mx.io.ImageRecordUInt8Iter_v1
¶
Description¶
Iterating on image RecordIO files.
ImageRecordUInt8Iter_v1
is deprecated. Use ImageRecordUInt8Iter
instead.
This iterator is identical to ImageRecordIter
except for using uint8
as
the data type instead of float
.
Usage¶
mx.io.ImageRecordUInt8Iter_v1(...)
Arguments¶
Argument |
Description |
---|---|
|
string, optional, default=’’. Path to the image list (.lst) file. Generally created with tools/im2rec.py. Format (Tab separated): <index of record> <one or more labels> <relative path from root folder>. |
|
string, optional, default=’’. Path to the image RecordIO (.rec) file or a directory path. Created with tools/im2rec.py. |
|
string, optional, default=’’. Path to the image RecordIO index (.idx) file. Created with tools/im2rec.py. |
|
string, optional, default=’aug_default’. The augmenter names to represent sequence of augmenters to be applied, seperated by comma. Additional keyword parameters will be seen by these augmenters. |
|
int, optional, default=’1’. The number of labels per image. |
|
int, optional, default=’4’. The number of threads to do preprocessing. |
|
boolean, optional, default=1. If or not output verbose information. |
|
int, optional, default=’1’. Virtually partition the data into these many parts. |
|
int, optional, default=’0’. The i-th virtual partition to be read. |
| Setting device_id to valid positive device id will create || Context::CPUPinned(device_id). Default is || 0. |
shuffle.chunk.size
long (non-negative), optional, default=0.
The data shuffle buffer size in MB. Only valid if shuffle is true.
shuffle.chunk.seed
int, optional, default=’0’.
The random seed for shuffling
seed.aug
int or None, optional, default=’None’.
Random seed for augmentations.
shuffle
boolean, optional, default=0.
Whether to shuffle data randomly or not.
seed
int, optional, default=’0’.
The random seed.
batch.size
int (non-negative), required.
Batch size.
round.batch
boolean, optional, default=1.
Whether to use round robin to handle overflow batch or not.
prefetch.buffer
long (non-negative), optional, default=4.
Maximum number of batches to prefetch.
ctx
{‘cpu’, ‘gpu’},optional, default=’gpu’.
Context data loader optimized for.
dtype
{None, ‘float16’, ‘float32’, ‘float64’, ‘int32’, ‘int64’, ‘int8’, ‘uint8’},optional, default=’None’.
Output data type.
None
means no change.
resize
int, optional, default=’-1’.
Down scale the shorter edge to a new size before applying other augmentations.
rand.crop
boolean, optional, default=0.
If or not randomly crop the image
random.resized.crop
boolean, optional, default=0.
If or not perform random resized cropping on the image, as a standard preprocessing for resnet training on ImageNet data.
max.rotate.angle
int, optional, default=’0’.
Rotate by a random degree in
[-v, v]
max.aspect.ratio
float, optional, default=0.
Change the aspect (namely width/height) to a random value. If min_aspect_ratio is None then the aspect ratio ins sampled from [1 - max_aspect_ratio, 1 + max_aspect_ratio], else it is in
[min_aspect_ratio, max_aspect_ratio]
min.aspect.ratio
float or None, optional, default=None.
Change the aspect (namely width/height) to a random value in
[min_aspect_ratio, max_aspect_ratio]
max.shear.ratio
float, optional, default=0.
Apply a shear transformation (namely
(x,y)->(x+my,y)
) withm
randomly chose from[-max_shear_ratio, max_shear_ratio]
max.crop.size
int, optional, default=’-1’.
Crop both width and height into a random size in
[min_crop_size, max_crop_size].``Ignored if ``random_resized_crop
is True.
min.crop.size
int, optional, default=’-1’.
Crop both width and height into a random size in
[min_crop_size, max_crop_size].``Ignored if ``random_resized_crop
is True.
max.random.scale
float, optional, default=1.
Resize into
[width*s, height*s]
withs
randomly chosen from[min_random_scale, max_random_scale]
. Ignored ifrandom_resized_crop
is True.
min.random.scale
float, optional, default=1.
Resize into
[width*s, height*s]
withs
randomly chosen from[min_random_scale, max_random_scale]``Ignored if ``random_resized_crop
is True.
max.random.area
float, optional, default=1.
Change the area (namely width * height) to a random value in
[min_random_area, max_random_area]
. Ignored ifrandom_resized_crop
is False.
min.random.area
float, optional, default=1.
Change the area (namely width * height) to a random value in
[min_random_area, max_random_area]
. Ignored ifrandom_resized_crop
is False.
max.img.size
float, optional, default=1e+10.
Set the maximal width and height after all resize and rotate argumentation are applied
min.img.size
float, optional, default=0.
Set the minimal width and height after all resize and rotate argumentation are applied
brightness
float, optional, default=0.
Add a random value in
[-brightness, brightness]
to the brightness of image.
contrast
float, optional, default=0.
Add a random value in
[-contrast, contrast]
to the contrast of image.
saturation
float, optional, default=0.
Add a random value in
[-saturation, saturation]
to the saturation of image.
pca.noise
float, optional, default=0.
Add PCA based noise to the image.
random.h
int, optional, default=’0’.
Add a random value in
[-random_h, random_h]
to the H channel in HSL color space.
random.s
int, optional, default=’0’.
Add a random value in
[-random_s, random_s]
to the S channel in HSL color space.
random.l
int, optional, default=’0’.
Add a random value in
[-random_l, random_l]
to the L channel in HSL color space.
rotate
int, optional, default=’-1’.
Rotate by an angle. If set, it overwrites the
max_rotate_angle
option.
fill.value
int, optional, default=’255’.
Set the padding pixels value to
fill_value
.
data.shape
Shape(tuple), required.
The shape of a output image.
inter.method
int, optional, default=’1’.
The interpolation method: 0-NN 1-bilinear 2-cubic 3-area 4-lanczos4 9-auto 10-rand.
pad
int, optional, default=’0’.
Change size from
[width, height]
into[pad + width + pad, pad + height + pad]
by padding pixes
Value¶
iter
The result mx.dataiter
Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/io/iter_image_recordio.cc#L377