Moderating content - Amazon Rekognition

Moderating content

You can use Amazon Rekognition to detect content that is inappropriate, unwanted, or offensive. You can use Rekognition moderation APIs in social media, broadcast media, advertising, and e-commerce situations to create a safer user experience, provide brand safety assurances to advertisers, and comply with local and global regulations.

Today, many companies rely entirely on human moderators to review third-party or user-generated content, while others simply react to user complaints to take down offensive or inappropriate images, ads, or videos. However, human moderators alone cannot scale to meet these needs at sufficient quality or speed, which leads to a poor user experience, high costs to achieve scale, or even a loss of brand reputation. By using Rekognition for image and video moderation, human moderators can review a much smaller set of content, typically 1-5% of the total volume, already flagged by machine learning. This enables them to focus on more valuable activities and still achieve comprehensive moderation coverage at a fraction of their existing cost. To set up human workforces and perform human review tasks, you can use Amazon Augmented AI, which is already integrated with Rekognition.

You can enhance the accuracy of the moderation deep learning model with the Custom Moderation feature. With Custom Moderation, you train a custom moderation adapter by uploading your images and annotating these images. The trained adapter can then be provided to the DetectModerationLabels operation to to enhance its performance on your images. See Enhancing accuracy with Custom Moderation for more information.

Using the image and video moderation APIs

In the Amazon Rekognition Image API, you can detect inappropriate, unwanted, or offensive content synchronously using DetectModerationLabels and asynchronously using StartMediaAnalysisJob and GetMediaAnalysisJob operations. You can use the Amazon Rekognition Video API to detect such content asynchronously by using the StartContentModeration and GetContentModeration operations.

Label Categories

Amazon Rekognition uses a three-level hierarchical taxonomy to label categories of inappropriate, unwanted, or offensive content. Each label with Taxonomy Level 1 (L1) has a number of Taxonomy Level 2 labels (L2), and some Taxonomy Level 2 labels may have Taxonomy Level 3 labels (L3). This allows a hierarchical classification of the content.

For each detected moderation label, the API also returns the TaxonomyLevel, which contains the level (1, 2, or 3) that the label belongs to. For example, an image may be labeled in accordance with the following categorization:

L1: Non-Explicit Nudity of Intimate parts and Kissing, L2: Non-Explicit Nudity, L3: Implied Nudity.


We recommend using L1 or L2 categories to moderate your content and using L3 categories only to remove specific concepts that you do not want to moderate (i.e. to detect content that you may not want to categorize as inappropriate, unwanted, or offensive content based on your moderation policy).

The following table shows the relationships between the category levels and the possible labels for each level. To download a list of the moderation labels, click here.

