subset
- Insert Into Array
- Delete From Array
- Initialize Array
- Build Array
- Concatenate Array
- Array Subset
- Min & Max
- Reshape Array
- Short Array
- Reverse 1D array
- Shuffle array
- Search In Array
- Split 1D Array
- Split 2D Array
- Rotate 1D Array
- Increment Array Element
- Decrement Array Element
- Interpolate 1D Array
- Threshold 1D Array
- Interleave 1D Array
- Decimate 1D Array
- Transpose Array
- Remove Duplicate From 1D Array
- Show All Articles (11) Collapse Articles
-
-
- Resume
- Add
- Substract
- Multiply
- Divide
- Quotient & Remainder
- Increment
- Decrement
- Add Array Element
- Multiply Array Element
- Absolute
- Round To Nearest
- Round Toward -Infinity
- Round Toward +Infinity
- Scale By Power Of Two
- Square Root
- Square
- Negate
- Reciprocal
- Sign
- Show All Articles (4) Collapse Articles
Updated
Read Frame
Description
Read the last frame. Type : polymorphic.

Input parameters
Session Src : class
Image Src : class
Output parameters
Session Dst : class
Image Dst : class, the type adapts to the image sent by the camera.
Frame Exist? : boolean, false if the frame doesn’t exist.
Examples
All these examples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Computer Vision βlibrary to run it).
Open and play a camera
1 β Initialize
Open camera reference and create a temporary memory location for an image.
2 β Process
Each loop reads the last frame and displays this frame.
3 β Close
We close all open references.
Table of Contents
