stylized-neural-painting
clip-glass
| stylized-neural-painting | clip-glass | |
|---|---|---|
| 6 | 13 | |
| 1,536 | 177 | |
| - | - | |
| 0.0 | 0.0 | |
| over 2 years ago | over 2 years ago | |
| Python | Python | |
| Creative Commons Zero v1.0 Universal | GNU General Public License v3.0 only |
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stylized-neural-painting
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I want to create an image to image transformer but I have no idea how to get started.
I want to create a Python program that takes in an image, paints over it, then spits out the resulting image. What I want to do is almost exactly like this project, but I want to do it from scratch, and make it more attuned to people's faces, as well as add more than just oil painting, pixel art, and marker strokes.
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test
(Added Mar. 9, 2021) PaintCLIP.ipynb - Colaboratory by advadnoun. Uses Stylized Neural Painter to generate images. As of time of writing, this gave me an error message.
- I want to create a Stylized Neural Painting software
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Combine neural painting with deepbrush for 100% realistic computer-made painting?
I think stroke-based painting methods like these are neat: https://github.com/jiupinjia/stylized-neural-painting https://github.com/fogleman/primitive
- Stylized Neural Painting
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Idea for developers: Use CLIP to steer a differentiable vector graphics generator
Not exactly what you suggested, but pretty fun! Here's PaintCLIP using https://github.com/jiupinjia/stylized-neural-painting
clip-glass
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test
(Added Feb. 5, 2021) CLIP-GLaSS.ipynb - Colaboratory by Galatolo. Uses BigGAN (default) or StyleGAN to generate images. The GPT2 config is for image-to-text, not text-to-image. GitHub.
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Image to text models
After a cursory search I found CLIP-GLaSS and CLIP-cap. I've used CLIP-GLaSS in a previous experiment, but found the captions for digital/CG images quite underwhelming. This is understandable since this is not what the model was trained on, but still I'd like to use a better model.
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[R] end-to-end image captioning
CLIP-GLaSS
- What CLIP-GLaSS thinks Ancient Egyptian computers would look like
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Texttoimage 3 Images For Text Photo Of Donald
The images were generated using this notebook.
- CLIP-GLaSS prompt: "Screenshot of a video game from the 1930s"
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[P] List of sites/programs/projects that use OpenAI's CLIP neural network for steering image/video creation to match a text description
The CLIP-GLaSS project has image-to-text functionality (I haven't tried it.)
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For educational purposes: Text-to-image (3 runs with no cherry-picking, 6 images each) for text "Photo of a Lamborghini painted purple and red" generated using CLIP-GLaSS. config=StyleGAN2_car_d. save_each=50. generations=1000
Link to notebook.
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Sharing CLIP magic based on OpenAI's blog post via a bit more accessible YT medium. Lmk what u think 🙈 ❤️
CLIP-GLaSS
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[R] [P] Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search. Link to code and Google Colab notebook for project CLIP-GLaSS is in a comment.
Github for CLIP-GLaSS is here.
What are some alternatives?
Primitive Pictures - Reproducing images with geometric primitives.
a-PyTorch-Tutorial-to-Image-Captioning - Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
Story2Hallucination
meshed-memory-transformer - Meshed-Memory Transformer for Image Captioning. CVPR 2020
deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun
Styleformer - A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/casual, active/passive, and many more. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
aphantasia - CLIP + FFT/DWT/RGB = text to image/video
big-sleep - A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun
StyleCLIP - Using CLIP and StyleGAN to generate faces from prompts.
pytorch-AdaIN - Unofficial pytorch implementation of 'Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization' [Huang+, ICCV2017]
CLIP-Style-Transfer - Doing style transfer with linguistic features using OpenAI's CLIP.