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lib/A1z/HTML5/Template.pm view on Meta::CPAN
my @thumbs = readdir(TH);
close TH;
foreach ( @thumbs )
{
if ( $_ and $_ =~ /(.jpg|.gif|.jpeg|.png|.tiff)$/ )
{
$out .= qq{\n<a href="$in{images_url}/$_" title="$_" data-gallery> <img src="$in{thumbs_url}/$_" alt="Image $_" width="$in{width}" height="$in{height}"> </a> \n};
}
}
}
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lib/AAC/Pvoice/Bitmap.pm view on Meta::CPAN
$cache->set("$file-$x-$y-$caption-$ibg-$blowup-$pbg-$mtime", $image);
}
my $fh = IO::Scalar->new(\$image);
my $contenttype = 'image/png';
return Wx::Bitmap->new(Wx::Image->newStreamMIME($fh, $contenttype))
}
sub wxColor2hex
{
lib/AAC/Pvoice/Bitmap.pm view on Meta::CPAN
fill => $ibg);
# Call the Composite method of the background image, with the logo image as an argument.
$background->Composite(image=>$img,compose=>'over', gravity => 'North');
$background->Set(quality=>100);
$background->Set(magick => 'png');
$image = $background->imagetoblob();
$cache->set("$file-$x-$y-$caption-$ibg-$blowup-$pbg-$mtime", $image);
undef $background;
undef $img;
}
my $fh = IO::Scalar->new(\$image);
my $contenttype = 'image/png';
return Wx::Bitmap->new(Wx::Image->newStreamMIME($fh, $contenttype))
}
END
{
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lib/AI/Anthropic.pm view on Meta::CPAN
} elsif ($part->{type} eq 'image' && $part->{base64}) {
push @parts, {
type => 'image',
source => {
type => 'base64',
media_type => $part->{media_type} // 'image/png',
data => $part->{base64},
},
};
} else {
push @parts, $part;
lib/AI/Anthropic.pm view on Meta::CPAN
local $/;
my $data = <$fh>;
close $fh;
# Detect media type
my $media_type = 'image/png';
if ($path =~ /\.jpe?g$/i) {
$media_type = 'image/jpeg';
} elsif ($path =~ /\.gif$/i) {
$media_type = 'image/gif';
} elsif ($path =~ /\.webp$/i) {
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lib/AI/Categorizer.pm view on Meta::CPAN
object framework. We give a conceptual overview, but don't get into
any of the details about interfaces or usage. See the documentation
for the individual classes for more details.
A diagram of the various classes in the framework can be seen in
C<doc/classes-overview.png>, and a more detailed view of the same
thing can be seen in C<doc/classes.png>.
=head2 Knowledge Sets
A "knowledge set" is defined as a collection of documents, together
with some information on the categories each document belongs to.
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lib/AI/CleverbotIO.pod view on Meta::CPAN
<a href="https://badge.fury.io/pl/AI-CleverbotIO">
<img alt="Current CPAN version" src="https://badge.fury.io/pl/AI-CleverbotIO.svg">
</a>
<a href="http://cpants.cpanauthors.org/dist/AI-CleverbotIO">
<img alt="Kwalitee" src="http://cpants.cpanauthors.org/dist/AI-CleverbotIO.png">
</a>
<a href="http://www.cpantesters.org/distro/A/AI-CleverbotIO.html?distmat=1">
<img alt="CPAN Testers" src="https://img.shields.io/badge/cpan-testers-blue.svg">
</a>
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t/01-simple.t view on Meta::CPAN
my $graphviz = $dtree->as_graphviz;
ok $graphviz;
if (0) {
# Only works on Mac OS X
my $file = '/tmp/tree.png';
open my($fh), "> $file" or die "$file: $!";
print $fh $graphviz->as_png;
close $fh;
system('open', $file);
}
} else {
skip("Skipping: GraphViz is not installed", 0);
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lib/AI/Genetic/Pro.pm view on Meta::CPAN
my $gd = $graph->plot( [ [ 0..$#{$data->[0]} ], @$data ] ) or croak($@);
open(my $fh, '>', $params{-filename}) or croak($@);
binmode $fh;
print $fh $gd->png;
close $fh;
return 1;
}
#=======================================================================
lib/AI/Genetic/Pro.pm view on Meta::CPAN
# best score
print "SCORE: ", $ga->as_value($ga->getFittest), ".\n";
# save evolution path as a chart
$ga->chart(-filename => 'evolution.png');
# save state of GA
$ga->save('genetic.sga');
# load state of GA
lib/AI/Genetic/Pro.pm view on Meta::CPAN
Path to font (in *.ttf format) to be used (default: none).
=item -logo
Path to logo (png/jpg image) to embed in a chart (default: none).
