{
"openapi": "3.0.0",
"info": {
"title": "AI Teeth Whitening",
"description": "# Overview\n**AI Teeth Whitening API**\n\nThe AI Teeth Whitening API provides an advanced, automated solution for enhancing smiles in photos. Using intelligent image processing, it brightens teeth naturally and accurately, creating polished, professional results within seconds.\n\n\n\n\n\n\n**How It Removes Yellow Teeth in Photos**\n\n**Smart Whitening** \nThe API automatically detects teeth and applies a natural-looking whitening effect without making the image appear artificial.\n\n**Adjustable Levels** \nA built-in adjustment feature allows users to control the degree of whitening, from a subtle enhancement to a more pronounced, camera-ready finish.\n\n\n\n**Key Features**\n\n**Quick and Easy Enhancement** \nAchieve a noticeably brighter smile in just a few seconds.\n\n**Accurate AI Detection** \nAdvanced detection ensures that only teeth are modified, maintaining a realistic and balanced appearance.\n\n**Adjustable Whitening Intensity** \nUsers can fine-tune the whitening strength to match their preferred style.\n\n**Natural Results with Advanced Algorithms**\n\nThe AI Teeth Whitening API uses sophisticated algorithms designed to identify teeth precisely and apply whitening effects that remain true to life. Users can refine the intensity to achieve a subtle, natural improvement, ensuring that the final result looks authentic and visually appealing.\n\n---\n\n## Integration Guide\n\n* Take a Selfie\n\n * Face the camera directly with proper lighting.\n * Use the JS Camera Kit to capture the photo.\n\n* Retrieve upload URLs and File IDs via ***/s2s/v2.0/file*** API\n\n Upload the following files using the upload URLs returned in the file API response:\n * Your selfie photo\n\n* Execute AI Task ***/s2s/v2.0/task/teeth-whiten***\n\n Run the AI task using file IDs or image URLs as the input source. Configure the effect parameters as desired.\n\n* Poll Task Status\n\n Use the returned **task\\_id** to monitor task progress. \n Poll **GET /s2s/v2.0/task/teeth-whiten/{task_id}** to check the engine's status. \n The task will remain in a **“running”** state until it is completed. No units are consumed while the task is running.\n\n\n\n* **Usage demonstration**\n\n\n\n\n\n\n\n## File Specs & Errors\n* Supported Formats & Dimensions\n\n|Type|Supported Dimensions|Supported File Size|Supported Formats|\n| ---- | ---- | ---- | ---- |\n|AI Teeth Whitening|Selfie Image:
* Long side ≤ 1920 px
* Short side ≥ 320 px |< 10MB|jpg/png|\n\n\n* Error Codes\n\n|Error Code|Description|\n| ---- | ---- |\n| error_exceed_max_image_size | If the longer side of an image exceeds 1920 pixels |\n|error_below_min_image_size|If your image is smaller than 320 pixels in width or height, it's too small to use|\n|error_face_position_invalid|Your face needs to be fully visible in the image, without any parts cut off|\n|error_face_position_too_small|The face in your photo is too small to analyze properly|\n|error_face_position_out_of_boundary|Your face is either too large or partially outside the edges of the photo|\n|error_insufficient_lighting|The lighting is too dim, which makes analysis difficult|\n|error_face_angle_invalid|Your face angle isn't quite right. For front-facing shots, keep your head within 10 degrees of straight. For side-facing shots, the angle should be more than 15 degrees|\n\n* Environment & Dependency\n\n| Sample Code Language / Tool | Recommended Runtime Versions |\n|---|---|\n| cURL | - bash >= 3.2 - curl >= 7.58 (modern TLS/HTTP support) - jq >= 1.6 (robust JSON parsing) |\n| Node.js (JavaScript) | Node >= 18 (for global fetch) |\n| JavaScript | - Chrome / Edge >= 80 - Firefox >= 74 - Safari >= 13.1 |\n| PHP | PHP >= 7.4 (for modern TLS/compat), ext-curl (recommended) or allow_url_fopen=On + ext-openssl, ext-json |\n| Python | Python >= 3.10 (for f-strings), requests >= 2.20.0 |\n| Java | Java 11+ (for HttpClient), Jackson Databind >= 2.12.0 |\n\n---\n\n## Unit Consumption\n\n| AI Feature | Unit Consumed |\n|---|---|\n| AI Teeth Whitening V1.0 | 1 |\n\n---\n",
"version": "",
"termsOfService": "https://www.makeupar.com/perfectbeauty/youcam/terms-of-service-api",
"contact": {
"email": "YouCamOnlineEditor_API@perfectcorp.com"
},
"license": {
"name": "Privacy policy",
"url": "https://www.makeupar.com/perfectbeauty/youcam/privacy-policy-api"
}
},
"servers": [
{
"url": "https://yce-api-01.makeupar.com"
}
],
"tags": [
{
"name": "V1.0",
"description": "Whitening teeth in photos using AI technology."