Top-Level Category (L1) Second-Level Category (L2) Third-Level Category (L3) Definitions
Explicit Explicit Nudity Exposed Male Genitalia Human male genitalia, including the penis (whether erect or flaccid), the scrotum, and any discernible pubic hair. This term is applicable in contexts involving sexual activity or any visual content where male genitals are displayed either completely or partially.
Exposed Female Genitalia External parts of the female reproductive system, encompassing the vulva, vagina, and any observable pubic hair. This term is applicable in scenarios involving sexual activity or any visual content where these aspects of female anatomy are displayed either completely or partially.
Exposed Buttocks or Anus Human buttocks or anus, including instances where the buttocks are nude or when they are discernible through sheer clothing. The definition specifically applies to situations where the buttocks or anus are directly and completely visible, excluding scenarios where any form of underwear or clothing provides complete or partial coverage.
Exposed Female Nipple Human female nipples, including fully visible and partially visible aerola (area surrounding the nipples) and nipples.
Explicit Sexual Activity N/A Depiction of actual or simulated sexual acts which encompasses human sexual intercourse, oral sex, as well as male genital stimulation and female genital stimulation by other body parts and objects. The term also includes ejaculation or vaginal fluids on body parts and erotic practices or roleplaying involving bondage, discipline, dominance and submission, and sadomasochism.
Sex Toys N/A Objects or devices used for sexual stimulation or pleasure, e.g., dildo, vibrator, butt plug, beats, etc.
Non-Explicit Nudity of Intimate parts and Kissing Non-Explicit Nudity Bare Back Human posterior part where the majority of the skin is visible from the neck to the end of the spine. This term does not apply when the individual's back is partially or fully occluded.
Exposed Male Nipple Human male nipples, including partially visible nipples.
Partially Exposed Buttocks Partially exposed human buttocks. This term includes a partially visible region of the buttocks or butt cheeks due to short clothes, or partially visible top portion of the anal cleft. The term does not apply to cases where the buttocks is fully nude.
Partially Exposed Female Breast Partially exposed human female breast where one a portion of the female's breast is visible or uncovered while not revealing the entire breast. This term applies when the region of the inner breast fold is visible or when the lower breast crease is visible with nipple fully covered or occluded.
Implied Nudity An individual who is nude, either topless or bottomless, but with intimate parts such as buttocks, nipples, or genitalia covered, occluded, or not fully visible.
Obstructed Intimate Parts Obstructed Female Nipple Visual depiction of a situation in which a female's nipples is covered by opaque clothing or coverings, but their shapes are clearly visible.
Obstructed Male Genitalia Visual depiction of a situation in which a male's genitalia or penis is covered by opaque clothing or coverings, but its shape is clearly visible. This term applies when the obstructed genitalia in the image is in close-up.
Kissing on the Lips N/A Depiction of one person's lips making contact with another person's lips.
Swimwear or Underwear Female Swimwear or Underwear N/A Human clothing for female swimwear (e.g., one-piece swimsuits, bikinis, tankinis, etc.) and female underwear (e.g., bras, panties, briefs, lingerie, thongs, etc.)
Male Swimwear or Underwear N/A Human clothing for male swimwear (e.g., swim trunks, boardshorts, swim briefs, etc.) and male underwear (e.g., briefs, boxers, etc.)
Violence Weapons N/A Instruments or devices used to cause harm or damage to living beings, structures, or systems. This includes firearms (e.g., guns, rifles, machine gunes, etc.), sharp weapons (e.g., swords, knives, etc.), explosives and ammunition (e.g., missile, bombs, bullets, etc.).
Graphic Violence Weapon Violence The use of weapons to cause harm, damage, injury, or death to oneself, other individuals, or properties.
Physical Violence The act of causing harm to other individuals or property (e.g., hitting, fighting, pulling hair, etc.) or other act of violence involving crowd or multiple individuals.
Self-Harm The act of causing harm to oneself, often by cutting body parts such as arms or legs, where cuts are typically visible.
Blood & Gore Visual representation of violence on a person, a group of individuals, or animals, involving open wounds, bloodshed, and mutilated body parts.
Explosions and Blasts Depiction of a violent and destructive burst of intense flames with thick smoke or dust and smoke erupting from the ground.
Visually Disturbing Death and Emaciation Emaciated Bodies Human bodies that are extremely thin and undernourished with severe physical wasting and depletion of muscle and fat tissue.
Corpses Human corpses in the form of mutilated bodies, hanging corpses, or skeletons.
Crashes Air Crash Incidents of air vehicles, such as airplanes, helicopters, or other flying vehicles, resulting in damage, injury, or death. This term applies when parts of the air vehicles are visible.
Drugs & Tobacco Products Pills Small, solid, often round or oval-shaped tables or capsules. This term applies to pills presented as standalones, in a bottle, or a transparent packet and does not apply to a visual depiction of a person taking pills.
Drugs & Tobacco Paraphernalia & Use Smoking The act of inhaling, exhaling, and lighting up burning substances including cigarettes, cigars, e-cigarettes, hookah, or joint.
Alcohol Alcohol Use Drinking The act of drinking alcoholic beverages from bottles or glasses of alcohol or liquor.
Alcoholic Beverages N/A Close up of one or multiple bottles of alcohol or liquor, glasses or mugs with alcohol or liquor, and glasses or mugs with alcohol or liquor held by an individual. This term does not apply to an individual drinking from bottles or glasses of alcohol or liquor.
Rude Gestures Middle Finger N/A Visual depiction of a hand gesture with middle finger is extended upward while the other fingers are folded down.
Gambling N/A N/A The act of participating in games of chance for a chance to win a prize in casinos, e.g., playing cards, blackjacks, roulette, slot machines at casinos, etc.
Hate Symbols Nazi Party N/A Visual depiction of symbols, flags, or gestures associated with Nazi Party.
White Supremacy N/A Visual depiction of symbols or clothings associated with Ku Klux Klan (KKK) and images with confederate flags.
Extremist N/A Images containing extremist and terrorist group flags.

