OutfitAnyone includes try-on models and auxiliary models for virtual try-on scenarios, from quick image generation and detail refinement to partial replacement.
This document applies only to the China (Beijing) region. Use an API key from this region.
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Quick links: Online trial | Billing and throttling | Free quota |
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Related APIs: |
Model overview
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Type |
Service |
Model |
Core feature |
Scenarios |
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Try-on model |
aitryon |
Fast try-on image generation. |
High-speed generation with standard texture quality. |
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Try-on model |
OutfitAnyone-Plus API reference (Recommended) |
aitryon-plus |
Higher image definition, improved texture details, and better logo restoration. |
Slower generation speed, suitable for non-time-sensitive scenarios. |
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Auxiliary model |
aitryon-refiner |
Enhances texture, definition, and realism of try-on images. |
Refines try-on model outputs for higher quality. |
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Auxiliary model |
aitryon-parsing-v1 |
Segments clothing areas in images. |
Enables partial try-on and interactive features like product hotspots. |
Scenarios
Combine these APIs based on your needs. Common scenarios:
Scenario 1: Basic try-on
Use case: Quick result verification or high-speed image generation.
Steps:
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Prepare inputs: Model image and clothing image.
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Call try-on model: Call OutfitAnyone - Basic Edition or OutfitAnyone-Plus API reference with the two images.
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Get result: The API returns the try-on image.
Scenario 2: Refined try-on
Use case: High-quality output with enhanced detail and realism.
Steps:
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Call try-on model: Follow steps in Scenario 1: Basic try-on to generate a try-on image.
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Call image refinement: Call OutfitAnyone - Image Refinement with the basic try-on image and original inputs (model image and clothing image).
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Get result: The API returns the refined try-on image.
Scenario 3: Partial try-on
Use case: Replace part of the outfit (e.g., replace only the top, keep the original pants).
Steps:
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Extract clothing to keep: Call OutfitAnyone-Parsing with the original model image to extract the clothing item to keep (e.g., pants).
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Combine for try-on: Call OutfitAnyone - Basic Edition or OutfitAnyone-Plus API reference with the original model image, new top, and extracted pants image.
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Get result: The API returns a try-on image combining the new top and original pants.
Scenario 4: Obtaining clothing coordinates
Use case: Add product labels or implement interactive features like product hotspots.
Steps:
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Call image segmentation: Call OutfitAnyone-Parsing with any model image (real photo or OutfitAnyone-generated image).
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Get result: The API returns clothing area coordinates (bbox) and visualization. Use these coordinates for frontend interactive features like product hotspots.