Apply cropping to the two-dimentional input.
Constructor
〔Method 1〕Use cropping
TSP.layers.Cropping2d( { cropping : [ [2, 2], [1, 1] ] } );〔Method 2〕Use shape
TSP.layers.Cropping2d( { shape : [ Int, Int, Int ] } );
Fig. 1 - Cropping2d layer collapse and expand
Arguments
Name Tag |
Type |
Instruction |
Usage Notes and Examples |
|---|---|---|---|
|
cropping |
[Int[]] | Cropping value | cropping : [ [2, 3], [1, 2] ] means to crop at left=2, right=3, top=1, bottom=2 |
|
name |
String | Name of this layer. Highly recommend to arrange to make code more readable. | name: "layerName" |
|
color |
color format | Color of layer | Cropping2d default is #cefc86 |
|
closeButton |
Dict | Close button appearance control dict, more about close button | display : Boolean. true[default] Show button, false Hide button ratio : Int. Times to normal size, default is 1 For example, 2 means twice the normal size |
|
initStatus |
String | Layer status at beginning. Open or Close | close[default] : Closed at beginning |
|
animeTime |
Int | The speed of open and close animation | For example, 2000 means 2 seconds. Note: Configure animeTime in a specific layer will override model's animeTime configuration. |
Properties
.inputShape : Int[]
filter_center_focusThe shape of input tensor, for
example inputShape = [ 28, 28, 3 ] represents 3 feature maps and each
one is 28 by 28.
filter_center_focusAfter model.init() data is
available, otherwise is undefined.
.outputShape : Int[]
filter_center_focusThe shape of output tensor is
3-dimensional. 3️⃣
filter_center_focusdataFormat 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
filter_center_focusAfter model.init() data is
available, otherwise is undefined.
.neuralValue : Float[]
filter_center_focusThe intermediate raw data after this
layer.
filter_center_focusAfter load and model.predict() data
is available, otherwise is undefined.
.name : String
filter_center_focusThe custom name for this layer.
filter_center_focusOnce created, you can get it.
.layerType : String
filter_center_focusType of this layer, return a
constant: string Cropping2d.
filter_center_focusOnce created, you can get it.
Method
.apply( layer ) : void
filter_center_focusThis method only used in Functional Model (Non-sequential, Graph structure).
filter_center_focusLink this layer to layer which is
the previous layer.
filter_center_focusTo crete a link between this layer
and the previous layer. You don't need to use this method specifically to create links in Sequential Model; Instead, you can simply add layers along the lines
of Keras or TensorFlow.js build the model
syntax.
let inputLayer = new TSP.layers.GreyscaleInput( {
shape: [28, 28]
} );
let croppingLayer = new TSP.layers.Cropping2d( {
cropping : [ [2, 2], [1, 1] ]
} );
croppingLayer.apply( inputLayer );.openLayer() : void
filter_center_focusClick on the layer directly to open
it by interacting directly with the object in the 3D scene.
filter_center_focusIn code, calling the method to open
it.
let croppingLayer = new TSP.layers.Cropping2d( {
// configure some parameters for Cropping2d.
} );
model.add( croppingLayer );
// ... add more layers for model.
model.init();
// Call openLayer API to open layer.
croppingLayer.openLayer();.closeLayer() : void
filter_center_focusTo close by interacting directly
with objects in a 3D scene by clicking the close button.
filter_center_focus In code, calling the method to
close it.
let croppingLayer = new TSP.layers.Cropping2d( {
// configure some parameters for Cropping2d.
} );
model.add( croppingLayer );
// ... add more layers for model.
model.init();
// If this layer already opened, call closeLayer API to close layer.
croppingLayer.closeLayer();Example
filter_center_focus Declare an instance of Cropping2d
to facilitate reuse
let croppingLayer = new TSP.layers.Cropping2d( {
cropping : [ [2, 2], [1, 1] ],
animeTime: 4000,
name: "cropping2d1",
opacityRatio: 2
initStatus: "open"
} );
model.add( croppingLayer );filter_center_focusAdd Cropping2d directly
model.add(new TSP.layers.Cropping2d( {
cropping : [ [2, 2], [1, 1] ],
name: "cropping2d2"
} ));Use Case
When you add cropping layer with Keras | TensorFlow | tfjs in your model the corresponding API is
Cropping2d in TensorSpace.
| Framework | Documentation |
|---|---|
| Keras️ | keras.layers.Cropping2D(cropping=((0, 0), (0, 0))) |
| TensorFlow | tf.keras.layers.Cropping2D |
| TensorFlow.js️ | tf.layers.cropping2D (config) |
Tag Lookup
| Tag Icon | Meaning | Instruction |
|---|---|---|
| ⭐️ | Required | Must be provided, cannot be empty. Meanwhile constructor works properly if this arguments provided. Control arguments use default value. |
| 🔧 | Suggest | Recommended for giving. The API can work without them. |
| ⚙️ | Optional | As an auxiliary adjustment parameter when used, selectively added according to the specific situation The parameters here have no effect on the structure of the layer (3D visualized form). |
| 📦 | Model | Configure the properties of the Layer. It changes the output shape. |
| 🎨 | Style | Override the properties in TSP.model (model configuration) |
| 🎦 | Animation | Override the properties in TSP.model (model configuration) |
Source Code