There may be a current issue with the extension. Here's an open issue on GitHub of others experiencing the same problem: github.com/thygate/stable-diffusion-webui-depthmap-script/issues/453 Recommend following that for updates.

@@PromptingPixels Thank you. But the problem was not solved there.

The developer has updated to the version DepthMap v0.4.7 (76a758c5).Everything works. Thank you.

I'd recommend making sure ComfyUI is up to date and also check the logs if there are any errors as to why its getting disconnected. When preparing for this video, I found this custom node was causing a similar issue: github.com/Acly/comfyui-inpaint-nodes Hope this helps!

Hey there - happy to hear the videos are helpful. So my personal setup is using a local PC with a RTX 3060 over the local network. When I boot comfy or automatic1111, i add the --listen command to open up LAN access. This allows me to generate via my MBP - or any other device. Some earlier tutorials I was just exclusively using a MBP. As far as RunDiffusion, Think Diffusion, etc. I need to do some videos on this. They are very beginner friendly, but can become a bit pricey and have some downsides that aren't really apparent at first (i.e. you can't access a file manager without booting up an instance). I think generally the best route is to scope out a project locally and offload the processing to them as it will help reduce total time use. Hope this answers some of your questions - if anything else, feel free to ask!

Yeah definitely. Easy to do with landscapes, scenes, etc. as you can raise the denoise (probably around .8-.9) and change your prompt accordingly. However, if doing this to characters, people, etc. you'll lose some of their likeness in the process. To counteract, I think using an IP Adapter or LoRA may help to counteract this.

Prompt: average looking guy, glasses, middle age, short beard, sedentary lifestyle, photo grain, poor camera quality, single light source, grey shirt, plain white room Negative prompt: hair

Interesting challenge. Let me play around with this idea. The one option would be to inverse select the subject and then apply changes. As for re-lighting the scene perhaps IC Light could then be added: github.com/kijai/ComfyUI-IC-Light-Wrapper This is just kicking around an idea but might be worth trying.

I think latentvision himself did that in a video i cant remember which one

I tried it but it changes the subject too, maybe I'm not doing it well🤔

Cloning is the same as copying it to your hard drive. There are a couple ways you could do this - either with the `git clone` command which was presented in the video. Or under that same box you could download the zip of the repo and then just extract it to your preferred location on the hard drive. Downside to this approach is that you can't perform a `git pull` command to update the repo when the author publishes updates to the repo. Alternatively, if you are having a hard time getting ComfyUI to work on your machine, Pinokio (pinokio.computer/) is super easy and offers a 1-click installer.

Before the VHS Video Combine node at the end you can do a face swap to then modify the frames before they are stitched together.

That would be an img2vid workflow rather than txt2img (as is outlined in this video). I was playing around with an img2vid workflow a few weeks ago. Will try to get a video about this posted up onto the channel as the process is going to be different than what was covered in this video. Method 1: You could use IPAdapter+AnimateDiff to convert an image into a short form video. This workflow goes through the steps: civitai.com/models/372584 Another option is to use Stable Video Diffusion (SVD) which takes an image as an input and outputs a video. The problem though is that you can't apply textual prompts (that I am aware of).

@@PromptingPixels can you do textual prompts inside of the img2vid workflow you mentioned wanting to make a video on?

@@GES1985 Yes, textual prompts should be supported to help inform the output.

Hey GES1985 - you can place upscale models in the ComfyUI\models\upscale_models directory. Models are available from multiple places as you mentioned - civitai, huggingface, openmodeldb.info.

Thanks so much for the kind words! If you have any other questions, don't be a stranger - drop them in the comments/Discord/website etc and I'll try my best to get back.

I haven't trained a checkpoint, only LoRAs. From my understanding, the question would largely be around the labeling of the images, minimum resolution depending on the model, and the types/diversity of images (whether its a general checkpoint that has all your images, or those separated based on the types of topics - i.e. wedding, wildlife, fashion, etc.). This article on HuggingFace (huggingface.co/docs/diffusers/en/tutorials/basic_training) demonstrates training a diffusion model based on 1k images from the Smithsonian Butterflies dataset. Sorry this is kind of a non-answer - but thought it may be helpful to share the thoughts above. Best of luck!

@@PromptingPixels Thank You so much, its a first step into teh right direction i think, much appreciated

This video in particular is using the Dreamshaper 8 Inapinting model which you can find on either HuggingFace and Civitai: huggingface.co/Lykon/dreamshaper-8-inpainting/tree/main civitai.com/models/4384?modelVersionId=131004

Hey @meadow-maker, wow, I never noticed how much I say 'go-ahead' until you pointed it out! Thanks for the heads-up. I’ll definitely work on that. And yeah, a drinking game would be dangerous with my tutorials! 😂 Cheers! 🍻

I believe this is native to ComfyUI - don't recall a custom node adding this feature.

@@PromptingPixels Appreciate the response. I found the ComfyUI Custom Scripts that did the autocomplete.

Thank you for the nice feedback - happy to see the tutorial was useful for ya!