{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"hf-space-humanaigc--outfitanyone","slug":"humanaigc--outfitanyone","name":"OutfitAnyone","type":"webapp","url":"https://huggingface.co/spaces/HumanAIGC/OutfitAnyone","page_url":"https://unfragile.ai/humanaigc--outfitanyone","categories":["automation"],"tags":["gradio","region:us"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"hf-space-humanaigc--outfitanyone__cap_0","uri":"capability://image.visual.virtual.try.on.clothing.transfer.with.pose.preservation","name":"virtual try-on clothing transfer with pose preservation","description":"Transfers clothing from a reference garment image onto a target person while preserving the target's pose, body shape, and spatial positioning. Uses diffusion-based image synthesis with pose-aware conditioning to warp and adapt clothing textures to match the target person's body geometry, implemented via a Gradio web interface that accepts image uploads and generates photorealistic outfit visualizations in real-time.","intents":["I want to see how a specific outfit looks on a different person without physically trying it on","I need to generate product mockups showing clothing on diverse body types and poses","I want to create fashion content showing the same garment across multiple models"],"best_for":["e-commerce platforms building virtual try-on features","fashion designers prototyping outfit combinations","content creators generating product photography at scale"],"limitations":["Requires clear, well-lit images of both the garment and target person for accurate transfer","May struggle with complex layered clothing, transparent fabrics, or extreme poses","Processing latency depends on HuggingFace Spaces compute allocation; free tier may have queue delays","Output quality degrades with occlusions or unusual body angles not well-represented in training data"],"requires":["Web browser with JavaScript enabled","Two image files (reference garment + target person) in JPEG/PNG format","Internet connection to access HuggingFace Spaces infrastructure","Images should be 512x768px or similar aspect ratio for optimal results"],"input_types":["image (reference garment photo)","image (target person photo)"],"output_types":["image (synthesized outfit visualization)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-humanaigc--outfitanyone__cap_1","uri":"capability://image.visual.multi.person.outfit.composition.from.reference.gallery","name":"multi-person outfit composition from reference gallery","description":"Enables users to select multiple reference garments from different source images and compose them onto a single target person, combining top, bottom, and accessory layers. The system uses sequential diffusion refinement to blend multiple clothing items while maintaining coherent styling and avoiding visual artifacts at garment boundaries, orchestrated through a Gradio interface that manages image upload workflows and layer composition.","intents":["I want to mix and match clothing pieces from different photos onto one person","I need to create outfit combinations showing how different tops pair with different bottoms","I want to generate styled looks combining multiple reference garments"],"best_for":["fashion stylists creating mood boards and outfit recommendations","retail platforms enabling outfit bundling and cross-product visualization","personal shopping apps showing coordinate suggestions"],"limitations":["Composition quality degrades with more than 3-4 garment layers due to diffusion refinement complexity","Requires manual segmentation or clear visual separation of clothing items in reference images","Color harmony and style coherence are not explicitly optimized; may produce visually jarring combinations","Processing time scales linearly with number of garment layers being composed"],"requires":["Web browser with modern JavaScript support","3-5 separate image files (one per garment piece + target person)","Images in JPEG/PNG format with clear clothing visibility","HuggingFace Spaces compute quota for sequential diffusion passes"],"input_types":["image (target person)","image (reference top garment)","image (reference bottom garment)","image (optional accessories)"],"output_types":["image (composite outfit visualization)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-humanaigc--outfitanyone__cap_2","uri":"capability://image.visual.batch.outfit.generation.with.style.consistency","name":"batch outfit generation with style consistency","description":"Processes multiple target person images in sequence, applying the same reference garment or outfit composition to each, with style consistency maintained across the batch through shared diffusion model state and conditioning parameters. The Gradio interface queues batch requests and generates outputs sequentially, enabling users to visualize how a single outfit looks across different people or poses without redefining the garment reference for each iteration.","intents":["I want to see how one outfit looks on 10 different models for a product catalog","I need to generate consistent styling across multiple lifestyle photos for a campaign","I want to apply the same virtual outfit to different body types to show inclusivity"],"best_for":["e-commerce platforms generating product photography across model diversity","marketing teams creating consistent campaign visuals","fashion brands demonstrating size/fit inclusivity"],"limitations":["Batch processing is sequential, not parallel; 10 images may take 2-5 minutes depending on queue","Style consistency is approximate; subtle variations in diffusion sampling may cause minor outfit variations across batch","Free HuggingFace Spaces tier may timeout on large batches (>20 images)","No built-in progress tracking or batch job persistence; page refresh loses queue state"],"requires":["Web browser with file upload capability","Batch of 5-20 target person images in JPEG/PNG format","One reference garment image or outfit composition","Patience for sequential processing; estimate 15-30 seconds per image"],"input_types":["image (reference garment/outfit)","image array (multiple target persons)"],"output_types":["image array (outfit applied to each target person)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-humanaigc--outfitanyone__cap_3","uri":"capability://image.visual.interactive.pose.guided.outfit.preview","name":"interactive