Hello everyone. I am Dr. Furkan Gözükara. PhD Computer Engineer. SECourses is a dedicated YouTube channel for the following topics : Tech, AI, News, Science, Robotics, Singularity, ComfyUI, SwarmUI, ML, Artificial Intelligence, Humanoid Robots, Wan 2.2, FLUX, Krea, Qwen Image, VLMs, Stable Diffusion
I'm thinking upscale and crop may still pose a problem if the aspect ratio is not square on the original image. I'm thinking I may need to sacrifice some detail/body on those in order to get a square fit? Does your resizer script help with that or will it not cut out body parts to make it square?
I would also like to say a few words about the sample photos. I am currently training a Lora, where all the training photos are upper body shots. My training burned very fast and I just went down to a d_coef of 0.65 to get a good lora. So that's why it's good to take your sample shots from as many angles and distances as possible, because you can make a stronger and more flexible Lora. Just taking the same type of photos will quickly get stuck and the model will learn too much.
my provided dataset is 768x1024 for realistic and image processing is 1024 in max resolution parameter. I followed the tutorial, first I adjusted the aspect ratio with the cropped.py script then I pre-processed the image at 768x1024 in the train tab. I have provided class files in the same resolution, however, the images it generates in the directory are 880x1176. I think I'll have to use it at 512x512 with realistic_vision_v5.1.
You were right, the problem was that the dataset was 768x1024 and the classes were 1024x768, I adjusted the dataset to 1024x768 and now it has gone to the cache latents phase. I think it will work now.
I haven't used ComfyUI yet, but the error is similar to the dreambooth save preview. If it uses transforms it could be the problem with the new versions in Torch 2.0. Try using an old version that used Torch before 2.0. Then if I have time and find out something about it I can share it. I have fixed many issues in my local version of dreambooth.
ValueError: Cannot load F:\AI\ComfyUI_windows_portable\ComfyUI\models\MagicAnimate\control_v11p_sd15_openpose because down_blocks.0.attentions.0.transformer_blocks.0.attn2.to_k.weight expected shape tensor(..., device='meta', size=(320, 1280)), but got torch.Size([320, 768]). If you want to instead overwrite randomly initialized weights, please make sure to pass both
Have scoured the docs for an answer to this, to no avail. Is it possible to add additional input channels to a model after initializing it using .from_pretrained. For example (taken from your Dream...
I'm new at this. After installing https://github.com/comfyanonymous/ComfyUI is it enough or do I need to also install: OpenposePreprocessor, VHS_VideoCombine,VHS_LoadVideo in custom_nodes ?
The most powerful and modular stable diffusion GUI with a graph/nodes interface. - GitHub - comfyanonymous/ComfyUI: The most powerful and modular stable diffusion GUI with a graph/nodes interface.
hmm i write E not well. the first, i install comfyui the next, i install manganer node if u do any workflow, i use "load" in tank. it's help u install miss node.
Hello everyone. I’d love your opinion on a topic. I’ve been experimenting with facial recognition softwares like roop, reactor, wav2lip, etc. Something I notice though is that the outputs are almost always significantly lower resolution than the beginning input. I’ve tried several up scalers to mitigate this, including doing frame by frame upscale to no avail. Do any of you know a good upscale tie a method I can try by chance? Thanks!!!
i keep getting huggingface errors while trying to install locally on my machine for magic generate - huggingface_hub.utils._validators.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': 'magic-animate/pretrained_models/stable-diffusion-v1-5'. Use
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Thank you for answering! Do you think an outside 3rd party upscale is an option? Or is it that once the video is generated, it is what it is and it can’t be improved?