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
when try install one click , i got error : Traceback (most recent call last): File "X:\03_General\huy\supir\SUPIR\gradio_demo.py", line 5, in <module> from gradio_imageslider import ImageSlider File "C:\Users\AZPC\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio_imageslider__init__.py", line 1, in <module> from .imageslider import ImageSlider File "C:\Users\AZPC\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio_imageslider\imageslider.py", line 16, in <module> from gradio.events import Events ImportError: cannot import name 'Events' from 'gradio.events' (C:\Users\AZPC\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio\events.py) Press any key to continue . . .
I'm a bit lost at this point For users who can connect to huggingface, please setting LLAVA_CLIP_PATH, SDXL_CLIP1_PATH, SDXL_CLIP2_CKPT_PTH in CKPT_PTH.py as None. These CLIPs will be downloaded automatically.
I used ChatGPT to explain some new parameters in SUPIR: --edm_steps: Number of steps for the EDM Sampling Scheduler. This determines how many iterations the sampling process will take. A higher number generally means more refinement but takes longer.
--s_stage1: Strength control for the first stage of processing. A negative value indicates that this stage is not used.
--s_churn: A hyperparameter of the EDM process, influencing the variability or diversity in the generated samples.
--s_noise: Another hyperparameter for EDM, affecting the amount of noise introduced during the diffusion process, which can impact the clarity or smoothness of the output.
--s_cfg: Classifier-free guidance scale for prompts. This parameter adjusts the influence of textual prompts on the generation process, affecting how closely the output matches the given textual description.
--s_stage2: Strength control for the second stage of processing. Adjusts the intensity of modifications in the second stage.
linear_CFG and --linear_s_stage2: These settings allow for a linear increase of the s_cfg and s_stage2 parameters from their start points (--spt_linear_CFG and --spt_linear_s_stage2) to their specified values through the process, providing a way to dynamically adjust the guidance strength.
--spt_linear_CFG and --spt_linear_s_stage2: Define the starting points for the linear increase of s_cfg and s_stage2, respectively.
--ae_dtype and --diff_dtype: Specify the data types (precision) used during inference for the autoencoder and diffusion processes, respectively, affecting memory usage and computational speed.
@Furkan Gözükara SECourses do you know how to make SUPIR work on ComfyUI with reduced memory? I’ve been trying to run the ComfyUI node but it runs out of VRAM - I’m using Colab T4 which has 15gb of VRAM
Just FYI, I upscale a pano 2048x1024 to 4096x2048 (2x) and it was eating over 20 gigs of Vram. That's the limit my 3090 can do. It did add a lot of details. Some area didn't look good so I did another version of 2x with Topaz Gigapixels. I then cherry pick masked in area I like best from the two with Photoshop. You can see the final pano here "https://sapphiregreenearth.com/stabledifussionwaterfall2/"
Thinking back, maybe Magnific can be justified for their high price, considering the amount of Vram they need time the amount of servers they use.
What I would love to see in the Gradio docs is the list of techniques or libraries they use. I don't see any AI packages in the requirements.txt but there are 50 total. torch and transformers?