}
],
"paths": {
"/s2s/v2.0/task/teeth-whiten/pre-process": {
"post": {
"summary": "Run an AI Teeth Whiten detection task.",
"description": "Use the pre-process task when the source image may contain more than one valid target, or when your integration needs to explicitly choose which detected target receives the effect. For single-target images, pre-process can be skipped when the feature supports a default `index` value and your application does not need manual target selection.\n\nThe pre-process task detects candidate targets in the source image and returns their coordinates in `data.results.result`. Each item in the result array represents one detected target. Review the returned coordinates, map them to the intended face or region in the source image, and use that item's zero-based array index as the `index` value when creating the effect task.\n\nFor images with multiple detected faces or regions, do not rely on the default `index` value without checking the pre-process result. The effect is applied only to the target selected by `index`, so the integration must confirm the result item that corresponds to the intended target before running the effect task.\n\nThis task is asynchronous. After creating the task, handle completion with webhook if the feature supports it, or poll the corresponding pre-process status endpoint until `data.task_status` is `success` or `error`.\n",
"tags": [
"V1.0"
],
"security": [
{
"BearerAuthenticationV2": []
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"allOf": [
{
"$ref": "#/components/schemas/BasicRunTaskV2"
}
]
}
}
}
},
"responses": {
"200": {
"description": "Successful execution of the task",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/BasicRunTaskResponseV2"
}
}
}
},
"400": {
"description": "Failed execution of task",
"content": {
"application/json": {
"schema": {
"allOf": [
{
"$ref": "#/components/schemas/RunError"
}
]
}
}
}
},
"401": {
"$ref": "#/components/responses/InvalidApiKey"
},
"429": {
"$ref": "#/components/responses/TooManyRequests"
}
}
}
},
"/s2s/v2.0/task/teeth-whiten/pre-process/{task_id}": {
"get": {
"summary": "Check the status of a AI Teeth Whiten detection task.",
"tags": [
"V1.0"
],
"security": [
{
"BearerAuthenticationV2": []
}
],
"parameters": [
{
"name": "task_id",
"in": "path",
"required": true,
"schema": {
"type": "string",
"example": "grH0CvsgXuAIHLUzD0V1Ol34hoet3R1tvdbtiVHrDb6_UqCLKIejAIajwxrhOAfe"
},
"description": "ID of task to check"
}
],
"responses": {
"200": {
"description": "Successful check of the task status",
"content": {
"application/json": {
"schema": {
"allOf": [
{
"$ref": "#/components/schemas/TaskStatusResponsePreProcessNoUrlBase"
},
{
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"results": {
"type": "object",
"properties": {
"timed": {
"type": "number"
},
"result": {
"type": "array",
"items": {
"type": "object",
"properties": {
"left": {
"type": "number"
},
"top": {
"type": "number"
},
"width": {
"type": "number"
},
"height": {
"type": "number"
}
}
}
}
}
}
}
}
}
}
]
}
}
}
},
"400": {
"$ref": "#/components/responses/InvalidTaskId"
},
"401": {
"$ref": "#/components/responses/InvalidApiKey"
},
"500": {
"$ref": "#/components/responses/TaskTimeout"
}
}
}
},
"/s2s/v2.0/task/teeth-whiten": {
"post": {
"summary": "Run an AI Teeth Whiten task.",
"description": "AI tasks are asynchronous. Prefer webhook-based completion handling when the feature supports webhooks. Configure your webhook endpoint, verify webhook signatures, and use the received `task_id` to query the task result after a `success` or `error` notification. See the [webhook integration guide](/develop/webhook.md) for setup and verification details.\n\nIf webhooks are not supported for the feature, or if your integration cannot use webhooks, implement polling. After starting an AI task, keep polling the task status endpoint at the given `polling_interval` until the task status is either `success` or `error`.\n\nDo not stop polling a running task for longer than the allowed polling window. If the task is not polled in time, the task may expire; a later status check can return `InvalidTaskId` even if processing finished, and the consumed units may still be charged.\n",
"tags": [
"V1.0"
],
"security": [
{
"BearerAuthenticationV2": []
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"allOf": [
{
"$ref": "#/components/schemas/BasicRunTaskV2"
},
{
"type": "object",
"required": [
"version",
"effect"
],
"properties": {
"version": {
"type": "string",
"enum": [
"1.0"
]
},
"index": {
"type": "integer",
"example": 0,
"default": 0,
"description": "Zero-based index of the target object to apply the effect to. For multi-objects images, run the pre-process task first, inspect the object coordinates in `data.results.result`, and pass the index of the selected object here.\n\nThe pre-processing step analyzes the input image to identify all detectable objects before any effect is applied. It runs a detection task that returns structured data for each object, including a list of bounding box coordinates. The position of each entry in this list serves as its zero-based index, which is then used to specify the target object for the effect.\n\nThis information is returned in a structured format, commonly under `data.results.result`.\nBy running this step first, you can:\n * Understand how many objects are present in the image\n * Inspect their positions and sizes\n * Select the correct target object by its index\n\nAlways run the pre-processing step for images with multiple objects.\nReview `data.results.result` to identify objects and their indices.\nUse the corresponding zero-based index to select the correct target."
