BigGAN-PyTorch
Text-to-Image-Synthesis
| BigGAN-PyTorch | Text-to-Image-Synthesis | |
|---|---|---|
| 4 | 1 | |
| 2,802 | 389 | |
| - | - | |
| 0.0 | 0.0 | |
| 10 months ago | almost 4 years ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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BigGAN-PyTorch
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[D] Pre-trained weights for GANs online?
The second link gives you the entire source code for training the model https://github.com/ajbrock/BigGAN-PyTorch/tree/master . Looks like BigGAN.py and BigGANdeep.py are the two files that define the architecture. Can you work with that?
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I'm looking for an AI Art generator from images
BigGAN (https://github.com/ajbrock/BigGAN-PyTorch) - This is a PyTorch implementation of the BigGAN model for generating high-resolution images. It is trained on a large dataset and can generate a wide range of images, including photographs of animals, objects, and landscapes.
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[D] Using activity regularization instead of batch norm.
Tangentially, theoretically you can't use BN in the discriminator for WGAN-GP anyway (assuming that you're using the Gulrajani work) because it breaks the sample independence assumptions of the GP. If you have a relatively structured dataset (eg all faces, all cars, all giraffes, etc.) and no class conditioning, look into StyleGAN2-ADA for the best results. If you have a dataset with a lot of variation and a lot of classes try using the BigGAN repo.
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Έφτιαξα ένα AI που παράγει εικόνες από μερικές λέξεις. Να τι έφτιαξε όταν του είπα να σκεφτεί ένα "Αφηρημένο Πορτρέτο"
BigGan και Deep Dream https://github.com/ajbrock/BigGAN-PyTorch https://github.com/google/deepdream
Text-to-Image-Synthesis
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Text to Image generation using path file
I trained a text to image generation model based on https://github.com/aelnouby/Text-to-Image-Synthesis. Now I have 2 path files (one for generator , another for discriminator) . How to generate images using this path files?
What are some alternatives?
stylegan2-ada-pytorch - StyleGAN2-ADA - Official PyTorch implementation
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
PyTorch-StudioGAN - StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
feed_forward_vqgan_clip - Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
pytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers
anycost-gan - [CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
transfer-learning-conv-ai - 🦄 State-of-the-Art Conversational AI with Transfer Learning
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
pytorch-forecasting - Time series forecasting with PyTorch
zsl-kg - Framework for zero-shot learning with knowledge graphs.
code-generator - Web Application to generate your training scripts with PyTorch Ignite
storyteller - Multimodal AI Story Teller, built with Stable Diffusion, GPT, and neural text-to-speech