Table Of Contents
Table Of Contents

ImageRecordIter_v1

mxnet.io.ImageRecordIter_v1(*args, **kwargs)

b’Iterating on image RecordIO filesnn.. note::nn ImageRecordIter_v1 is deprecated. Use ImageRecordIter instead.nnnRead images batches from RecordIO files with a rich of data augmentationnoptions.nnOne can use tools/im2rec.py to pack individual image files into RecordIOnfiles.nnnnDefined in src/io/iter_image_recordio.cc:L352’

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