Not every label in the L2 category has a supported label in the L3 category. Additionally, L3 labels under “Products” and “Drug and Tobacco Paraphernalia and Use” L2 labels aren’t exhaustive. These L2 labels cover concepts beyond the mentioned L3 labels and in such cases, only L2 labels is returned in the API response.

You determine the suitability of content for your application. For example, images of a suggestive nature might be acceptable, but images containing nudity might not. To filter images, use the ModerationLabel labels array that's returned by DetectModerationLabels (images) and by GetContentModeration (videos).

Content type

The API can also identify animated or illustrated content type, and the content type is returned as part of the response:

  • Animated content includes video game and animation (e.g., cartoon, comics, manga, anime).

  • Illustrated content includes drawing, painting, and sketches.


You can set the confidence threshold that Amazon Rekognition uses to detect inappropriate content by specifying the MinConfidence input parameter. Labels aren't returned for inappropriate content that is detected with a lower confidence than MinConfidence.

Specifying a value for MinConfidence that is less than 50% is likely to return a high number of false-positive results (i.e. higher recall, lower precision). On the other hand, specifying a MinConfidence above 50% is likely to return a lower number of false-positive results (i.e. lower recall, higher precision). If you don't specify a value for MinConfidence, Amazon Rekognition returns labels for inappropriate content that is detected with at least 50% confidence.

The ModerationLabel array contains labels in the preceding categories, and an estimated confidence in the accuracy of the recognized content. A top-level label is returned along with any second-level labels that were identified. For example, Amazon Rekognition might return “Explicit Nudity” with a high confidence score as a top-level label. That might be enough for your filtering needs. However, if it's necessary, you can use the confidence score of a second-level label (such as "Graphic Male Nudity") to obtain more granular filtering. For an example, see Detecting inappropriate images.


Amazon Rekognition Image and Amazon Rekognition Video both return the version of the moderation detection model that is used to detect inappropriate content (ModerationModelVersion).

Sorting and Aggregating

When retrieving results with GetContentModeration, you can sort and aggregate your results.

Sort order — The array of labels returned is sorted by time. To sort by label, specify NAME in the SortByinput parameter for GetContentModeration. If the label appears multiple times in the video, there will be multiples instances of the ModerationLabel element.

Label information — The ModerationLabels array element contains a ModerationLabel object, which in turn contains the label name and the confidence Amazon Rekognition has in the accuracy of the detected label. Timestamp is the time the ModerationLabel was detected, defined as the number of milliseconds elapsed since the start of the video. For results aggregated by video SEGMENTS, the StartTimestampMillis, EndTimestampMillis, and DurationMillis structures are returned, which define the start time, end time, and duration of a segment respectively.

Aggregation — Specifies how results are aggregated when returned. The default is to aggregate by TIMESTAMPS. You can also choose to aggregate by SEGMENTS, which aggregates results over a time window. Only labels detected during the segments are returned.

Custom Moderation adapter statuses

Custom Moderation adapters can be in one of the following statuses: TRAINING_IN_PROGRESS, TRAINING_COMPLETED, TRAINING_FAILED, DELETING, DEPRECATED, or EXPIRED. For a full explanation of these adapter statuses, see Managing adapters.


Amazon Rekognition isn't an authority on, and doesn't in any way claim to be an exhaustive filter of, inappropriate or offensive content. Additionally, the image and video moderation APIs don't detect whether an image includes illegal content, such as CSAM.