IDM VTON

Best-in-class clothing virtual try on in the wild

Playground

Try the model in real time below.

idm-ip.png selected

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idm-viton-dress.png selected

You can drop your own file here

Click or Drag-n-Drop

You can drop your own file here

output image


Examples

Check out what others have created with IDM VTON
Example preview
steps: 30seed: 42

API

If you're looking for an API, you can choose from your desired programming language.

POST
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 import requests import base64 # Use this function to convert an image file from the filesystem to base64 def image_file_to_base64(image_path): with open(image_path, 'rb') as f: image_data = f.read() return base64.b64encode(image_data).decode('utf-8') # Use this function to fetch an image from a URL and convert it to base64 def image_url_to_base64(image_url): response = requests.get(image_url) image_data = response.content return base64.b64encode(image_data).decode('utf-8') api_key = "YOUR_API_KEY" url = "https://api.segmind.com/v1/idm-vton" # Request payload data = { "crop": False, "seed": 42, "steps": 30, "category": "upper_body", "force_dc": False, "human_img": "https://segmind-sd-models.s3.amazonaws.com/display_images/idm-ip.png", "garm_img": "https://segmind-sd-models.s3.amazonaws.com/display_images/idm-viton-dress.png", "mask_only": False, "garment_des": "Green colour semi Formal Blazer" } headers = {'x-api-key': api_key} response = requests.post(url, json=data, headers=headers) print(response.content) # The response is the generated image
RESPONSE
image/jpeg
HTTP Response Codes
200 - OKImage Generated
401 - UnauthorizedUser authentication failed
404 - Not FoundThe requested URL does not exist
405 - Method Not AllowedThe requested HTTP method is not allowed
406 - Not AcceptableNot enough credits
500 - Server ErrorServer had some issue with processing

Attributes


cropbool ( default: 1 )

Use cropping? (check this if your image is not 3:4)


seedint ( default: 42 )


stepsint ( default: 30 )

min : 1,

max : 40


categoryenum:str ( default: upper_body )

An enumeration.

Allowed values:


force_dcbool ( default: 1 )

Use the DressCode version of IDM-VTON (this is default false, except if category=dresses)


human_imgstr *

Model, if this is not 3:4 check crop


garm_imgstr *

Garment, should match the category, can be a product image or even a photo of someone


mask_imgstr ( default: 1 )

Mask image, optional (but faster)


mask_onlybool ( default: 1 )

Return only the mask


garment_desstr ( default: Green colour semi Formal Blazer )

Description of garment e.g. Short Sleeve Round Neck T-shirt

To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.


Pricing

Serverless Pricing

Buy credits that can be used anywhere on Segmind

$ 0.0038 /per second

Dedicated Cloud Pricing

For enterprise costs and dedicated endpoints

$ 0.0007 - $ 0.0031 /per second
FEATURES

PixelFlow allows you to use all these features

Unlock the full potential of generative AI with Segmind. Create stunning visuals and innovative designs with total creative control. Take advantage of powerful development tools to automate processes and models, elevating your creative workflow.

Segmented Creation Workflow

Gain greater control by dividing the creative process into distinct steps, refining each phase.

Customized Output

Customize at various stages, from initial generation to final adjustments, ensuring tailored creative outputs.

Layering Different Models

Integrate and utilize multiple models simultaneously, producing complex and polished creative results.

Workflow APIs

Deploy Pixelflows as APIs quickly, without server setup, ensuring scalability and efficiency.

IDM Viton

IDM Viton is cutting-edge solution for authentic virtual try-on experiences. It can handle a wide variety of garments and adapt to different body types, ensuring a seamless and inclusive virtual try-on session.

IDM Viton is currently considered the best-in-class virtual try-on model, utilizes an innovative two-stream conditional diffusion model. It uses two different modules to encode the semantics of garment image. Given the base UNet of the diffusion model, the high-level semantics extracted from a visual encoder are fused to the cross-attention layer, and then the low-level features extracted from parallel UNet are fused to the self-attention layer. This approach allows IDM-VTON to provide highly realistic and authentic virtual try-on experiences.

lDM VTON License

The IDM VTON model is licensed under the Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International Public License. This license allows for the free use, modification, and distribution of the software for non-commercial purposes only, provided that the original copyright notice and disclaimer are included in all copies or substantial portions of the software. However, it does not permit the sharing of adapted material. The license also does not permit the use of the name of the license holder or the names of its contributors to endorse or promote products derived from this software without specific prior written permission. Furthermore, the license is irrevocable, meaning once granted, it cannot be taken back.

F.A.Q.

Frequently Asked Questions

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