stable-diffusion-webui-images-browser VS sd-dynamic-thresholding

https://github.com/ljleb/prompt-fusion-extension https://github.com/DominikDoom/a1111-sd-webui-tagcomplete https://github.com/adieyal/sd-dynamic-prompts https://github.com/yfszzx/stable-diffusion-webui-images-browser

If you want to see the generation data of a specific image I would recommend the image browser extension: https://github.com/yfszzx/stable-diffusion-webui-images-browser If you just want a list of all the prompts you've ever used, I can't help you.

Images are saves to /tmp/outputs so you will need to download them to your PC if you want to keep them, or change the storage location to /notebooks/stable-diffusion-webui/outputs to keep them in your paperspace - it is recommended to install the image browser extension by opening a terminal in paperspace, and then using cd /notebooks/stable-diffusion-webui and then git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser , then stopping and restarting the second cell (Note this is how all extensions need to be installed)

Image Browser

!git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui '/content/stable-diffusion-webui' !git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser /content/stable-diffusion-webui/extensions/stable-diffusion-webui-images-browser !curl -Lo /content/stable-diffusion-webui/models/Stable-diffusion/SomeModel.safetensors https://huggingface.co/author/SomeModel/resolve/main/SomeModel.safetensors !curl -Lo /content/stable-diffusion-webui/models/Stable-diffusion/AnotherModel.safetensors https://huggingface.co/author/AnotherModel/resolve/main/AnotherModel.safetensors

https://github.com/deforum-art/deforum-for-automatic1111-webui https://github.com/yfszzx/stable-diffusion-webui-images-browser https://github.com/camenduru/stable-diffusion-webui-huggingface https://github.com/Vetchems/sd-civitai-browser https://github.com/kohya-ss/sd-webui-additional-networks

!pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15+e163309.d20230103-cp38-cp38-linux\_x86\_64.whl !git clone -b v1.6 https://github.com/camenduru/stable-diffusion-webui !git clone https://github.com/deforum-art/deforum-for-automatic1111-webui /content/stable-diffusion-webui/extensions/deforum-for-automatic1111-webui !git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser /content/stable-diffusion-webui/extensions/stable-diffusion-webui-images-browser !git clone https://github.com/camenduru/stable-diffusion-webui-huggingface /content/stable-diffusion-webui/extensions/stable-diffusion-webui-huggingface !git clone https://github.com/Vetchems/sd-civitai-browser /content/stable-diffusion-webui/extensions/sd-civitai-browser %cd /content/stable-diffusion-webui !wget https://huggingface.co/prompthero/midjourney-v4-diffusion/resolve/main/mdjrny-v4.ckpt -O /content/stable-diffusion-webui/models/Stable-diffusion/mdjrny-v4.ckpt

!git clone https://github.com/camenduru/stable-diffusion-webui !git clone https://github.com/deforum-art/deforum-for-automatic1111-webui /content/stable-diffusion-webui/extensions/deforum-for-automatic1111-webui !git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser /content/stable-diffusion-webui/extensions/stable-diffusion-webui-images-browser %cd /content/stable-diffusion-webui

I believe there is an extension that allows you to do that called Image Browser. You can install it from the extensions panel in Auto1111.

For outputs to look right, you will need some form of CFG rescale or dynamic thresholding in order to correct for overexposure (A1111 extensions are linked -- I am told that ComfyUI has nodes available for these functions). A good starting point for CFG rescale is 0.7, as recommended in the paper. I strongly suspect that CFG rescale is not an ideal solution and leaves a substantial training-inference gap, and when using zero terminal SNR models I find that Dynamic Thresholding can give better outputs that are closer to what I expect from the data without the brownout often caused by CFG rescale. A potential starting point for Dynamic Thresholding would be: Restart sampler, 15 CFG scale, Mimic CFG scale 15 7.5, Sawtooth on both scale schedulers, 6 for both minimum values, scheduler value 4, do not separate feature channels, ZERO, STD. You will likely have to experiment a lot with Dynamic Thresholding. (edit: small correction to DT settings)

Recently switched from A1111 and i love it so far, flexibility to orchestrate complex workflows automatically instead of manual operations is a life changer. Anyhow, one extension i like on A1111 was this one: https://github.com/mcmonkeyprojects/sd-dynamic-thresholding

In the Automatic1111 webui, there is a Dynamic Thresholding (CFG scale fix) extension that:

Ive found using ADetailer (https://github.com/Bing-su/adetailer, using their reccomended advanced settings and face_yolov8n.pt) and Dynamic Thresholding (CFG set to 12 and Mimic to 7) has vastly improved my face renders. (https://github.com/mcmonkeyprojects/sd-dynamic-thresholding) GL!

The output LoRA works best with CFG at 4, because at 7 it gets that gasoline colors and contrast of overbaking, but I guess this is a tradeoff of that many steps in total (5200) since the earlier snapshots were not that good in style and with character details. You can use a workaround like the Dynamic Trescholding extention: https://github.com/mcmonkeyprojects/sd-dynamic-thresholding.git - helps a lot in many cases when you want a high CFG but the model/lora overbakes them (it mimics a lower CFG while keeping the high CFG details and prompt alignment).

Use sd-dynamic-thresholding extension (set CFG scale to 12 or more and mimic CFG scale to 7): https://github.com/mcmonkeyprojects/sd-dynamic-thresholding

Tweak this up or down for small changes. Too far and you’ll get a different image. Extensions like Dynamic Thresholding can let you go much higher without the overexposed look.

Turn CFG scale down or maybe use this extension, I've never used Dynamic Thresholding before but I think its what you want