> ## Documentation Index > Fetch the complete documentation index at: https://gcore.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Create AI CM:soft_nudity task > This algorithm allows to identify explicit nudity and partial nudity too (including the presence of male and female faces and other uncovered body parts) in a video. Generic info about all capabilities and limits see in the generic ["Content Moderation"](/docs/api-reference/streaming/ai/create-ai-task) method. **What is Soft nudity detection?** This method is often used to analyze UGC to determine whether videos can be published to all users, or to prohibit publication due to offensive and inappropriate content. Objects that can be detected: - `ANUS_COVERED` - `ANUS_EXPOSED` - `ARMPITS_COVERED` - `ARMPITS_EXPOSED` - `BELLY_COVERED` - `BELLY_EXPOSED` - `BUTTOCKS_COVERED` - `BUTTOCKS_EXPOSED` - `FACE_FEMALE` - `FACE_MALE` - `FEET_COVERED` - `FEET_EXPOSED` - `FEMALE_BREAST_COVERED` - `FEMALE_BREAST_EXPOSED` - `FEMALE_GENITALIA_COVERED` - `FEMALE_GENITALIA_EXPOSED` - `MALE_BREAST_EXPOSED` - `MALE_GENITALIA_EXPOSED` This method allows you to identify faces and other body parts. Used to find complex combinations of what is happening in a video. Please note that the number of objects is more than in the hard-nudity-detection. The method is slower. ![AI Content Moderation: hard nudity detection visual example](https://demo-files.gvideo.io/apidocs/soft_nudity_detection.gif) **How to use?** The information is returned with the video frame number where it was found and probability of the detected object. Nudity detection is done using AI, so for each object a probability percentage is applied; objects with a probability of at least 30% are included in the response. Video processing speed is approximately 1:5. Example of detected nudity or body parts: ``` { "nudity_detected": true, "detection_results": [ "FACE_FEMALE", "BELLY_COVERED" ] "frames": [ { "confidence": 0.82, "frame_number": 1, "label": "BELLY_COVERED" },... ] } ``` Example response when nudity or body parts were not found: ``` { "nudity_detected": false, "detection_results": [] "frames": [] } ``` There is no universal recipe under which a video can be considered unacceptable, since different services host different types of videos for different audiences: adult content, children's content, educational content, etc. You can determine the probability threshold at which you consider a video inappropriate. The easiest option is to run several of your videos and analyze the resulting probability coefficient. Sometimes a detected object at the beginning of the video immediately makes it clear that there is no need to further analyze the video. For such cases, you can use stop tags. Use parameter "stop_objects" to specify comma separated stop tags. It is also possible to specify % probability threshold value, above which the stop tag will be triggered. ``` { "url": "...", "stop_objects": "BELLY_COVERED:0.9,FEMALE_GENITALIA_COVERED" } ``` Please note that the API only provides a set of data (json) about the objects found, so no video is generated. The demo video video (above ^) was specially created based on json from the API for visual demonstration and better perception of the possibilities. ## OpenAPI ````yaml /api-reference/services_documented/streaming_api.yaml post /streaming/ai/tasks#cm_soft_nudity openapi: 3.1.0 info: title: Gcore OpenAPI – Streaming API description: >- This OpenAPI is an aggregated OpenAPI specification that unifies all Gcore products into a single file. It covers Cloud, CDN, DNS, WAAP, DDoS Protection, Object Storage, Streaming, and FastEdge services. version: '2026-05-15T06:37:28.230198+00:00' servers: - url: https://api.gcore.com security: - APIKey: [] tags: - name: AI x-displayName: AI - name: Broadcasts x-displayName: Broadcasts - name: Directories x-displayName: Directories - name: Overlays x-displayName: Overlays - name: Players x-displayName: Players - name: Playlists x-displayName: Playlists - name: QualitySets x-displayName: QualitySets - name: Restreams x-displayName: Restreams - name: Streaming Statistics x-displayName: Statistics - name: Streams x-displayName: Streams - name: Subtitles x-displayName: Subtitles - name: Videos x-displayName: Videos paths: /streaming/ai/tasks#cm_soft_nudity: post: tags: - AI summary: Create AI CM:soft_nudity task description: >- This algorithm allows to identify explicit nudity and partial nudity too (including the presence of male and female faces and other uncovered body parts) in a video. Generic info about all capabilities and limits see in the generic ["Content Moderation"](/docs/api-reference/streaming/ai/create-ai-task) method. **What is Soft nudity detection?** This method is often used to analyze UGC to determine whether videos can be published to all users, or to prohibit publication due to offensive and inappropriate content. Objects that can be detected: - `ANUS_COVERED` - `ANUS_EXPOSED` - `ARMPITS_COVERED` - `ARMPITS_EXPOSED` - `BELLY_COVERED` - `BELLY_EXPOSED` - `BUTTOCKS_COVERED` - `BUTTOCKS_EXPOSED` - `FACE_FEMALE` - `FACE_MALE` - `FEET_COVERED` - `FEET_EXPOSED` - `FEMALE_BREAST_COVERED` - `FEMALE_BREAST_EXPOSED` - `FEMALE_GENITALIA_COVERED` - `FEMALE_GENITALIA_EXPOSED` - `MALE_BREAST_EXPOSED` - `MALE_GENITALIA_EXPOSED` This method allows you to identify faces and other body parts. Used to find complex combinations of what is happening in a video. Please note that the number of objects is more than in the hard-nudity-detection. The method is slower. ![AI Content Moderation: hard nudity detection visual example](https://demo-files.gvideo.io/apidocs/soft_nudity_detection.gif) **How to use?