public ExtractJpegShape<Integer> extractJpegShape(Operand<String> contents)
ExtractJpegShape
operationcontents
- 0-D. The JPEG-encoded image.ExtractJpegShape
public <T extends Number> CropAndResizeGradBoxes cropAndResizeGradBoxes(Operand<Float> grads, Operand<T> image, Operand<Float> boxes, Operand<Integer> boxInd, CropAndResizeGradBoxes.Options... options)
CropAndResizeGradBoxes
operationgrads
- A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.image
- A 4-D tensor of shape `[batch, image_height, image_width, depth]`.boxes
- A 2-D tensor of shape `[num_boxes, 4]`. The `i`-th row of the tensorboxInd
- A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.options
- carries optional attributes valuesCropAndResizeGradBoxes
public DecodeBmp decodeBmp(Operand<String> contents, DecodeBmp.Options... options)
DecodeBmp
operationcontents
- 0-D. The BMP-encoded image.options
- carries optional attributes valuesDecodeBmp
public <T extends Number> RandomCrop<T> randomCrop(Operand<T> image, Operand<Long> size, RandomCrop.Options... options)
RandomCrop
operationimage
- 3-D of shape `[height, width, channels]`.size
- 1-D of length 2 containing: `crop_height`, `crop_width`..options
- carries optional attributes valuesRandomCrop
public DecodeJpeg decodeJpeg(Operand<String> contents, DecodeJpeg.Options... options)
DecodeJpeg
operationcontents
- 0-D. The JPEG-encoded image.options
- carries optional attributes valuesDecodeJpeg
public <T extends Number> ResizeNearestNeighbor<T> resizeNearestNeighbor(Operand<T> images, Operand<Integer> size, ResizeNearestNeighbor.Options... options)
ResizeNearestNeighbor
operationimages
- 4-D with shape `[batch, height, width, channels]`.size
- = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. Theoptions
- carries optional attributes valuesResizeNearestNeighbor
public <T extends Number> HsvToRgb<T> hsvToRgb(Operand<T> images)
HsvToRgb
operationimages
- 1-D or higher rank. HSV data to convert. Last dimension must be size 3.HsvToRgb
public ExtractGlimpse extractGlimpse(Operand<Float> input, Operand<Integer> size, Operand<Float> offsets, ExtractGlimpse.Options... options)
ExtractGlimpse
operationinput
- A 4-D float tensor of shape `[batch_size, height, width, channels]`.size
- A 1-D tensor of 2 elements containing the size of the glimpsesoffsets
- A 2-D integer tensor of shape `[batch_size, 2]` containingoptions
- carries optional attributes valuesExtractGlimpse
public <T extends Number> ResizeBilinear resizeBilinear(Operand<T> images, Operand<Integer> size, ResizeBilinear.Options... options)
ResizeBilinear
operationimages
- 4-D with shape `[batch, height, width, channels]`.size
- = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. Theoptions
- carries optional attributes valuesResizeBilinear
public EncodeJpegVariableQuality encodeJpegVariableQuality(Operand<UInt8> images, Operand<Integer> quality)
EncodeJpegVariableQuality
operationimages
- Images to adjust. At least 3-D.quality
- An int quality to encode to.EncodeJpegVariableQuality
public <T extends Number> ResizeBicubic resizeBicubic(Operand<T> images, Operand<Integer> size, ResizeBicubic.Options... options)
ResizeBicubic
operationimages
- 4-D with shape `[batch, height, width, channels]`.size
- = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. Theoptions
- carries optional attributes valuesResizeBicubic
public <T extends Number> ExtractImagePatches<T> extractImagePatches(Operand<T> images, List<Long> ksizes, List<Long> strides, List<Long> rates, String padding)
ExtractImagePatches
operationimages
- 4-D Tensor with shape `[batch, in_rows, in_cols, depth]`.ksizes
- The size of the sliding window for each dimension of `images`.strides
- How far the centers of two consecutive patches are inrates
- Must be: `[1, rate_rows, rate_cols, 1]`. This is thepadding
- The type of padding algorithm to use.ExtractImagePatches
public DecodeGif decodeGif(Operand<String> contents)
DecodeGif
operationcontents
- 0-D. The GIF-encoded image.DecodeGif
public <T extends Number> EncodePng encodePng(Operand<T> image, EncodePng.Options... options)
EncodePng
operationimage
- 3-D with shape `[height, width, channels]`.options
- carries optional attributes valuesEncodePng
public <T extends Number> AdjustContrast<T> adjustContrast(Operand<T> images, Operand<Float> contrastFactor)
AdjustContrast
operationimages
- Images to adjust. At least 3-D.contrastFactor
- A float multiplier for adjusting contrast.AdjustContrast
public <T extends Number> ExtractJpegShape<T> extractJpegShape(Operand<String> contents, Class<T> outputType)
ExtractJpegShape
operationcontents
- 0-D. The JPEG-encoded image.outputType
- (Optional) The output type of the operation (int32 or int64).ExtractJpegShape
public DecodePng<UInt8> decodePng(Operand<String> contents, DecodePng.Options... options)
DecodePng
operationcontents
- 0-D. The PNG-encoded image.options
- carries optional attributes valuesDecodePng
public <T extends Number> CropAndResizeGradImage<T> cropAndResizeGradImage(Operand<Float> grads, Operand<Float> boxes, Operand<Integer> boxInd, Operand<Integer> imageSize, Class<T> T, CropAndResizeGradImage.Options... options)
CropAndResizeGradImage
operationgrads
- A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.boxes
