Table Of Contents
Table Of Contents

ImageRecordIter

mxnet.io.ImageRecordIter(*args, **kwargs)

b’Iterates on image RecordIO filesnnReads batches of images from .rec RecordIO files. One can use im2rec.py tooln(in tools/) to pack raw image files into RecordIO files. This iterator is lessnflexible to customization but is fast and has lot of language bindings. Toniterate over raw images directly use ImageIter instead (in Python).nnExample::nn data_iter = mx.io.ImageRecordIter(n path_imgrec=”./sample.rec”, # The target record file.n data_shape=(3, 227, 227), # Output data shape; 227x227 region will be cropped from the original image.n batch_size=4, # Number of items per batch.n resize=256 # Resize the shorter edge to 256 before cropping.n # You can specify more augmentation options. Use help(mx.io.ImageRecordIter) to see all the options.n )n # You can now use the data_iter to access batches of images.n batch = data_iter.next() # first batch.n images = batch.data[0] # This will contain 4 (=batch_size) images each of 3x227x227.n # process the imagesn …n data_iter.reset() # To restart the iterator from the beginning.nnnnDefined in src/io/iter_image_recordio_2.cc:L751’

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.
  • mirror (boolean, optional, default=0) – Whether to mirror the image or not. If true, images are flipped along the horizontal axis.
  • rand_mirror (boolean, optional, default=0) – Whether to randomly mirror images or not. If true, 50% of the images will be randomly mirrored (flipped along the horizontal axis)
  • mean_img (string, optional, default='') – Filename of the mean image.
  • mean_r (float, optional, default=0) – The mean value to be subtracted on the R channel
  • mean_g (float, optional, default=0) – The mean value to be subtracted on the G channel
  • mean_b (float, optional, default=0) – The mean value to be subtracted on the B channel
  • mean_a (float, optional, default=0) – The mean value to be subtracted on the alpha channel
  • std_r (float, optional, default=1) – Augmentation Param: Standard deviation on R channel.
  • std_g (float, optional, default=1) – Augmentation Param: Standard deviation on G channel.
  • std_b (float, optional, default=1) – Augmentation Param: Standard deviation on B channel.
  • std_a (float, optional, default=1) – Augmentation Param: Standard deviation on Alpha channel.
  • scale (float, optional, default=1) – Multiply the image with a scale value.
  • max_random_contrast (float, optional, default=0) – Change the contrast with a value randomly chosen from [-max_random_contrast, max_random_contrast]
  • max_random_illumination (float, optional, default=0) – Change the illumination with a value randomly chosen from [-max_random_illumination, max_random_illumination]
Returns:

The result iterator.

Return type:

MXDataIter