AI-MXNet
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lib/AI/MXNet/Image.pm view on Meta::CPAN
AI::MXNet::ImageIter - Image data iterator.
=cut
=head1 DESCRIPTION
Image data iterator with a large number of augumentation choices.
Supports reading from both .rec files and raw image files with image list.
To load from .rec files, please specify path_imgrec. Also specify path_imgidx
to use data partition (for distributed training) or shuffling.
To load from raw image files, specify path_imglist and path_root.
Parameters
----------
batch_size : Int
Number of examples per batch
data_shape : Shape
Data shape in (channels, height, width).
lib/AI/MXNet/Image.pm view on Meta::CPAN
Created with tools/im2rec.py or bin/im2rec
path_imglist : str
path to image list (.lst)
Created with tools/im2rec.py or with custom script.
Format: index\t[one or more label separated by \t]\trelative_path_from_root
imglist: array ref
a list of image with the label(s)
each item is a list [imagelabel: float or array ref of float, imgpath]
path_root : str
Root folder of image files
path_imgidx : str
Path to image index file. Needed for partition and shuffling when using .rec source.
shuffle : bool
Whether to shuffle all images at the start of each iteration.
Can be slow for HDD.
part_index : int
Partition index
num_parts : int
Total number of partitions.
data_name='data' Str
label_name='softmax_label' Str
lib/AI/MXNet/Image.pm view on Meta::CPAN
=cut
has 'batch_size' => (is => 'ro', isa => 'Int', required => 1);
has 'data_shape' => (is => 'ro', isa => 'Shape', required => 1);
has 'label_width' => (is => 'ro', isa => 'Int', default => 1);
has 'data_name' => (is => 'ro', isa => 'Str', default => 'data');
has 'label_name' => (is => 'ro', isa => 'Str', default => 'softmax_label');
has [qw/path_imgrec
path_imglist
path_root
path_imgidx
/] => (is => 'ro', isa => 'Str');
has 'shuffle' => (is => 'ro', isa => 'Bool', default => 0);
has 'part_index' => (is => 'ro', isa => 'Int', default => 0);
has 'num_parts' => (is => 'ro', isa => 'Int', default => 0);
has 'aug_list' => (is => 'rw', isa => 'ArrayRef[CodeRef]');
has 'imglist' => (is => 'rw', isa => 'ArrayRef|HashRef');
has 'kwargs' => (is => 'ro', isa => 'HashRef');
has [qw/imgidx
imgrec
seq
cur
provide_data
provide_label
/] => (is => 'rw', init_arg => undef);
sub BUILD
{
my $self = shift;
assert($self->path_imgrec or $self->path_imglist or ref $self->imglist eq 'ARRAY');
if($self->path_imgrec)
{
print("loading recordio...\n");
if($self->path_imgidx)
{
$self->imgrec(
AI::MXNet::IndexedRecordIO->new(
idx_path => $self->path_imgidx,
uri => $self->path_imgrec,
flag => 'r'
)
);
$self->imgidx([@{ $self->imgrec->keys }]);
}
else
{
$self->imgrec(AI::MXNet::RecordIO->new(uri => $self->path_imgrec, flag => 'r'));
}
}
my %imglist;
my @imgkeys;
if($self->path_imglist)
{
lib/AI/MXNet/Image.pm view on Meta::CPAN
shape => [$self->batch_size]
)
]);
}
if(not defined $self->imgrec)
{
$self->seq(\@imgkeys);
}
elsif($self->shuffle or $self->num_parts > 1)
{
assert(defined $self->imgidx);
$self->seq($self->imgidx);
}
if($self->num_parts > 1)
{
assert($self->part_index < $self->num_parts);
my $N = @{ $self->seq };
my $C = $N/$self->num_parts;
$self->seq([@{ $self->seq }[$self->part_index*$C..($self->part_index+1)*$C-1]]);
}
if(defined $self->aug_list or defined $self->kwargs)
{
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