mxnet.io.ImageRecordUInt8Iter¶

mxnet.io.ImageRecordUInt8Iter(*args, **kwargs)¶

b’Iterating on image RecordIO filesnnThis iterator is identical to ImageRecordIter except for using uint8 asnthe data type instead of float.nnnnDefined in src/io/iter_image_recordio_2.cc:L777’

Parameters

path_imglist (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>.
path_imgrec (string, optional, default='') – Path to the image RecordIO (.rec) file or a directory path. Created with tools/im2rec.py.
path_imgidx (string, optional, default='') – Path to the image RecordIO index (.idx) file. Created with tools/im2rec.py.
aug_seq (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.
label_width (int, optional, default='1') – The number of labels per image.
data_shape (Shape(tuple), required) – The shape of one output image in (channels, height, width) format.
preprocess_threads (int, optional, default='4') – The number of threads to do preprocessing.
verbose (boolean, optional, default=1) – If or not output verbose information.
num_parts (int, optional, default='1') – Virtually partition the data into these many parts.
part_index (int, optional, default='0') – The i-th virtual partition to be read.
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
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.
dtype ({None, 'float16', 'float32', 'float64', 'int32', 'int64', '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)) with m 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] with s randomly chosen from [min_random_scale, max_random_scale]. Ignored if random_resized_crop is True.
min_random_scale (float, optional, default=1) – Resize into [width*s, height*s] with s 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 if random_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 if random_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.
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
seed_aug (int or None, optional, default='None') – Random seed for augmentations.

Returns

The result iterator.

Return type

MXDataIter