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Fashion ApparelTop 10 Best AI Product Model Photo Generator of 2026
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Google Imagen
High-fidelity photoreal rendering from text prompts with strong control of materials and lighting
Built for teams generating realistic AI product model photos and iterating prompts fast.
OpenAI GPT-Image
Text-to-image generation tuned for cohesive product visuals from detailed prompts
Built for teams needing fast product image ideation with iterative prompt refinement.
Canva Magic Media
Magic Media text-to-image generation inside Canva with immediate design placement
Built for marketing teams creating synthetic product model visuals for campaigns.
Comparison Table
This comparison table evaluates AI product photo generator tools such as Google Imagen, OpenAI GPT-Image, Adobe Firefly, Canva Magic Media, GetIMG, and other popular options. You’ll see how each model performs for product-focused image generation across key factors like input control, output quality, edit workflows, and typical use cases.
| # | Tool | Category | Overall | Features | Ease of Use | Value |
|---|---|---|---|---|---|---|
| 1 | Google Imagen Generates high-quality product and model images from text prompts using Google’s Imagen image generation models. | text-to-image | 9.1/10 | 9.0/10 | 8.2/10 | 8.4/10 |
| 2 | OpenAI GPT-Image Creates and edits product and model images from prompts and reference images using OpenAI’s image generation tooling. | prompt-to-image | 8.3/10 | 8.8/10 | 7.9/10 | 7.6/10 |
| 3 | Adobe Firefly Generates and edits product and apparel images with text prompts and reference inputs in Adobe Firefly. | creative suite | 7.8/10 | 8.2/10 | 8.0/10 | 6.9/10 |
| 4 | Canva Magic Media Produces product and model imagery from prompts and enables quick image edits inside Canva’s design workflow. | design-integrated | 7.4/10 | 7.6/10 | 8.6/10 | 7.2/10 |
| 5 | GetIMG Creates product photos and model images for e-commerce using AI with guided input and exportable results. | ecommerce-focused | 7.4/10 | 7.2/10 | 7.8/10 | 7.0/10 |
| 6 | Ecommerce-Photo AI Generates product and model photo variants for online storefronts from product photos and prompts. | product-variant | 7.2/10 | 7.6/10 | 7.4/10 | 6.8/10 |
| 7 | Zyro AI Product Images Generates product images and variations for storefront use with AI tools embedded in Zyro’s marketing pages. | storefront-generation | 7.1/10 | 7.0/10 | 8.2/10 | 6.9/10 |
| 8 | Pixelcut Creates model and product photo-style outputs using AI for background replacement and image transformation. | ecommerce-imaging | 7.6/10 | 8.1/10 | 8.3/10 | 7.0/10 |
| 9 | Clipdrop Uses AI image generation and editing tools to create realistic product and model visuals from uploaded images. | image-editing | 7.3/10 | 7.6/10 | 8.3/10 | 7.0/10 |
| 10 | Fotor AI Image Generator Generates product and model imagery from text prompts and supports AI-based image edits in the Fotor editor. | all-in-one | 7.2/10 | 7.0/10 | 8.4/10 | 7.4/10 |
Generates high-quality product and model images from text prompts using Google’s Imagen image generation models.
Creates and edits product and model images from prompts and reference images using OpenAI’s image generation tooling.
Generates and edits product and apparel images with text prompts and reference inputs in Adobe Firefly.
Produces product and model imagery from prompts and enables quick image edits inside Canva’s design workflow.
Creates product photos and model images for e-commerce using AI with guided input and exportable results.
Generates product and model photo variants for online storefronts from product photos and prompts.
Generates product images and variations for storefront use with AI tools embedded in Zyro’s marketing pages.
Creates model and product photo-style outputs using AI for background replacement and image transformation.
Uses AI image generation and editing tools to create realistic product and model visuals from uploaded images.
Generates product and model imagery from text prompts and supports AI-based image edits in the Fotor editor.
Google Imagen
text-to-imageGenerates high-quality product and model images from text prompts using Google’s Imagen image generation models.
