Knifestripe

As promised, today I will show you how to use controlnet_depth to create the pose you want with 100% accurate.In my previous article, we mentioned open_pose but in terms of accuracy, they are still not really perfect.Hands and fingers problems are always happen when using Stable Diffusion, so this control_net will solve these kind of problems.The way control_net depth works is very simple, they will analyze the 3D surface of the object from the image you gave, and then render the image from that 3D surface.1/ First, click here2/ Select control_net depth3/ Select the working mode for controlnet depth, here I will choose the working mode zoe instead of midas because the accuracy of zoe is much higher than midas4/ Upload your reference image via this option5/ Adjust the weight of control_net depth, recommend 0.5~0.7 for best results without losing much details6/ And tadaaaa UwUTry again with another pictureAnd the resultHope you enjoy my post, subscribe or support me for more quality content next time (乃^o^)乃

Have you ever encounter these problem, when you use Stable Diffusion and suddenly many girls appear in one frame, or the limbs are deformed, or the body is stretched out?These are common errors when you use Stable Diffusion. The reasons for fixing them are very simple and many people often ignore them because they think they are not important.The reason behind is the resolution and image ratio you have chosen are all wrong.I will give a brief explanation about this, because as we know Stable Diffusion currently has two most popular versions: SD 1.5 and SDXL.With version SD1.5, they are trained by million small resolution images, with a pixel size of only about 512x512. Therefore, when you choose an image size > 1.5 times larger than the resolution of 512x512, the AI will encounter many difficulties in the sampling and denoising process, then errors will certainly occur.Similar to the SDXL model, although in terms of prompt understanding they are clearly superior to SD1.5, and the SDXL trained data is twice that of SD1.5 (1024x1024), but still, they still has the error of the human body being stretched out.Although you can use negative prompts to prevented these errors, they will certainly still occur frequently, which really annoying.So to avoid these errors from happening, I recommend adjusting the resolution to only 1.1~1.5 times than the original data training image sizeAnd here are the tweaks that I often use, please pay attention to the ratio too (d ^o^ b)1. 768x768 (ratio: 1:1) with SD 1.5 and 1024x1024 (ratio: 1:1) with SDXL: Portrait, logo, vector, close-up sports display)2. 640x960 (ratio: 2:3) with SD 1.5 and 768x1024 (ratio: 3:4) with SDXL: In cases you want to create full body view photos, cowboy shots, street landscape photos3. 960x640 (ratio 3:2) with SD 1.5 and 1024x768 (ratio: 4:3) with SDXL: In case you want to create of many people, photos of natural scenes with many details.

Hi guys, this is my first article on TensorArt. Have you ever found it difficult to make a difficult pose for a character such as dancing?­Even though you used many specific words to describe it, but it seem like AI don't understand your promptToday I will introduce to you the control_net that will make your "AI life" easier than ever. ^o^That is control_net openposeHow to use?It's very simple.Let say you wanna make a ballet dancer1/ Go to the "Add control net" option2/Upload the image sample you have, then select the working model of control_net (for ex: openpose)3/ Then wait for the resultOne more example with akimbo pose, with in my opinion is very hard for AI to understandOf course, because this is a very basic controlnet pose, it is understandable that the accuracy is not high.In the next article, I will show you a more advanced option called control_depth, which helps you achieve results 10 times more accurate than openpose.­­­­­