def jpeg_distortion_pipe(device='cpu', quality=None):
iii = InputImagesIter(seq_len)
inputs = fn.external_source(source=iii, layout='FHWC', batch=False)
if device == 'gpu':
inputs = inputs.gpu()
if quality is None:
quality = fn.random.uniform(range=[1, 99], dtype=types.INT32)
tmp = fn.jpeg_compression_distortion(inputs, quality=quality)
outs = []
for i in range(seq_len):
# First, slice of the distorted sequence
outs.append(fn.slice(tmp, axes=(0, ), start=(i, ), end=(i + 1, )))
# Second, distorted slice of the input
slice_in = fn.slice(inputs, axes=(0, ), start=(i, ), end=(i + 1, ))
outs.append(
fn.jpeg_compression_distortion(slice_in, quality=quality))
return tuple(outs)
def jpeg_distortion_pipe(device='cpu', quality=None):
encoded, _ = fn.readers.file(file_root=images_dir)
in_images = fn.decoders.image(encoded, device='cpu')
if quality is None:
quality = fn.random.uniform(range=[1, 99], dtype=types.INT32)
images = in_images.gpu() if device == 'gpu' else in_images
out_images = fn.jpeg_compression_distortion(images, quality=quality)
return out_images, in_images, quality
def jpeg_distortion_pipe(device='cpu', quality=None):
if layout == 'FHWC':
iii = InputImagesIter(sequence_length)
in_tensors = fn.external_source(source=iii,
layout='FHWC',
batch=False)
else:
encoded, _ = fn.readers.file(file_root=images_dir)
in_tensors = fn.decoders.image(encoded, device='cpu')
inputs = in_tensors.gpu() if device == 'gpu' else in_tensors
if quality is None:
quality = fn.random.uniform(range=[1, 99], dtype=types.INT32)
out_tensors = fn.jpeg_compression_distortion(inputs, quality=quality)
return (out_tensors, in_tensors, quality)