Layer - Cropping2d

Cropping2d

Apply cropping to the two-dimensional input.

Constructor

Based on whether TensorSpace Model load a pre-trained model before initialization, configure Layer in different ways. Checkout Layer Configuration documentation for more information about the basic configuration rules.

〔Case 1〕If TensorSpace Model has loaded a pre-trained model before initialization, there is no need to configure network model related parameters.

TSP.layers.Cropping2d();

〔Case 2〕If there is no pre-trained model before initialization, it is required to configure network model related parameters.

[Method 1] Use cropping

TSP.layers.Cropping2d( { cropping : [ [ Int,  Int ], [ Int, Int ] ] } );

[Method 2] Use shape

TSP.layers.Cropping2d( { shape : [ Int, Int, Int ] } );

Fig. 1 - Cropping2d layer close and open

Arguments

Name Tag	Type	Instruction	Usage Notes and Examples
cropping	[Int[]]	Cropping value, Network Model Related	For example, cropping : [ [2, 3], [1, 2] ] means to crop at left=2, right=3, top=1, bottom=2
shape	Int[]	Output shape, Network Model Related	For example, shape: [ 28, 28, 6 ] means the output is 3-dimensional, 6 feature maps and each one is 28 by 28. Data format is channel last.
name	String	Name of the layer	For example, name: "layerName" In Sequential Model: Highly recommend to add a name attribute to make it easier to get Layer object from model. In Functional Model: It is required to configure name attribute for TensorSpace Layer, and the name should be the same as the name of corresponding Layer in pre-trained model.
color	Color Format	Color of layer	Cropping2d's default color is #CEFC86
closeButton	Dict	Close button appearance control dict. More about close button	display: Bool. true[default] Show button, false Hide button ratio: Int. Times to close button's normal size, default is 1, for example, set ratio to be 2, close button will become twice the normal size
initStatus	String	Layer initial status. Open or Close. More about Layer initial Status	close[default]: Closed at beginning, open: Open at beginning
animeTime	Int	The speed of open and close animation	For example, animeTime: 2000 means the animation time will last 2 seconds. Note: Configure animeTime in a specific layer will override model's animeTime configuration.

Properties

.inputShape : Int[]

The shape of input tensor, for example inputShape = [ 28, 28, 3 ] represents 3 feature maps and each one is 28 by 28.

After model.init() data is available, otherwise is undefined.

.outputShape : Int[]

The shape of output tensor is 3-dimensional. 3️⃣

dataFormat is channel last. for example outputShape = [ 32, 32, 4 ] represents the output through this layer has 4 feature maps and each one is 32 by 32.

After model.init() data is available, otherwise is undefined.

.neuralValue : Float[]

The intermediate raw data after this layer.

After load and model.predict() data is available, otherwise is undefined.

.name : String

The customized name of this layer.

Once created, you can get it.

.layerType : String

Type of this layer, return a constant: string Cropping2d.

Once created, you can get it.

Methods

.apply( previous_layer ) : void

Link this layer to previous layer.

This method can be use to construct topology in Functional Model.

See Construct Topology for more details.

.openLayer() : void

Open Layer, if layer is already in "open" status, the layer will keep open.

See Layer Status for more details.

.closeLayer() : void

Close Layer, if layer is already in "close" status, the layer will keep close.

See Layer Status for more details.

Examples

If TensorSpace Model load a pre-trained model before initialization, there is no need to configure network model related parameters.

let croppingLayer = new TSP.layers.Cropping2d( {

    // Recommend Configuration. Required for TensorSpace Functional Model.
    name: "cropping2d1",
    // Optional Configuration.
    animeTime: 4000,
    initStatus: "open"

} );

If there is no pre-trained model before initialization, it is required to configure network model related parameters.

let croppingLayer = new TSP.layers.Cropping2d( {

    // Required network model related Configuration.
    cropping : [ [2, 2], [1, 1] ],
    // Recommend Configuration. Required for TensorSpace Functional Model.
    name: "cropping2d2",
    // Optional Configuration.
    animeTime: 4000,
    initStatus: "open"

} );

Use Case

When you add cropping layer with Keras | TensorFlow | tfjs in your model the corresponding API is Cropping2d in TensorSpace.

Framework	Documentation
Keras	keras.layers.Cropping2D(cropping=((0, 0), (0, 0)))
TensorFlow	tf.keras.layers.Cropping2D
TensorFlow.js	tf.layers.cropping2D (config)

Source Code

tensorspace/src/layer/intermediate/Cropping2d.js