=item For example:
$ga->chart(-width => 480, height => 320, -filename => 'chart.png');
=back
=item I<$ga>-E<gt>B<save>($file)
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lib/AI/Image.pm view on Meta::CPAN
'key' => 'sk-......',
);
my $image_url = $ai->image("A dog reading a newspaper");
getstore( $image_url, 'my_ai_image.png' );
=head1 SEE ALSO
L<https://openai.com> - OpenAI official website
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lib/AI/ML/Expr.pm view on Meta::CPAN
output => $file,
title => "Cost",
xlabel => "Iter",
ylabel => "Cost"
);
$chart->png;
my $data = Chart::Gnuplot::DataSet->new(
xdata => \@iters,
ydata => \@costs,
style => "linespoints"
);
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examples/calculator.pl view on Meta::CPAN
my @lsz = @{$train_iter->label->[0][1]->shape};
my $shape = {
data => [ $batch_size, splice @dsz, 1 ],
softmax_label => [ $batch_size, splice @lsz, 1 ],
};
print mx->viz->plot_network($sym, shape => $shape)->graph->as_png;
exit;
}
my $model = mx->mod->Module(
symbol => $sym,
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bin/localfiles view on Meta::CPAN
push @INC ,-d $pubdir ? $picdir :"";
my $xx=$memd->get("localfile_".$match);
if(!$xx){
my @images = File::Find::Rule->file()
->name('*'.lc($match).'*\.(png|jpg|gif|svg)')
->in(@INC);
#my $dat = {};
#foreach(@images){
#my @d = split("/",$_);
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lib/AI/NNFlex.pm view on Meta::CPAN
speed it up
write a tk gui
=head1 CHANGES
v0.11 introduces the lesion method, png support in the draw module and datasets.
v0.12 fixes a bug in reinforce.pm & adds a reflector in feedforward->run to make $network->run($dataset) work.
v0.13 introduces the momentum learning algorithm and fixes a bug that allowed training to proceed even if the node activation function module can't be loaded
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MANIFEST.SKIP view on Meta::CPAN
^cpan/
^MYMETA
^.releaserc
^.*.cmd
^AI-Ollama-Client
^frame-\d+.png
^demo/
^\.carmel/
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lib/AI/PredictionClient/Testing/Camel.pm view on Meta::CPAN
use 5.010;
use MIME::Base64 qw( encode_base64 decode_base64 );
use Moo;
my $camel_jpeg_b64;
my $camel_png_b64;
has camel_jpeg_ref => (
is => 'lazy',
builder => 1,
);
lib/AI/PredictionClient/Testing/Camel.pm view on Meta::CPAN
sub _build_camel_jpeg_ref {
my $self = $_[0];
return \decode_base64(${ $self->camel_jpeg_b64_ref });
}
has camel_png_ref => (
is => 'lazy',
builder => 1,
);
sub _build_camel_png_ref {
my $self = $_[0];
return \decode_base64(${ $self->camel_png_b64_ref });
}
has camel_jpeg_b64_ref => (
is => 'ro',
default => sub { \$camel_jpeg_b64 },
);
has camel_png_b64_ref => (
is => 'ro',
default => sub { \$camel_png_b64 },
);
$camel_jpeg_b64
= '/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkS
Ew8UHRofHh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJ
lib/AI/PredictionClient/Testing/Camel.pm view on Meta::CPAN
bA6+g4H4VtWG3+zrbaML5S4GMcYFZ0Kfs3byLqz51csUUUV1GBXnsbW5ffPbxSNt
25ZQTj0p0tpbzW4t5YI3hGAI2UFeOnFTUUrId2RQW8NrF5dvEkSZJ2ouBk1HLp9n
NcLPLaxPMpBV2QEgjpg1ZoostguyG5tLa8QJcwRzKDkB1BANSqqooVQAoGAB0Apa
KLdRXP/Z';
$camel_png_b64
= 'iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAYAAACqaXHeAAAOiUlEQVR42u2beYxd
V33HP+ecu7593uz2eBwvsWMnUJI4gQRSoOw0pSJdpEqILkIq0FYUqfxTKrVIrWhV
IRCiVBUSVFVpC5StLKW0FAqBxCFx7IQ48T5jz/pm3v7uu/s5/WNcILXJYjK2ROb3
15Pufef93uee+zvf8/3dK4wxhudxSJ7nsQVgC8DzPKxneqLRmjyLCftt4qCD45fp
LJ9m8dGvsefOtzCx6wU/ewD67QaNsw8TdZchaSOSJpajkFnMoNvBr1UpOobS6Laf
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lib/AI/TensorFlow/Libtensorflow/Manual/Notebook/InferenceUsingTFHubCenterNetObjDetect.pod view on Meta::CPAN
p %subset;
use PDL::Graphics::Gnuplot;
my $plot_output_path = 'objects-detected.png';
my $gp = gpwin('pngcairo', font => ",12", output => $plot_output_path, aa => 2, size => [10] );
my @qual_cmap = ('#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c','#fdbf6f','#ff7f00','#cab2d6');
$gp->options(
map {
lib/AI/TensorFlow/Libtensorflow/Manual/Notebook/InferenceUsingTFHubCenterNetObjDetect.pod view on Meta::CPAN
with => 'image', $pdl_images[0],
);
$gp->close;
IPerl->png( bytestream => path($plot_output_path)->slurp_raw ) if IN_IPERL;
use Filesys::DiskUsage qw/du/;
my $total = du( { 'human-readable' => 1, dereference => 1 },
$model_archive_path, $model_base );
lib/AI/TensorFlow/Libtensorflow/Manual/Notebook/InferenceUsingTFHubCenterNetObjDetect.pod view on Meta::CPAN
The following uses the bounding boxes and class label information to draw boxes and labels on top of the image using Gnuplot.