pose-guided outfit preview","description":"Allows users to adjust or specify the target person's pose through interactive controls (e.g., pose keypoint selection or pose template selection) before outfit transfer, enabling outfit visualization across different body positions and angles. The system uses pose estimation and conditioning to guide the diffusion model, ensuring the transferred garment adapts to the specified pose rather than being locked to the original pose in the reference image.","intents":["I want to see how an outfit looks on a person in a sitting vs standing pose","I need to visualize clothing fit across different arm positions and angles","I want to generate outfit previews matching specific pose templates for consistency"],"best_for":["fashion apps enabling interactive outfit exploration","virtual fitting room systems requiring pose flexibility","content creators generating outfit variations across poses"],"limitations":["Pose adjustment is limited to templates or keypoint presets; free-form pose drawing is not supported","Extreme poses (e.g., lying down, contorted positions) may produce unrealistic garment draping","Pose conditioning adds ~500ms-1s latency per generation compared to fixed-pose transfer","Requires accurate pose estimation in the reference image; poor pose detection degrades output quality"],"requires":["Web browser with interactive UI support (canvas/SVG rendering)","Reference garment image and target person image","Pose estimation model loaded in browser or backend (adds ~100MB memory overhead)","JavaScript enabled for interactive pose adjustment controls"],"input_types":["image (reference garment)","image (target person)","pose specification (keypoints or template selection)"],"output_types":["image (outfit preview in specified pose)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-humanaigc--outfitanyone__cap_4","uri":"capability://automation.workflow.gradio.based.web.interface.with.real.time.preview","name":"gradio-based web interface with real-time preview","description":"Provides a Gradio-powered web UI hosted on HuggingFace Spaces that handles image uploads, parameter configuration, and real-time output preview without requiring local installation or API key management. The interface abstracts the underlying diffusion model complexity through intuitive form controls, image galleries, and progress indicators, enabling non-technical users to perform outfit transfer through a browser without command-line interaction.","intents":["I want to try virtual outfit transfer without installing software or managing API keys","I need a shareable demo link to show stakeholders outfit transfer capabilities","I want to experiment with outfit combinations without writing code"],"best_for":["non-technical users exploring virtual try-on capabilities","product managers and designers prototyping outfit features","teams sharing demos and gathering feedback on outfit transfer quality"],"limitations":["Gradio UI is stateless; refreshing the page loses all uploaded images and previous results","No built-in authentication or rate limiting; free tier may experience throttling under high traffic","File upload size limits (typically 10-50MB per image on HuggingFace Spaces free tier)","Gradio's reactive model can cause UI lag if diffusion generation takes >30 seconds","No persistent job history or result archival; outputs must be manually downloaded"],"requires":["Web browser (Chrome, Firefox, Safari, Edge)","Internet connection to HuggingFace Spaces","No API key or local setup required","Images in JPEG/PNG format under 50MB"],"input_types":["image (via file upload or drag-and-drop)","text (optional parameters like style guidance scale)"],"output_types":["image (preview in Gradio gallery)","downloadable image file"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":22,"verified":false,"data_access_risk":"low","permissions":["Web browser with JavaScript enabled","Two image files (reference garment + target person) in JPEG/PNG format","Internet connection to access HuggingFace Spaces infrastructure","Images should be 512x768px or similar aspect ratio for optimal results","Web browser with modern JavaScript support","3-5 separate image files (one per garment piece + target person)","Images in JPEG/PNG format with clear clothing visibility","HuggingFace Spaces compute quota for sequential diffusion passes","Web browser with file upload capability","Batch of 5-20 target person images in JPEG/PNG format"],"failure_modes":["Requires clear, well-lit images of both the garment and target person for accurate transfer","May struggle with complex layered clothing, transparent fabrics, or extreme poses","Processing latency depends on HuggingFace Spaces compute allocation; free tier may have queue delays","Output quality degrades with occlusions or unusual body angles not well-represented in training data","Composition quality degrades with more than 3-4 garment layers due to diffusion refinement complexity","Requires manual segmentation or clear visual separation of clothing items in reference images","Color harmony and style coherence are not explicitly optimized; may produce visually jarring combinations","Processing time scales linearly with number of garment layers being composed","Batch processing is sequential, not parallel; 10 images may take 2-5 minutes depending on queue","Style consistency is approximate; subtle variations in diffusion sampling may cause minor outfit variations across batch","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.2,"ecosystem":0.36,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.766Z","last_scraped_at":"2026-05-03T14:22:48.012Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=humanaigc--outfitanyone","compare_url":"https://unfragile.ai/compare?artifact=humanaigc--outfitanyone"}},"signature":"uYAgyQRXGCnXsvmQbvz5SgdEk33M109OUi64cR2xZSCAIpWyvd+xlLHk86R2mLMbI2o7H7/5J/xCYfOQwomrDA==","signedAt":"2026-06-22T22:12:58.483Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/humanaigc--outfitanyone","artifact":"https://unfragile.ai/humanaigc--outfitanyone","verify":"https://unfragile.ai/api/v1/verify?slug=humanaigc--outfitanyone","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}