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A simple PyTorch implementation of conditional denoising diffusion probabilistic models (DDPM) on MNIST, Fashion-MNIST, and Sprite datasets
Generate photo-realistic & high-resolution images by user-defined prompts using Flux-schnell, in PyTorch & Gradio
PyTorch implementation of U-Net for segmentation of neural structures in electron microscopic stacks
Generate image by prompts using Stable Diffusion XL-turbo, in Pytorch & Gradio
Generate image by prompts using Stable Diffusion XL-lightning, in PyTorch & Gradio
A (clean) PyTorch implementation of CycleGAN on Horse2zebra dataset
Repositories
12A simple PyTorch implementation of conditional denoising diffusion probabilistic models (DDPM) on MNIST, Fashion-MNIST, and Sprite datasets
PyTorch implementation of U-Net for segmentation of neural structures in electron microscopic stacks
Generate photo-realistic & high-resolution images by user-defined prompts using Flux-schnell, in PyTorch & Gradio
Generate image by prompts using Stable Diffusion XL-turbo, in Pytorch & Gradio
A (clean) PyTorch implementation of CycleGAN on Horse2zebra dataset
Blur objects (in an image) via text prompts, using pretrained mobile-sam and OWLViT-v2, in PyTorch and Gradio
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Synthesize fast (4x upscaled) super-resolution images, in PyTorch & Gradio
Image generation by text prompts, using Stable Diffusion-v1-5, in PyTorch & Gradio
Generate image by prompts using Stable Diffusion XL-lightning, in PyTorch & Gradio
Object detection via text prompt using OWLv2 and Gradio app in PyTorch
Image segmentation using FastSAM and (negative and positive) prompts in PyTorch