High-fidelity photoreal rendering from text prompts with strong control of materials and lighting
Google Imagen is a research-grade image generation model that produces highly realistic product-focused visuals with strong prompt following. Imagen supports text-to-image synthesis and can generate consistent studio-style scenes suited to AI product model photography use cases. The workflow integrates with Google tools for rapid iteration and quality filtering, which helps reduce manual editing. Its main limitation for production pipelines is that it is not a turn-key e-commerce photo studio with built-in catalog management and automatic storefront-ready exports.
Pros
- Produces photoreal product images with strong lighting and material fidelity
- Prompt control yields usable variations for model photos without extensive retouching
- Fits rapid experimentation workflows with quick iteration and quality selection
Cons
- Not a dedicated product photo studio with catalog and variant management
- Batch production and consistent multi-view sets require additional workflow engineering
- Higher output quality can increase iteration time when prompts need tuning
Best For
Teams generating realistic AI product model photos and iterating prompts fast
OpenAI GPT-Image
prompt-to-imageCreates and edits product and model images from prompts and reference images using OpenAI’s image generation tooling.
Text-to-image generation tuned for cohesive product visuals from detailed prompts
OpenAI GPT-Image stands out for generating high-fidelity product-focused images directly from text prompts. You can create marketing-style visuals such as isolated products, lifestyle scenes, and variant concepts using consistent prompt guidance. The model supports iterative refinement by adjusting wording and constraints to steer composition, lighting, and style. For production pipelines, it pairs well with workflows that automate prompt generation and asset management.
Pros
- Strong prompt adherence for product composition and style direction
- Good image quality for marketing and catalog style mockups
- Iterative prompt refinement helps converge on usable variants
Cons
- Less consistent for strict brand packaging details across many iterations
- Production workflows often require engineering and prompt tooling
- Image set output and cost efficiency can be limiting for bulk generation
Best For
Teams needing fast product image ideation with iterative prompt refinement
Adobe Firefly
creative suiteGenerates and edits product and apparel images with text prompts and reference inputs in Adobe Firefly.
Content credentials for AI-generated images in supported outputs
Adobe Firefly stands out because it is designed by Adobe for creative workflows that connect directly to Adobe tools. It can generate realistic product-style images from text prompts and can use reference images to guide composition and style. You can iterate quickly with prompt refinement and variation generation for model photo outputs. It also provides content credentials to help label AI-generated images in supported contexts.
Pros
- Strong text-to-image results for studio-like product photo aesthetics
- Reference-image guidance improves consistency across model photo iterations
- Fast variation generation supports rapid concept-to-selection workflows
- Integration with Adobe creative ecosystem streamlines downstream editing
- Content credentials labeling helps track AI-generated outputs
Cons
- Less reliable for strict, repeating poses and exact SKU details
- Model attire and branding text can drift across iterations
- Reference guidance can still alter lighting and background unexpectedly
- Value drops for high-volume generation without clear usage planning
Best For
Marketing teams creating diverse product model photo concepts without a full studio
Canva Magic Media
design-integratedProduces product and model imagery from prompts and enables quick image edits inside Canva’s design workflow.
Magic Media text-to-image generation inside Canva with immediate design placement
Canva Magic Media stands out by combining AI media generation with Canva’s mainstream design workflow for product photography assets. It can generate synthetic imagery from text prompts and lets you place results into product layouts, ads, and catalogs. You can use common Canva editing controls after generation, including cropping, background adjustments, and brand-style reuse across designs. The workflow is strongest for marketers who need fast visual iterations rather than controlled studio-grade model pipelines.
Pros
- Fast text-to-image generation integrated directly into Canva editor
- Works well inside existing product ad, listing, and catalog templates
- Easy post-editing for cropping, backgrounds, and layout composition
- Brand kit and reusable styles help keep generated assets consistent
Cons
- Limited control compared with dedicated product photo generation tools
- Harder to enforce repeatable model identity across many images
- Prompting for strict product angles and lighting can require retries
- Generated outputs may need cleanup for e-commerce grade accuracy
Best For
Marketing teams creating synthetic product model visuals for campaigns
GetIMG
ecommerce-focusedCreates product photos and model images for e-commerce using AI with guided input and exportable results.