},
"effect": {
"type": "object",
"required": [
"whitening_intensity"
],
"properties": {
"whitening_intensity": {
"type": "integer",
"maximum": 100,
"minimum": 0
},
"skin_smooth_strength": {
"type": "integer",
"minimum": 0,
"maximum": 100,
"default": 50
},
"skin_smooth_color_intensity": {
"type": "integer",
"minimum": 0,
"maximum": 100,
"default": 50
}
}
}
}
}
]
}
}
}
},
"responses": {
"200": {
"description": "Successful execution of the task",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/BasicRunTaskResponseV2"
}
}
}
},
"400": {
"description": "Failed execution of task",
"content": {
"application/json": {
"schema": {
"allOf": [
{
"$ref": "#/components/schemas/RunError"
}
]
}
}
}
},
"401": {
"$ref": "#/components/responses/InvalidApiKey"
},
"429": {
"$ref": "#/components/responses/TooManyRequests"
}
}
}
},
"/s2s/v2.0/task/teeth-whiten/{task_id}": {
"get": {
"summary": "Check the status of a AI Teeth Whiten task.",
"tags": [
"V1.0"
],
"security": [
{
"BearerAuthenticationV2": []
}
],
"parameters": [
{
"name": "task_id",
"in": "path",
"required": true,
"schema": {
"type": "string",
"example": "grH0CvsgXuAIHLUzD0V1Ol34hoet3R1tvdbtiVHrDb6_UqCLKIejAIajwxrhOAfe"
},
"description": "ID of task to check"
}
],
"responses": {
"200": {
"description": "Successful check of the task status",
"content": {
"application/json": {
"schema": {
"allOf": [
{
"$ref": "#/components/schemas/TaskStatusResponseV2"
},
{
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"results": {
"type": "object",
"properties": {
"timed": {
"type": "number"
},
"timed_apply": {
"type": "number"
}
}
}
}
}
}
}
]
}
}
}
},
"400": {
"$ref": "#/components/responses/InvalidTaskId"
},
"401": {
"$ref": "#/components/responses/InvalidApiKey"
},
"500": {
"$ref": "#/components/responses/TaskTimeout"
}
}
}
}
},
"components": {
"securitySchemes": {
"BearerAuthenticationV2": {
"type": "http",
"scheme": "bearer",
"description": "Use the standard 'Bearer authentication'. Put your 'API Key' in header: \\`Authorization:Bearer YOUR_API_KEY\\`. Notice that there is ' ' a space between 'Bearer' and the 'YOUR_API_KEY'."
