lama
dl-colab-notebooks
Our great sponsors
| lama | dl-colab-notebooks | |
|---|---|---|
| 17 | 1 | |
| 7,165 | 1,659 | |
| 3.7% | - | |
| 5.4 | 0.0 | |
| 3 months ago | about 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
lama
-
Can someone please help me with inpainting settings to remove the subject from this image? I want to rebuild as much of the original background as possible.
You could try to use ControlNet inpaint+lama locally, but results aren't as good in my experience. Or you could try local install of lama directly, but the setup process isn't very smooth.
-
[D] Which open source models can replicate wonder dynamics's drag'n'drop cg characters?
You may be able to remove the actor with lama. https://github.com/advimman/lama
-
ControlNet Update: [1.1.222] Preprocessor: inpaint_only+lama
LaMa: Resolution-robust Large Mask Inpainting with Fourier Convolutions (Apache-2.0 license) Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, Victor Lempitsky (Samsung Research and EPFL)
-
[Inpainting] [Q] Want to remove a person/ group of people from an image.
You could try using LaMA: https://github.com/saic-mdal/lama .
-
[task] Python developer for two tasks, one 30$ the other 50$
Task 1: 30$ Write a script to prepare data for https://github.com/saic-mdal/lama. You should be able to prove on video that your script works properly after i give you some data and you train and there's some acceptable output (not perfect, since i know how ml works).
-
Research Topics for Master/PHD
I have some interest in image inpainting, but the recent paper introduced by Samsung - https://github.com/saic-mdal/lama seems like it reached a stage where there isn't much room that we can add for novelty. I am quite interested but not confident if I can come up with a novel idea that can do better than the proposed model, especially if they trained the model on multiple GPUs for days, which is something that I don't have.
- The Black Hole Photographs: Censored Images from America’s Great Depression
- Image inpainting tool powered by LaMa
- Resolution-Robust Large Mask Inpainting with Fourier Convolutions
-
[D] Paper Explained - Resolution-robust Large Mask Inpainting with Fourier Convolutions (w/ Author Interview)
Code: https://github.com/saic-mdal/lama
dl-colab-notebooks
-
xQc's New TTS Summed Up
Alright, thanks. I don't think I found uberduck's notebooks with a quick google but I did find this, will probably look at those at some point in time
What are some alternatives?
IOPaint - Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures.
Colab-Crypto-Mining - Cryptocurrency Mining Experiments on Google CoLab Notebooks
Torrent-To-Google-Drive-Downloader-v3 - Simple notebook to stream torrent files to Google Drive using Google Colab and python3.
Julia-on-Colab - Notebook for running Julia on Google Colab
strv-ml-mask2face - Virtually remove a face mask to see what a person looks like underneath
blender-colab - Render Blender 4.x scenes with Google Colaboratory
cleanup.pictures - Code for https://cleanup.pictures
Real-ESRGAN-Video-Batch-Process - Upscale any number of videos using this colab notebook!
MyST-NB - Parse and execute ipynb files in Sphinx
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.