Canonical: https://instain.ru/en/ai/controlnet/ Language: en Lvmin Zhang, Anyi Rao, Maneesh Agrawala model # ControlNet. Composition control for image generation 4.35 / 5 [Directory score](https://instain.ru/en/ai/controlnet/#editorial-rating) [Official website ](https://github.com/lllyasviel/ControlNet) An original architecture for conditioning diffusion models. It can use a separate image to describe the scene's structure. ![Official Repository ControlNet with a description of the conditions of generation.](https://instain.ru/assets/images/controlnet-screen-6b261c328af2-1200.webp) Repository of ControlNet authors with examples of spatial control. [Open the source ](https://github.com/lllyasviel/ControlNet) ## An extra condition for generation ControlNet adds frame structure data to the text query. In the original work, the authors show control by contours, lines, depth and posture. Each condition needs the right weight set. This helps to keep the details between options. Content and style define the text, and the condition is responsible for part of the spatial organization. A compatible basic model is required. ## Variations from a room sketch Sketch a workshop with a window on the left, a table in the middle, and a clear wall on the right. Clean up the lines and choose weights that match the input. Generate several lighting options from the same sketch. Check that the spacing between the table and window stays consistent. If the model follows stray pencil marks, clean up the source image or reduce the conditioning strength. Change one setting at a time when comparing versions. If you need one item, check the rest of the frame. Strong binding to the lines can transfer to the edge walls that were auxiliary. ## Check compatibility before a batch Check which models are weighted and write down their names along with the query options. The original image handler also affects the outcome. For control, save the option without a structural condition and compare the composition. If the drawing belongs to another author, agree on the terms of its use before publishing the result. Check the weight separately. ## Suitable tasks - Save your own sketch - Compare Styling Options for One Scene Features ## Strengths - Control over a given image structure - Different types of additional conditions Things to consider ## Limitations - A compatible basic model is needed - The hard condition can emphasize the extra lines ## Selection and conditions Free access Yes Trial period Not confirmed No sign-up required Not confirmed Russian interface Not confirmed Local installation Yes API Not confirmed “Not confirmed” means there is not enough information. The feature may still be available; check the developer’s terms. Input formats Text, Image Result Image ### Terms The model is connected to a compatible diffusion system. Select the weights for the basic model and the type of structural image. From task to first result ## Practical example Task Save your own sketch What to prepare A short description of the intended illustration and the chosen aspect ratio. ### Task brief or prompt Editorial illustration: a small workshop, a notebook and a green desk lamp on a table, soft daylight, a simple composition and space on the left for a headline. No lettering, logos or watermarks. ### Expected result An illustration with a clear composition and space for text; this is a brief, not a published generated result. ### How to check the result - Check object geometry and any unintended lettering. - Check the dimensions, license and commercial-use terms for the selected mode. An editorial teaching example of a task brief, not the result of hands-on testing of the service. Check that the required mode is available, that you have rights to the source material and that the intended use of the result is permitted. Check details ## Official sources - [ControlNet Code and Examples ](https://github.com/lllyasviel/ControlNet) - [Article by ControlNet ](https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_Adding_Conditional_Control_to_Text-to-Image_Diffusion_Models_ICCV_2023_paper) This description is based on the developer’s material. Features, prices and availability may change; check the primary source before use. About the tool Developer Lvmin Zhang, Anyi Rao, Maneesh Agrawala Category [Images](https://instain.ru/en/category/images/) Access The model is connected to a compatible diffusion system. Select the weights for the basic model and the type of structural image. Payment The code and examples of self-starting are published. Licenses of ControlNet, the base model and weights may vary. API No separate API specified [Developer terms ](https://github.com/lllyasviel/ControlNet) Directory score 4.35 / 5 Features 4.60 / 5 Workflows 4.00 / 5 Ecosystem 4.50 / 5 Documentation 4.30 / 5 Scores are an editorial guide to the directory. They are not user reviews or the results of personal testing. [See the methodology ](https://instain.ru/en/methodology/) Keep exploring ## For similar tasks [Full category ](https://instain.ru/en/category/images/) Assistants ### [YesAI](https://instain.ru/en/ai/yesai/) Chat, images and videos in one browser 4.70 / 5 service API availability confirmed Images ### [ProxyAI](https://instain.ru/en/ai/proxyai/) Midjourney, Kling and Veo in a Russian-language browser interface 4.67 / 5 service Other result format: Video Images ### [Adobe Firefly](https://instain.ru/en/ai/adobe-firefly/) Generative tools alongside familiar design workflows 4.65 / 5 service API availability confirmed