Prompt-guided generation of consistent product model photo variations from a reference image
GetIMG focuses on generating product model photos from uploaded images, which makes it useful for e-commerce photo workflows. It supports creating consistent variations of a model image for different product shots, with customization driven by prompt inputs. The workflow is geared toward marketing and catalog use where you need many similar visuals quickly. It still requires careful prompting and image selection to avoid unnatural hands, mismatched lighting, or background artifacts.
Pros
- Product-focused outputs that fit e-commerce catalog photo needs
- Fast generation for multiple model photo variations from one starting point
- Prompt-driven control for scene, style, and product presentation
- Works well for teams needing repeatable image look across listings
Cons
- Quality depends heavily on input image and prompt specificity
- Background and lighting mismatches require manual cleanup or retries
- Hands and fine details can degrade on complex poses
- Limited advanced control compared with dedicated creative workflows
Best For
E-commerce teams producing consistent product model images at scale
Ecommerce-Photo AI
product-variantGenerates product and model photo variants for online storefronts from product photos and prompts.
Product model photo generation from your existing ecommerce images
Ecommerce-Photo AI specializes in generating product model photography from ecommerce assets using AI image generation. It focuses on converting product photos into consistent lifestyle and model-style images for catalog and ad use. The workflow centers on creating multiple variants of a product model look while keeping the product appearance recognizable. It is positioned for teams that need faster visual merchandising output without full studio production.
Pros
- Product-first generation that keeps the original item recognizable
- Rapid creation of multiple model-style image variants
- Built for ecommerce use cases like listings and ad creative
Cons
- Less suitable for fully custom scenes beyond ecommerce styling
- Model and background consistency can vary across a batch
- Value depends on how many variations you need per product
Best For
Ecommerce teams producing lifestyle model images without studio shoots
Zyro AI Product Images
storefront-generationGenerates product images and variations for storefront use with AI tools embedded in Zyro’s marketing pages.
Prompt-driven product model photo generation designed for ecommerce creatives
Zyro AI Product Images distinguishes itself by combining image generation for product photography with quick storefront-style asset creation inside a simple website builder workflow. You can generate product model photos by entering prompts and selecting style direction, then download results for use in listings and marketing creatives. The tool supports iterative refinement through prompt edits and multiple output variations, which helps narrow toward consistent product presentation. It is best suited for teams that need fast visual drafts rather than studio-grade control over lighting, pose, and background matching.
Pros
- Fast prompt-based generation for product model photo drafts
- Simple workflow that fits into Zyro website and storefront use
- Multiple variations help converge on usable marketing images
Cons
- Limited controls for exact pose, hand placement, and anatomy consistency
- Background and lighting alignment can require several iterations
- Fewer advanced customization options than dedicated generative photo tools
Best For
Ecommerce teams needing quick AI model photos for listings and ads
Pixelcut
ecommerce-imagingCreates model and product photo-style outputs using AI for background replacement and image transformation.
Product background and scene replacement with model-aware compositing
Pixelcut focuses on generating realistic product and model photo variations from a single input image, with strong background and scene replacement for eCommerce workflows. It emphasizes cutout-style edits and quick model-centric outputs that let you preview multiple listing-ready compositions. The generator is most useful when you need consistent product presentation across sizes, angles, or studio-style settings rather than highly bespoke fashion direction. It generally trades deep art-direction controls for faster iteration and straightforward results for store catalogs.
Pros
- Fast model and product image generation for listing-ready variations
- Strong background replacement for studio and lifestyle scene swaps
- Good cutout and compositing tools for clean product presentation
Cons
- Less control than dedicated fashion retouching tools
- Results can require cleanup for complex hands and clothing edges
- Higher costs add up for large catalog volumes
Best For
Ecommerce teams generating consistent model product images for catalogs
Clipdrop
image-editingUses AI image generation and editing tools to create realistic product and model visuals from uploaded images.
Background Replacement with product cutouts to generate model-style product scenes from your photos
Clipdrop stands out for fast, browser-based image generation workflows focused on realistic product and model visuals. It supports generative background replacement, object removal, and photo-to-photo transformations that help turn a base product photo into a shoot-ready model scene. The tool also includes tools for enhancing cutouts and managing consistent product presentation across variations. Clipdrop is strongest when you already have product images and need quick AI-assisted scene creation rather than a full studio pipeline.