}
},
"schemas": {
"BasicRunTaskV2SrcFileUrl": {
"type": "object",
"required": [
"src_file_url"
],
"properties": {
"src_file_url": {
"type": "string",
"description": "Url of the file to run task. The url should be publicly accessible.",
"example": "https://example.com/selfie.jpg"
}
}
},
"BasicRunTaskV2SrcFileId": {
"type": "object",
"required": [
"src_file_id"
],
"properties": {
"src_file_id": {
"type": "string",
"description": "ID of file to run task. File ID from upload file API.",
"example": "pfNK5PuRe0MrwLHcGA3DOmB1ahwfXTbYHjv+KoBIxbE="
}
}
},
"BasicRunTaskV2": {
"title": "BasicRunTaskV2",
"anyOf": [
{
"title": "Run task with src file url",
"allOf": [
{
"$ref": "#/components/schemas/BasicRunTaskV2SrcFileUrl"
}
]
},
{
"title": "Run task with src file ID",
"allOf": [
{
"$ref": "#/components/schemas/BasicRunTaskV2SrcFileId"
}
]
}
]
},
"BasicRunTaskResponseV2": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"description": "Response status",
"example": 200
},
"data": {
"type": "object",
"properties": {
"task_id": {
"type": "string",
"description": "ID of this task. Task result is valid to query by this ID for 24 hours.",
"example": "grH0CvsgXuAIHLUzD0V1Ol34hoet3R1tvdbtiVHrDb6_UqCLKIejAIajwxrhOAfe"
}
}
}
}
},
"RunError": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"description": "Response status",
"example": 400
},
"error": {
"type": "string",
"description": "Error message",
"example": "The operation could not be completed"
},
"error_code": {
"type": "string",
"enum": [
"InvalidParameters",
"CreditInsufficiency",
"InvalidStyleGroup",
"InvalidStyle",
"BadRequest"
],
"description": "Error code:\n * InvalidParameters - Invalid request parameters\n * CreditInsufficiency - Insufficient unit to run\n * BadRequest - Unexpected request parameter\n * InvalidStyleGroup - Invalid style group id\n * InvalidStyle - Invalid style id\n"
}
}
},
"EngineErrorCode": {
"type": "string",
"nullable": true,
"enum": [
"error_exceed_max_image_size",
"exceed_max_filesize",
"invalid_parameter",
"error_download_image",
"error_download_mask",
"error_decode_image",
"error_decode_mask",
"error_nsfw_content_detected",
"error_no_face",
"error_pose",
"error_face_parsing",
"error_inference",
"exceed_nsfw_retry_limits",
"error_upload",
"unknown_internal_error"
],
"description": "Errors:\n- \\`error_exceed_max_image_size\\` - Input image size exceeds the maximum limit\n- \\`exceed_max_filesize\\` - Input file size exceeds the maximum limit\n- \\`invalid_parameter\\` - Invalid parameter value\n- \\`error_download_image\\` - Download source image error\n- \\`error_download_mask\\` - Download mask image error\n- \\`error_decode_image\\` - Decode source image error\n- \\`error_decode_mask\\` - Decode mask image error\n- \\`error_nsfw_content_detected\\` - NSFW content detected in source image\n- \\`error_no_face\\` - No face detected on source image\n- \\`error_pose\\` - Failed to detect pose on source image\n- \\`error_face_parsing\\` - Failed to do face segmentation on source image\n- \\`error_inference\\` - Inference pipeline error\n- \\`exceed_nsfw_retry_limits\\` - Exceed the retry limits to avoid generated NSFW image\n- \\`error_upload\\` - Upload result image error\n- \\`unknown_internal_error\\` - Others\n"
},
"TaskStatusResponsePreProcessNoUrlBase": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"description": "Response status",
"example": 200
},
"data": {
"type": "object",
"properties": {
"task_status": {
"type": "string",
"enum": [
"running",
"success",
"error"
],
"description": "Status of this task"
},
"error": {
"$ref": "#/components/schemas/EngineErrorCode"
},
"error_message": {
"type": "string",
"description": "Detailed description of error"
}
}
}
}
},
"TaskStatusResponseBodySingleUrlResultsV2": {
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "URL to download this result. Valid for 2 hours",
"example": "https://example.com/sample-result-url"
}
}
},
"TaskStatusResponseV2": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"description": "Response status",
"example": 200
},
"data": {
"type": "object",
"properties": {
"task_status": {
"type": "string",
"enum": [
"running",
"success",
"error"
],
"description": "Status of this task"
},
"error": {
"$ref": "#/components/schemas/EngineErrorCode"
},
"error_message": {
"type": "string",
"description": "Detailed description of error"
},
"results": null
}
}
},
"$ref": "#/components/schemas/TaskStatusResponseBodySingleUrlResultsV2"
}
},
"responses": {
"InvalidApiKey": {
"description": "Invalid or missing API key",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"example": 401,
"description": "Response status"
},
"error": {
"type": "string",
"example": "Invalid API key"
}
}
}
}
}
},
"TooManyRequests": {
"description": "Too many requests",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"example": 429,
"description": "Response status"
},
"error": {
"type": "string",
"example": "Too many requests"
}
}
}
}
}
},
"InvalidTaskId": {
"description": "Invalid task ID",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"example": 400,
"description": "Response status"
},
"error": {
"type": "string",
"example": "Invalid task ID"
}
}
}
}
}
},
"TaskTimeout": {
"description": "Task execution timeout",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"status": {
"type": "integer",
"example": 500,
"description": "Response status"
},
"error": {
"type": "string",
"example": "Task execution timed out"
}
}
}
}
}
}
}
}
}