- A 2-D tensor of shape `[num_boxes, 4]`. The `i`-th row of the tensorboxInd
- A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.imageSize
- A 1-D tensor with value `[batch, image_height, image_width, depth]`T
- options
- carries optional attributes valuesCropAndResizeGradImage
public <T extends Number> CropAndResize cropAndResize(Operand<T> image, Operand<Float> boxes, Operand<Integer> boxInd, Operand<Integer> cropSize, CropAndResize.Options... options)
CropAndResize
operationimage
- A 4-D tensor of shape `[batch, image_height, image_width, depth]`.boxes
- A 2-D tensor of shape `[num_boxes, 4]`. The `i`-th row of the tensorboxInd
- A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.cropSize
- A 1-D tensor of 2 elements, `size = [crop_height, crop_width]`. Alloptions
- carries optional attributes valuesCropAndResize
public <T extends Number> AdjustSaturation<T> adjustSaturation(Operand<T> images, Operand<Float> scale)
AdjustSaturation
operationimages
- Images to adjust. At least 3-D.scale
- A float scale to add to the saturation.AdjustSaturation
public <T> QuantizedResizeBilinear<T> quantizedResizeBilinear(Operand<T> images, Operand<Integer> size, Operand<Float> min, Operand<Float> max, QuantizedResizeBilinear.Options... options)
QuantizedResizeBilinear
operationimages
- 4-D with shape `[batch, height, width, channels]`.size
- = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. Themin
- max
- options
- carries optional attributes valuesQuantizedResizeBilinear
public EncodeJpeg encodeJpeg(Operand<UInt8> image, EncodeJpeg.Options... options)
EncodeJpeg
operationimage
- 3-D with shape `[height, width, channels]`.options
- carries optional attributes valuesEncodeJpeg
public NonMaxSuppressionWithOverlaps nonMaxSuppressionWithOverlaps(Operand<Float> overlaps, Operand<Float> scores, Operand<Integer> maxOutputSize, Operand<Float> overlapThreshold, Operand<Float> scoreThreshold)
NonMaxSuppressionWithOverlaps
operationoverlaps
- A 2-D float tensor of shape `[num_boxes, num_boxes]` representingscores
- A 1-D float tensor of shape `[num_boxes]` representing a singlemaxOutputSize
- A scalar integer tensor representing the maximum number ofoverlapThreshold
- A 0-D float tensor representing the threshold for deciding whetherscoreThreshold
- A 0-D float tensor representing the threshold for deciding when to removeNonMaxSuppressionWithOverlaps
public <T extends Number> SampleDistortedBoundingBox<T> sampleDistortedBoundingBox(Operand<T> imageSize, Operand<Float> boundingBoxes, Operand<Float> minObjectCovered, SampleDistortedBoundingBox.Options... options)
SampleDistortedBoundingBox
operationimageSize
- 1-D, containing `[height, width, channels]`.boundingBoxes
- 3-D with shape `[batch, N, 4]` describing the N bounding boxesminObjectCovered
- The cropped area of the image must contain at least thisoptions
- carries optional attributes valuesSampleDistortedBoundingBox
public <T extends Number> ResizeArea resizeArea(Operand<T> images, Operand<Integer> size, ResizeArea.Options... options)
ResizeArea
operationimages
- 4-D with shape `[batch, height, width, channels]`.size
- = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. Theoptions
- carries optional attributes valuesResizeArea
public <T extends Number,U extends Number> NonMaxSuppression nonMaxSuppression(Operand<T> boxes, Operand<T> scores, Operand<Integer> maxOutputSize, Operand<U> iouThreshold, Operand<U> scoreThreshold, NonMaxSuppression.Options... options)
NonMaxSuppression
operationboxes
- A 2-D float tensor of shape `[num_boxes, 4]`.scores
- A 1-D float tensor of shape `[num_boxes]` representing a singlemaxOutputSize
- A scalar integer tensor representing the maximum number ofiouThreshold
- A 0-D float tensor representing the threshold for deciding whetherscoreThreshold
- A 0-D float tensor representing the threshold for deciding when to removeoptions
- carries optional attributes valuesNonMaxSuppression
public <T extends Number> RgbToHsv<T> rgbToHsv(Operand<T> images)
RgbToHsv
operationimages
- 1-D or higher rank. RGB data to convert. Last dimension must be size 3.RgbToHsv
public <T extends Number> DecodePng<T> decodePng(Operand<String> contents, Class<T> dtype, DecodePng.Options... options)
DecodePng
operationcontents
- 0-D. The PNG-encoded image.dtype
- options
- carries optional attributes valuesDecodePng
public DecodeAndCropJpeg decodeAndCropJpeg(Operand<String> contents, Operand<Integer> cropWindow, DecodeAndCropJpeg.Options... options)
DecodeAndCropJpeg
operationcontents
- 0-D. The JPEG-encoded image.cropWindow
- 1-D. The crop window: [crop_y, crop_x, crop_height, crop_width].options
- carries optional attributes valuesDecodeAndCropJpeg
public <T extends Number> AdjustHue<T> adjustHue(Operand<T> images, Operand<Float> delta)
AdjustHue
operationimages
- Images to adjust. At least 3-D.delta
- A float delta to add to the hue.AdjustHue
public <T extends Number> DrawBoundingBoxes<T> drawBoundingBoxes(Operand<T> images, Operand<Float> boxes)
DrawBoundingBoxes
operationimages
- 4-D with shape `[batch, height, width, depth]`. A batch of images.boxes
- 3-D with shape `[batch, num_bounding_boxes, 4]` containing boundingDrawBoundingBoxes
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