A Real-ESRGAN equipped Colab notebook for CLIP Guided Diffusion

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Deep Learning 360Diffusion
Overview

#360Diffusion automatically upscales your CLIP Guided Diffusion outputs using Real-ESRGAN.

Latest Update: Alpha 1.61 [Main Branch] - 01/11/22

Note that 4096 files aren’t quite as pretty as 2048, and they’re massive in file size. 2048 is appealing in most cases. If you intend on upscaling to anything higher than 1024, I recommend using the 512 diffusion model found in the settings-

Credits & Acknowledgements

Prior release(s): Implemented Daniel Russ’s Perlin revisions, fixed init_bug, 4096 double-pass, VRAM fixes, practical debug_mode (set to higher skip_timestep)

All edits & feedback are welcome and appreciated~

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Comments
  • Two errors in notebook

    Two errors in notebook

    Running the notebook as-is on colab pro, I get the following errors:

    Current upscale target is /content/drive/MyDrive/MyName/Diffusion/existential/existentialbatch0000_iteration0021_output0000_211217-112807_637275_out.png next_outscale is 2 usage: inference_realesrgan.py [-h] [-i INPUT] [-n MODEL_NAME] [-o OUTPUT] [-s OUTSCALE] [--suffix SUFFIX] [-t TILE] [--tile_pad TILE_PAD] [--pre_pad PRE_PAD] [--face_enhance] [--half] [--alpha_upsampler ALPHA_UPSAMPLER] [--ext EXT] inference_realesrgan.py: error: unrecognized arguments: --model_path /content/Real-ESRGAN/experiments/pretrained_models/RealESRGAN_x4plus.pth

    ERROR: CAN'T FIND UPSCALED FILE /content/drive/MyDrive/MyName/Diffusion/existential/existentialbatch0000_iteration0021_output0000_211217-112807_637275_out.png

    bug 
    opened by Ali762 3
  • 2022 Critical Fixes Tracking

    2022 Critical Fixes Tracking

    Critical tasks

    • [x] Revise depcrecated real-esrgan param 'model_path' (Referenced in #3)
    • [x] Update links if necessary - see this for reference
    • [ ] Revise project to point to direct to self-forked repos (longevity)
    documentation 
    opened by sadnow 1
  • Updated params for inference_realesrgan.py

    Updated params for inference_realesrgan.py

    The upscaler (inference_realesrgan.py) now uses a different param for the upscaling model (--model_name , just a name, instead of --model_path, the path to the pth file). I've updated the code to reflect this: without this fix, the colab can not upscale and save the generated image.

    opened by juanalonso 0
  • not really a issue more a question about seeds

    not really a issue more a question about seeds

    at the moment the seeds change per batch which is great if you have one initial image , is there a way to disable that so it does one seed throughout the whole batch run. The reason I ask is , at the moment I change my initial image per batch number ,so batch 0 / initial_img000.png || batch 1 initial_img_001.png and so on. I would love to have the seed consistant through the batch run so only the initial image changes for me.

    I hope this makes sense somehow haha.

    Thank you so much for your work!

    documentation question 
    opened by UglyStupidHonest 2
Owner
I have twisted and crawled and churned through the absurd in search of the truth but alas, this is all just paper flying in our faces.
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