Pros
- Browser workflow enables quick iteration without setting up a local pipeline
- Background replacement creates believable model product scenes from simple inputs
- Object removal and cutout tools speed up cleanup for e-commerce-ready imagery
Cons
- Limited control for consistent multi-image model identity across large sets
- Product-spec accuracy like exact color matching can require manual touch-ups
- Fewer automation options than dedicated e-commerce creative suites
Best For
E-commerce teams needing quick AI model scene variants from existing product photos
Fotor AI Image Generator
all-in-oneGenerates product and model imagery from text prompts and supports AI-based image edits in the Fotor editor.
Prompt-based image generation with built-in background and style adjustments
Fotor AI Image Generator stands out with a single, web-based workflow that combines AI image creation and basic photo editing tools. It supports prompt-driven generation of product-style images, including variations, background changes, and style tuning for marketing visuals. The generator also includes common finishing tools like retouching and templates, which helps turn a first render into a usable asset. Output quality is strong for general product mockups, but fine control over lighting, angles, and brand-specific consistency is more limited than specialist model generators.
Pros
- Fast prompt-to-image workflow for product-style visuals
- Built-in editing tools for background and quick retouching
- Style and variation controls speed up iteration for mockups
- Web interface reduces setup and tool integration effort
Cons
- Limited precision for camera angle and studio lighting consistency
- Brand-specific product likeness consistency can drift across generations
- Fewer advanced controls than dedicated e-commerce model pipelines
- Details like labels and small text are unreliable
Best For
Small teams generating marketing product mockups without complex pipelines
Conclusion
After evaluating 10 fashion apparel, Google Imagen stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right AI Product Model Photo Generator
This buyer’s guide helps you choose an AI Product Model Photo Generator by mapping real tool capabilities to specific production needs like photoreal materials, repeatable model-style sets, and fast ecommerce variations. It covers Google Imagen, OpenAI GPT-Image, Adobe Firefly, Canva Magic Media, GetIMG, Ecommerce-Photo AI, Zyro AI Product Images, Pixelcut, Clipdrop, and Fotor AI Image Generator.
What Is AI Product Model Photo Generator?
An AI Product Model Photo Generator creates product-focused model photography images from text prompts or from your existing product photos. It solves the need to produce studio-like product-and-model visuals for catalog pages, ads, and storefronts without running full photoshoots. Some tools generate from prompts alone like Google Imagen and OpenAI GPT-Image. Others convert existing product images into model scenes using background replacement and cutouts like Clipdrop and Ecommerce-Photo AI.
Key Features to Look For
The right feature mix determines whether you get ecommerce-ready consistency or you spend extra cycles on retouching and re-prompting.
Photoreal product material and lighting control from prompts
Google Imagen generates photoreal product images with strong lighting and material fidelity so your model photos look like real studio captures. OpenAI GPT-Image also follows detailed prompts closely for cohesive product visuals, which helps when you need consistent surfaces across variations.
Cohesive product visuals from detailed prompt constraints
OpenAI GPT-Image is tuned for creating cohesive product visuals from detailed prompts so you can steer composition and style with iterative refinement. Google Imagen supports rapid prompt iteration with quality filtering so teams can converge on usable model photo directions quickly.
Reference-image guidance to improve iteration consistency
Adobe Firefly uses reference images to guide composition and style across model photo iterations, which helps keep outputs closer to the look you want. GetIMG and Ecommerce-Photo AI both use input product images as the anchor for generating consistent model-style variants.
Background replacement and cutout workflows for model scene creation
Clipdrop uses background replacement with product cutouts so you can turn a base product photo into a shoot-ready model scene. Pixelcut focuses on model and product compositing for listing-ready variations, which is useful when you need fast studio and lifestyle swaps.
Built-in editor tools for immediate finishing and placement
Canva Magic Media generates images inside the Canva design workflow so you can place renders into ads and catalog layouts right after generation. Fotor AI Image Generator combines prompt-driven image creation with basic retouching and background tools so you can finalize mockups without switching apps.
