📄 Source: GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization.php
<?php
/*
* Copyright 2014 Google Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
namespace Google\Service\Aiplatform;
class GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization extends \Google\Model
{
/**
* Should not be used.
*/
public const COLOR_MAP_COLOR_MAP_UNSPECIFIED = 'COLOR_MAP_UNSPECIFIED';
/**
* Positive: green. Negative: pink.
*/
public const COLOR_MAP_PINK_GREEN = 'PINK_GREEN';
/**
* Viridis color map: A perceptually uniform color mapping which is easier to
* see by those with colorblindness and progresses from yellow to green to
* blue. Positive: yellow. Negative: blue.
*/
public const COLOR_MAP_VIRIDIS = 'VIRIDIS';
/**
* Positive: red. Negative: red.
*/
public const COLOR_MAP_RED = 'RED';
/**
* Positive: green. Negative: green.
*/
public const COLOR_MAP_GREEN = 'GREEN';
/**
* Positive: green. Negative: red.
*/
public const COLOR_MAP_RED_GREEN = 'RED_GREEN';
/**
* PiYG palette.
*/
public const COLOR_MAP_PINK_WHITE_GREEN = 'PINK_WHITE_GREEN';
/**
* Default value. This is the same as NONE.
*/
public const OVERLAY_TYPE_OVERLAY_TYPE_UNSPECIFIED = 'OVERLAY_TYPE_UNSPECIFIED';
/**
* No overlay.
*/
public const OVERLAY_TYPE_NONE = 'NONE';
/**
* The attributions are shown on top of the original image.
*/
public const OVERLAY_TYPE_ORIGINAL = 'ORIGINAL';
/**
* The attributions are shown on top of grayscaled version of the original
* image.
*/
public const OVERLAY_TYPE_GRAYSCALE = 'GRAYSCALE';
/**
* The attributions are used as a mask to reveal predictive parts of the image
* and hide the un-predictive parts.
*/
public const OVERLAY_TYPE_MASK_BLACK = 'MASK_BLACK';
/**
* Default value. This is the same as POSITIVE.
*/
public const POLARITY_POLARITY_UNSPECIFIED = 'POLARITY_UNSPECIFIED';
/**
* Highlights the pixels/outlines that were most influential to the model's
* prediction.
*/
public const POLARITY_POSITIVE = 'POSITIVE';
/**
* Setting polarity to negative highlights areas that does not lead to the
* models's current prediction.
*/
public const POLARITY_NEGATIVE = 'NEGATIVE';
/**
* Shows both positive and negative attributions.
*/
public const POLARITY_BOTH = 'BOTH';
/**
* Should not be used.
*/
public const TYPE_TYPE_UNSPECIFIED = 'TYPE_UNSPECIFIED';
/**
* Shows which pixel contributed to the image prediction.
*/
public const TYPE_PIXELS = 'PIXELS';
/**
* Shows which region contributed to the image prediction by outlining the
* region.
*/
public const TYPE_OUTLINES = 'OUTLINES';
/**
* Excludes attributions below the specified percentile, from the highlighted
* areas. Defaults to 62.
*
* @var float
*/
public $clipPercentLowerbound;
/**
* Excludes attributions above the specified percentile from the highlighted
* areas. Using the clip_percent_upperbound and clip_percent_lowerbound
* together can be useful for filtering out noise and making it easier to see
* areas of strong attribution. Defaults to 99.9.
*
* @var float
*/
public $clipPercentUpperbound;
/**
* The color scheme used for the highlighted areas. Defaults to PINK_GREEN for
* Integrated Gradients attribution, which shows positive attributions in
* green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which
* highlights the most influential regions in yellow and the least influential
* in blue.
*
* @var string
*/
public $colorMap;
/**
* How the original image is displayed in the visualization. Adjusting the
* overlay can help increase visual clarity if the original image makes it
* difficult to view the visualization. Defaults to NONE.
*
* @var string
*/
public $overlayType;
/**
* Whether to only highlight pixels with positive contributions, negative or
* both. Defaults to POSITIVE.
*
* @var string
*/
public $polarity;
/**
* Type of the image visualization. Only applicable to Integrated Gradients
* attribution. OUTLINES shows regions of attribution, while PIXELS shows per-
* pixel attribution. Defaults to OUTLINES.
*
* @var string
*/
public $type;
/**
* Excludes attributions below the specified percentile, from the highlighted
* areas. Defaults to 62.
*
* @param float $clipPercentLowerbound
*/
public function setClipPercentLowerbound($clipPercentLowerbound)
{
$this->clipPercentLowerbound = $clipPercentLowerbound;
}
/**
* @return float
*/
public function getClipPercentLowerbound()
{
return $this->clipPercentLowerbound;
}
/**
* Excludes attributions above the specified percentile from the highlighted
* areas. Using the clip_percent_upperbound and clip_percent_lowerbound
* together can be useful for filtering out noise and making it easier to see
* areas of strong attribution. Defaults to 99.9.
*
* @param float $clipPercentUpperbound
*/
public function setClipPercentUpperbound($clipPercentUpperbound)
{
$this->clipPercentUpperbound = $clipPercentUpperbound;
}
/**
* @return float
*/
public function getClipPercentUpperbound()
{
return $this->clipPercentUpperbound;
}
/**
* The color scheme used for the highlighted areas. Defaults to PINK_GREEN for
* Integrated Gradients attribution, which shows positive attributions in
* green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which
* highlights the most influential regions in yellow and the least influential
* in blue.
*
* Accepted values: COLOR_MAP_UNSPECIFIED, PINK_GREEN, VIRIDIS, RED, GREEN,
* RED_GREEN, PINK_WHITE_GREEN
*
* @param self::COLOR_MAP_* $colorMap
*/
public function setColorMap($colorMap)
{
$this->colorMap = $colorMap;
}
/**
* @return self::COLOR_MAP_*
*/
public function getColorMap()
{
return $this->colorMap;
}
/**
* How the original image is displayed in the visualization. Adjusting the
* overlay can help increase visual clarity if the original image makes it
* difficult to view the visualization. Defaults to NONE.
*
* Accepted values: OVERLAY_TYPE_UNSPECIFIED, NONE, ORIGINAL, GRAYSCALE,
* MASK_BLACK
*
* @param self::OVERLAY_TYPE_* $overlayType
*/
public function setOverlayType($overlayType)
{
$this->overlayType = $overlayType;
}
/**
* @return self::OVERLAY_TYPE_*
*/
public function getOverlayType()
{
return $this->overlayType;
}
/**
* Whether to only highlight pixels with positive contributions, negative or
* both. Defaults to POSITIVE.
*
* Accepted values: POLARITY_UNSPECIFIED, POSITIVE, NEGATIVE, BOTH
*
* @param self::POLARITY_* $polarity
*/
public function setPolarity($polarity)
{
$this->polarity = $polarity;
}
/**
* @return self::POLARITY_*
*/
public function getPolarity()
{
return $this->polarity;
}
/**
* Type of the image visualization. Only applicable to Integrated Gradients
* attribution. OUTLINES shows regions of attribution, while PIXELS shows per-
* pixel attribution. Defaults to OUTLINES.
*
* Accepted values: TYPE_UNSPECIFIED, PIXELS, OUTLINES
*
* @param self::TYPE_* $type
*/
public function setType($type)
{
$this->type = $type;
}
/**
* @return self::TYPE_*
*/
public function getType()
{
return $this->type;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization::class, 'Google_Service_Aiplatform_GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization');
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