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Stable Diffusion Depth2img


AI model preview image
The stable-diffusion-depth2img model is a machine learning model that can create variations of an image while preserving shape and depth. It uses a stable diffusion process to gradually transform an input image into different variants, allowing users to explore different possibilities without sacrificing the original structure and depth of the image. This model is useful for tasks such as image editing and generation, as it enables the creation of visually appealing and coherent variations of an image.

Use cases

This model can be used in various applications, such as photo editing software, where users can apply different variations to an image while maintaining its original shape and depth. It can also be used in virtual reality or augmented reality applications, where realistic and coherent variations of images are required. Additionally, this model can be applied in the field of computer graphics, enabling the generation of new images with desired variations while preserving the underlying structure and depth. Possible products or practical uses of this model could include an image editing software that allows users to easily explore different variations of their photos while maintaining their original quality, or a virtual reality application that seamlessly transforms the visual properties of objects in real-time without distorting their shape and depth.


Cost per run
Avg run time
Nvidia A100 (40GB) GPU

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Try it!

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Summary of this model and related resources.

Model NameStable Diffusion Depth2img
Create variations of an image while preserving shape and depth.
Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkView on Arxiv


How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?

Model Rank
Creator Rank


How much does it cost to run this model? How long, on average, does it take to complete a run?

Cost per Run$0.0184
Prediction HardwareNvidia A100 (40GB) GPU
Average Completion Time8 seconds