Ecommerce-first output behavior that keeps the product recognizable
Ecommerce-Photo AI is built around converting ecommerce assets into lifestyle and model-style images while keeping the original item recognizable. GetIMG emphasizes product-focused outputs for ecommerce catalog photo needs, which supports producing many similar visuals with fewer creative detours.
How to Choose the Right AI Product Model Photo Generator
Match the tool’s input style and consistency strengths to your asset workflow and your required level of model-set repeatability.
Choose your input workflow: text-only or product-photo conversion
Pick text-to-image tools like Google Imagen when you want to generate studio-style model photography from prompts and refine lighting and materials by iterating wording. Pick photo-conversion tools like Clipdrop or Ecommerce-Photo AI when you already have product images and want AI to create model scenes from those inputs.
Decide how strict you need brand- and SKU-accuracy across many images
If you need strong photoreal rendering and stable material behavior for product surfaces, choose Google Imagen. If you need cohesive product composition from detailed prompts for fast ideation, OpenAI GPT-Image helps, but strict repeating packaging details can drift across many iterations.
Select the tool that best matches your consistency strategy for multi-variant sets
If you plan to generate many variations and you want prompt control to reduce manual retouching, Google Imagen is a fit because it provides usable variations with strong lighting and material fidelity. If your process starts from one reference and you need guided consistency, GetIMG and Ecommerce-Photo AI are built around producing consistent product model photo variations using your starting assets.
Plan for scene control gaps like hands, anatomy, and exact pose matching
For strict pose and anatomy repeatability, recognize that Adobe Firefly and Canva Magic Media can drift on repeating poses and exact SKU details, which can force more retries. For image generation from reference photos, GetIMG and Zyro AI Product Images can require extra work on hands and fine details, so build selection and cleanup steps into your workflow.
Pick the tool that fits your downstream production system
If you need to place outputs directly into marketing designs, Canva Magic Media connects generation with layout workflows in Canva. If you want a web-based browser workflow for quick transformations and cutouts, Clipdrop reduces setup friction compared with local pipelines, while Fotor AI Image Generator adds finishing tools for background changes and quick retouching.
Who Needs AI Product Model Photo Generator?
These tools target teams that need faster ecommerce merchandising and marketing visuals without the time cost of full studio production for every variant.
Teams generating realistic AI product model photos and iterating prompts fast
Google Imagen is a strong match because it produces photoreal product images with strong control of materials and lighting and supports rapid prompt iteration with quality selection. OpenAI GPT-Image also fits teams that refine composition and style through iterative prompt wording for product-focused visuals.
Ecommerce teams producing consistent product model images at scale from a reference
GetIMG is built for e-commerce workflows that produce consistent product model photo variations from an uploaded reference image. Ecommerce-Photo AI also supports turning ecommerce assets into lifestyle and model-style variants while keeping the product recognizable.
Ecommerce teams that already have product photos and need fast model scene variants
Clipdrop is ideal when you want quick browser-based background replacement and product cutouts to generate model-style scenes from your photos. Pixelcut is a fit for generating listing-ready compositions with strong background and scene replacement using model-aware compositing.
Marketing teams creating synthetic product model visuals inside design workflows
Canva Magic Media suits marketers who need generation inside Canva so they can immediately use results in product layouts and ads with cropping and background adjustments. Adobe Firefly supports reference-guided iterations and adds content credentials labeling in supported outputs for tracking AI-generated images.
Common Mistakes to Avoid
The most common failures come from choosing a tool that cannot support your consistency level or from skipping the cleanup and selection steps needed for ecommerce-grade outputs.
Assuming prompt generation alone will handle repeatable multi-view sets
Google Imagen can produce strong material fidelity, but it is not a turn-key product photo studio with catalog and variant management, so batch multi-view sets need extra workflow engineering. OpenAI GPT-Image can generate high-fidelity product visuals, but production workflows require engineering and prompt tooling to manage bulk generation effectively.
Over-relying on AI to keep exact packaging details and brand text stable
Adobe Firefly can drift on model attire and branding text across iterations, which can force additional correction for strict brand packaging requirements. Fotor AI Image Generator and Canva Magic Media can also drift on brand-specific product likeness and struggle with reliable small text like labels.