use PDL::Graphics::Gnuplot;
my $plot_output_path = 'objects-detected.png';
my $gp = gpwin('pngcairo', font => ",12", output => $plot_output_path, aa => 2, size => [10] );
my @qual_cmap = ('#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c','#fdbf6f','#ff7f00','#cab2d6');
$gp->options(
map {
lib/AI/TensorFlow/Libtensorflow/Manual/Notebook/InferenceUsingTFHubCenterNetObjDetect.pod view on Meta::CPAN
with => 'image', $pdl_images[0],
);
$gp->close;
IPerl->png( bytestream => path($plot_output_path)->slurp_raw ) if IN_IPERL;
=head1 RESOURCE USAGE
use Filesys::DiskUsage qw/du/;
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samples/termites.pl view on Meta::CPAN
for my $ter (@{$ters->{termites}}) {
my $color = (defined($ter->{wood_ix}) ? $red : $green);
$im->filledEllipse(scl($ter->{pos}), 3, 3, $color);
}
my $name = sprintf "%s-%05d.png", $output, $fn;
open my $fh, ">", $name;
print $fh $im->png;
close $fh;
print "$n ($fn)\r";
for (1..$one_of) {
$n++;
samples/termites.pl view on Meta::CPAN
=head1 MAKING MOVIES
In order to convert a set of PNGs into an animation, ffmpeg can be
used as follows:
ffmpeg -i output-%05d.png video.mpg
=head1 SEE ALSO
The idea about artificial termites comes from the book "Adventures in
Modeling" by Vanessa Stevens Colella, Eric Klopfer and Mitchel Resnick
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examples/githubcl-appspec.yaml view on Meta::CPAN
Powerful collaboration, code review, and code management for open source and private projects.
termsOfService: https://help.github.com/articles/github-terms-of-service/#b-api-terms
title: GitHub
version: v3
x-logo:
url: http://assets-cdn.github.com/images/modules/logos_page/GitHub-Mark.png
x-origin:
format: swagger
url: https://raw.githubusercontent.com/APIs-guru/unofficial_openapi_specs/master/github.com/v3/swagger.yaml
version: '2.0'
x-providerName: github.com
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lib/API/Instagram.pm view on Meta::CPAN
=for Pod::Coverage client_id client_secret grant_type no_cache redirect_uri response_type scope BUILD
=for HTML <a href="https://travis-ci.org/gabrielmad/API-Instagram"><img src="https://travis-ci.org/gabrielmad/API-Instagram.svg?branch=build%2Fmaster"></a>
=for HTML <a href='https://coveralls.io/r/gabrielmad/API-Instagram?branch=build%2Fmaster'><img src='https://coveralls.io/repos/gabrielmad/API-Instagram/badge.png?branch=build%2Fmaster' alt='Coverage Status' /></a>
=head1 VERSION
version 0.013
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t/00-load.t
t/01-api.t
t/manifest.t
t/pod-coverage.t
t/pod.t
t/test.png
LICENSE
META.json
META.yml
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applications/collector-test.pl view on Meta::CPAN
# Add a custom CDML text at the bottom right of the plot area as the logo
$c->addText($width - 3, 92, $APPLICATION . " @ " . $BUSINESS, "arial.ttf", 8, 0x999999, 6, 270);
$c->addText($width - 18, $hight - 21, "Interval: " . $interval . " min, " . $DEPARTMENT . " @ " . $BUSINESS . ", created on: " . scalar(localtime()) . ".", "arial.ttf", 8, 0x000000, 6, 0);
#output the chart
$c->makeChart("$dbiFilename.png");
return $rv;
}
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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lib/ASP4/StaticHandler.pm view on Meta::CPAN
my %types = (
swf => 'application/x-shockwave-flash',
xml => 'text/xml',
jpg => 'image/jpeg',
jpeg => 'image/jpeg',
png => 'image/png',
bmp => 'image/bmp',
gif => 'image/gif',
json => 'application/x-json',
css => 'text/css',
pdf => 'application/x-pdf',
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lib/ASP4x/Captcha/Imager.pm view on Meta::CPAN
$img->filter( type => 'gaussian', stddev => 1 );
}# end for()
# Render the image as PNG:
my $str = "";
$img->write(type=>'png', data => \$str)
or die $img->errstr;
$Response->Expires( -30 );
$Response->AddHeader( pragma => 'no-cache' );
$Response->SetHeader('content-type' => 'image/png');
$Response->ContentType( 'image/png' );
$Response->Write( $str );
}# end run()
sub generate_pair
lib/ASP4x/Captcha/Imager.pm view on Meta::CPAN
C<ASP4x::Captcha::Imager> uses L<Imager> to generate an image of a random string
of numbers and letters.
=head2 What Does the Captcha Image Look Like?
You can see an example in the example/example.png file included with this distribution.
=head2 Recommendations and Considerations
=over 4
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