Skip to content

ESRGAN

Video Lecture

Section Video Links
ESRGAN ESRGAN ESRGAN 

 (Pay Per View)

You can use PayPal to purchase a one time viewing of this video for $1.49 USD.

Pay Per View Terms

  • One viewing session of this video will cost the equivalent of $1.49 USD in your currency.
  • After successful purchase, the video will automatically start playing.
  • You can pause, replay and go fullscreen as many times as needed in one single session for up to an hour.
  • Do not refresh the browser since it will invalidate the session.
  • If you want longer-term access to all videos, consider purchasing full access through Udemy or YouTube Memberships instead.
  • This Pay Per View option does not permit downloading this video for later viewing or sharing.
  • All videos are Copyright © 2019-2025 Sean Bradley, all rights reserved.
Video Timings 00:00 Understanding ESRGAN: Enhanced Super Resolution Generative Adversarial Network
00:35 ESRGAN's Deep Learning for Image Enhancement
01:10 Contrasting ESRGAN with Basic Upscaling Algorithms
01:50 Installing ESRGAN Models via ComfyUI Manager
02:30 Manually Downloading and Integrating More ESRGAN Models
03:15 Demonstrating Different ESRGAN Scaling Factors (X2, X4, X8)
04:00 Observing Performance, Speed, and Potential Artifacts
04:40 Setting Up Side-by-Side Image Comparisons
05:20 Installing the ComfyUI Image Compare Custom Node
06:00 Utilizing Image Compare for Clear Quality Visualization
06:40 Applying ESRGAN to Various Generated Image Prompts
07:20 Downscaling ESRGAN Output Proves Sustained Quality
08:00 Conclusion and Encouragement to Experiment with ESRGAN

Description

ESRGAN is an abbreviation for Enhanced Super-Resolution Generative Adversarial Network.

  • Enhanced – It's an improvement over earlier SRGAN (Super-Resolution GAN) models.

  • Super-Resolution – Refers to the task of increasing image resolution (e.g., 256×256 → 1024×1024) while preserving or enhancing detail.

  • Generative Adversarial Network (GAN) – A type of machine learning model where two networks (a generator and a discriminator) compete to produce high-quality, realistic outputs.

ESRGAN uses deep learning to sharpen, upscale, and restore images, often adding plausible detail during the process.

ESRGANx2

ESRGANx4

ESRGANx4plus

ESRGANx8

ESRGANx4plus produces better quality output versus ESRGANx4 at the expense of speed and more VRAM requirement. ESRGANx4plus requires ~4–6 GB verses ~2–4 GB for ESRGANx4.

Tip

The Image Compare tool shown in the video is no longer available.

You can instead use newer ComfyUI Image Compare tool that you will find using the Manager search tool.

Sample Prompts

  • modern organic interior

  • colourful 1970s interior

  • gaudi style interior or gaudi style gardens

  • cyberpunk interior

Troubleshooting

Error : Failed to clone repo: https://github.com/rakki194/ComfyUI-ImageCompare

The Image Compare tool shown in the video is no longer available.

You can instead use the more general ComfyUI Image Compare tool that you will find in the Manager UI custom node search option.

Or, for a more advanced version that allows choosing the blend mode, you can try the ComfyUI-EsesImageCompare tool instead.

ComfyUI Image Compare (GitHub)