Ignoring the reality that hands and fine details often degrade
GetIMG can produce consistent product variations from reference inputs, but hands and fine details can degrade on complex poses. Zyro AI Product Images and Pixelcut also can require cleanup for complex hands and clothing edges.
Skipping background and cutout finishing for listing-grade images
Clipdrop and Pixelcut can generate model scenes through background replacement and compositing, but complex edges and fine product accuracy can still require manual touch-ups. Ecommerce-Photo AI keeps the product recognizable, but model and background consistency can vary across a batch, so you need a selection step.
How We Selected and Ranked These Tools
We evaluated each AI Product Model Photo Generator by overall performance, feature depth, ease of use, and value across the specific workflows people use for product model photography. We prioritized tools that deliver photoreal product images and usable variation control, because those reduce retouching cycles for model-like ecommerce visuals. Google Imagen separated itself by combining high-fidelity photoreal rendering from text prompts with strong control of materials and lighting, which makes generated model photo directions more directly usable. Tools lower in the list often trade away deep studio-grade control for faster iteration or simpler design placement, which can increase cleanup and re-prompting time for strict consistency needs.
Frequently Asked Questions About AI Product Model Photo Generator
Which tool is best for generating photoreal studio-style product model photos from text prompts?
Google Imagen is built for research-grade, prompt-following image generation with strong control of materials and lighting, which fits studio-style product model visuals. OpenAI GPT-Image also produces high-fidelity product-focused images, but Imagen’s prompt-to-photoreal workflow is a better fit for teams focused on studio realism.
Do any generators let you keep the product recognizable by using your existing product photo as input?
GetIMG generates product model photos from uploaded images and then creates consistent variations driven by prompt inputs. Ecommerce-Photo AI and Clipdrop both center on transforming existing ecommerce images into lifestyle and model-style scenes while preserving product identity.
What’s the fastest workflow if you want to go from a single render to many listing-ready variations?
Pixelcut focuses on generating realistic product and model photo variations from a single input image, with scene replacement aimed at ecommerce speed. Canva Magic Media also accelerates iteration by generating synthetic imagery from prompts inside Canva, then letting you place outputs directly into ads and product layouts.
Which option is strongest when you need consistent model-looking backgrounds and cutouts for catalog use?
Clipdrop emphasizes generative background replacement and cutout enhancement so you can turn a base product photo into shoot-ready model scenes. Pixelcut is also designed for consistent catalog presentation through model-aware compositing and quick background or scene swaps.
Can I guide generation using reference images to keep style and composition consistent across a set?
Adobe Firefly supports using reference images to guide composition and style during product image generation. OpenAI GPT-Image achieves consistency primarily through iterative prompt refinement, while Firefly is more reference-driven for style matching.
Which tool is best if you need the output embedded into an existing marketing design workflow?
Canva Magic Media generates images from prompts and then places results into Canva design workflows for catalogs and ads. Fotor AI Image Generator similarly combines generation with basic photo editing so you can retouch and apply templates without switching tools.
What tool is most suitable for teams that want ecommerce-focused model shots without full studio production?
Ecommerce-Photo AI is positioned specifically for converting product photos into consistent lifestyle and model-style images for catalog and ad use. Zyro AI Product Images pairs prompt-driven model photo generation with quick storefront-style asset creation inside a website builder workflow.
Why might AI outputs show artifacts like mismatched lighting or unnatural anatomy in model shots?
GetIMG and Ecommerce-Photo AI both rely on prompt inputs and image selection to avoid artifacts like unnatural hands, mismatched lighting, or background glitches. Pixelcut and Clipdrop can reduce some issues through compositing and scene replacement, but prompt constraints still matter for coherence.
Which tool provides built-in labeling support for AI-generated content in supported contexts?
Adobe Firefly includes content credentials to help label AI-generated images when supported by the output pipeline. Other tools like Google Imagen and OpenAI GPT-Image focus more on image generation performance than on credential labeling features.
Tools reviewed
Referenced in the comparison table and product reviews above.
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