Function transform_

tfjs-core/src/ops/image/transform.ts:58–92

* Applies the given transform(s) to the image(s). * * @param image 4d tensor of shape `[batch, imageHeight, imageWidth, depth]`. * @param transforms Projective transform matrix/matrices. A tensor1d of length * 8 or tensor of size N x 8. If one row of transforms is [a0, a1, a2, b0, * b1,

(
    image: Tensor4D|TensorLike, transforms: Tensor2D|TensorLike,
    interpolation: 'nearest'|'bilinear' = 'nearest',
    fillMode: 'constant'|'reflect'|'wrap'|'nearest' = 'constant', fillValue = 0,
    outputShape?: [number, number])

 * @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'}
 */
function transform_(
    image: Tensor4D|TensorLike, transforms: Tensor2D|TensorLike,
    interpolation: 'nearest'|'bilinear' = 'nearest',
    fillMode: 'constant'|'reflect'|'wrap'|'nearest' = 'constant', fillValue = 0,
    outputShape?: [number, number]): Tensor4D {
  const $image = convertToTensor(image, 'image', 'transform', 'float32');
  const $transforms =
      convertToTensor(transforms, 'transforms', 'transform', 'float32');

  util.assert(
      $image.rank === 4,
      () => 'Error in transform: image must be rank 4,' +
          `but got rank ${$image.rank}.`);

  util.assert(
      $transforms.rank === 2 &&
          ($transforms.shape[0] === $image.shape[0] ||
           $transforms.shape[0] === 1) &&
          $transforms.shape[1] === 8,
      () => `Error in transform: Input transform should be batch x 8 or 1 x 8`);

  util.assert(
      outputShape == null || outputShape.length === 2,
      () =>
          'Error in transform: outputShape must be [height, width] or null, ' +
          `but got ${outputShape}.`);

  const inputs: TransformInputs = {image: $image, transforms: $transforms};
  const attrs:
      TransformAttrs = {interpolation, fillMode, fillValue, outputShape};

  return ENGINE.runKernel(
      Transform, inputs as unknown as NamedTensorMap,
      attrs as unknown as NamedAttrMap);
}

export const transform = /* @__PURE__ */ op({transform_});