** The information is returned with the video frame number where it was found and probability of the detected object. Nudity detection is done using AI, so for each object a probability percentage is applied; objects with a probability of at least 30% are included in the response. Video processing speed is approximately 1:5. Example of detected nudity or body parts: ``` { "nudity_detected": true, "detection_results": [ "FACE_FEMALE", "BELLY_COVERED" ] "frames": [ { "confidence": 0.82, "frame_number": 1, "label": "BELLY_COVERED" },... ] } ``` Example response when nudity or body parts were not found: ``` { "nudity_detected": false, "detection_results": [] "frames": [] } ``` There is no universal recipe under which a video can be considered unacceptable, since different services host different types of videos for different audiences: adult content, children's content, educational content, etc. You can determine the probability threshold at which you consider a video inappropriate. The easiest option is to run several of your videos and analyze the resulting probability coefficient. Sometimes a detected object at the beginning of the video immediately makes it clear that there is no need to further analyze the video. For such cases, you can use stop tags. Use parameter "stop_objects" to specify comma separated stop tags. It is also possible to specify % probability threshold value, above which the stop tag will be triggered. ``` { "url": "...", "stop_objects": "BELLY_COVERED:0.9,FEMALE_GENITALIA_COVERED" } ``` Please note that the API only provides a set of data (json) about the objects found, so no video is generated. The demo video video (above ^) was specially created based on json from the API for visual demonstration and better perception of the possibilities. operationId: post_ai_contentmoderation_softnudity parameters: [] requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/ai_contentmoderation_softnudity' responses: '201': description: >- Response returns ID of the created AI task. Using this AI task ID, you can check the status and get the video processing result. Look at GET /ai/results method. content: application/json: schema: $ref: '#/components/schemas/ai_post_response' '400': description: |- Bad request: - "url" is not specified, - Queue limit reached (100), try later, - etc content: application/json: schema: $ref: '#/components/schemas/streaming_error' '422': description: >- This is advanced functionality; to enable it, contact your manager or the Support Team. content: application/json: schema: $ref: '#/components/schemas/upgraderequired' components: schemas: ai_contentmoderation_softnudity: allOf: - $ref: '#/components/schemas/ai_contentmoderation_general' required: - category properties: category: type: string enum: - soft_nudity description: AI content moderation with "soft_nudity" algorithm stop_objects: type: string enum: - ANUS_COVERED - ANUS_EXPOSED - ARMPITS_COVERED - ARMPITS_EXPOSED - BELLY_COVERED - BELLY_EXPOSED - BUTTOCKS_COVERED - BUTTOCKS_EXPOSED - FACE_FEMALE - FACE_MALE - FEET_COVERED - FEET_EXPOSED - FEMALE_BREAST_COVERED - FEMALE_BREAST_EXPOSED - FEMALE_GENITALIA_COVERED - FEMALE_GENITALIA_EXPOSED - MALE_BREAST_EXPOSED - MALE_GENITALIA_EXPOSED description: >- Comma separated objects, and probabilities, that will cause the processing to stop immediatelly after finding. example: url: https://demo-files.gvideo.io/ai_demo_subtitles_nudity_detection.mp4 task_name: content-moderation category: soft_nudity stop_objects: BELLY_COVERED:0.9,FEMALE_GENITALIA_COVERED ai_post_response: type: object required: - task_id properties: task_id: type: string format: uuid description: >- ID of the created AI task, from which you can get the execution result example: task_id: aafe70c6-0000-0000-0000-327b65f7670f streaming_error: type: object properties: error: type: string description: Text message with description of error. example: error: Queue limit reached (100), try later. upgraderequired: type: object properties: error: type: string description: >- This is advanced functionality; to enable it, contact your manager or support service. example: error: Feature is disabled. Contact support to enable. ai_contentmoderation_general: type: object required: - url - task_name properties: task_name: type: string description: Name of the task to be performed enum: - content-moderation url: type: string description: >- URL to the MP4 file to analyse. File must be publicly accessible via HTTP/HTTPS. category: type: string description: >- Model for analysis (content-moderation only). Determines what exactly needs to be found in the video. enum: - sport - nsfw - hard_nudity - soft_nudity client_user_id: type: string maxLength: 256 default: null description: >- Meta parameter, designed to store your own identifier. Can be used by you to tag requests from different end-users. It is not used in any way in video processing. client_entity_data: type: string maxLength: 4096 default: null description: >- Meta parameter, designed to store your own extra information about a video entity: video source, video id, etc. It is not used in any way in video processing. For example, if an AI-task was created automatically when you uploaded a video with the AI auto-processing option (nudity detection, etc), then the ID of the associated video for which the task was performed will be explicitly indicated here. example: url: https://demo-files.gvideo.io/ai_demo_subtitles_nudity_detection.mp4 task_name: content-moderation category: nsfw securitySchemes: APIKey: description: >- API key for authentication. Make sure to include the word `apikey`, followed by a single space and then your token. Example: `apikey 1234$abcdef` type: apiKey in: header name: Authorization ````