Rossjillian
Rank:Average Model Cost: $0.0041
Number of Runs: 13,698,340
Models by this creator
controlnet
The ControlNet model is a diffusion-based model that generates images from text descriptions. It uses a two-step process to first generate a semantic layout from the text and then synthesizes the image based on the layout. The model is trained on a large dataset of paired text and image examples to learn the relationship between text and visual content. It allows for fine-grained control over the image generation process by conditioning the synthesis on specific attributes or features mentioned in the text. ControlNet can be used in various applications such as image generation from captions or enhancing existing images with specific features described in text.
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6.9M
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controlnet
ControlNet is a type of diffusion model used in image generation tasks, specifically in the Text-to-Image domain. It aims to control the generation process by obtaining additional supervision from a given textual description. By incorporating this textual information, ControlNet produces more accurate and controllable image generations. The model receives both a textual description and a random noise vector as input and generates a corresponding image output, aligning it with the given description more effectively. The ControlNet model helps improve the quality and control of text-based image generation tasks.
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controlnet_2-1
controlnet_2-1
ControlNet with SD 2.1 is an Image-to-Image AI model that can edit and enhance images based on provided inputs. It takes an image URL and a set of parameters including scale, steps, prompts, image structure, number of samples, thresholds, and image resolution. The prompts determine how the image is processed - for quality, detail, and specific features. It returns an enhanced image based on these specifications. It can be used, for example, to transform an image into a depiction of "a modernist house in a nice landscape" with specified quality and detail expectations.
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11.7K
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controlnet_2-1
controlnet_2-1
The controlnet_2-1 model is a text-to-image transformer that utilizes inputs such as scale, steps, prompts, structure, samples, threshold levels, and image resolution to generate a specified image. The primary input is the base image, supplemented with additional parameters defining attributes such as quality, features, and structural details. It then produces a URL link to the newly generated image as its output. This model is being particularly used for creating detailed depictions of given prompts, even allowing users to determine the level of detail and quality.
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11.2K
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controlnet_1-1
controlnet_1-1
The model, controlnet_1-1, is an image-to-image model, primarily used for converting or transforming input images based on specific prompts and parameters provided by users. It receives a variety of inputs, including an image URL, the scale and steps for processing, and several prompts to guide the transformation process. The prompts describe the desired quality of the output, undesirable features to avoid, and the overall structure of the output. The model also takes input parameters such as the number of samples, image resolution, as well as low and high threshold settings. Upon processing, the model outputs a URL to the transformed image. The model is updated nightly in this release.
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7.9K
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rankiqa
Rankiqa is a model that is designed to provide image quality scores. It takes an image as input and generates a score that represents the quality of the image. This can be useful in various applications, such as image classification, image search, or content moderation, where determining the quality of an image is important. Overall, Rankiqa helps in assessing and ranking the quality of images.
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1.3K
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