Video Generation from text

Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation

Setup

Requirements

pip install -r requirements.txt

Weights

[Stable Diffusion] Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. The pre-trained Stable Diffusion models can be downloaded from Hugging Face (e.g., Stable Diffusion v1-4, v2-1). You can also use fine-tuned Stable Diffusion models trained on different styles (e.g, Modern Disney, Redshift, etc.).

[DreamBooth] DreamBooth is a method to personalize text-to-image models like Stable Diffusion given just a few images (3~5 images) of a subject. Tuning a video on DreamBooth models allows personalized text-to-video generation of a specific subject. There are some public DreamBooth models available on Hugging Face (e.g., mr-potato-head). You can also train your own DreamBooth model following this training example.

Usage

Training

To fine-tune the text-to-image diffusion models for text-to-video generation, run this command:

accelerate launch train_tuneavideo.py --config="configs/man-skiing.yaml"

Inference

Once the training is done, run inference:

from tuneavideo.pipelines.pipeline_tuneavideo import TuneAVideoPipeline
from tuneavideo.models.unet import UNet3DConditionModel
from tuneavideo.util import save_videos_grid
import torch

pretrained_model_path = "./checkpoints/stable-diffusion-v1-4"
my_model_path = "./outputs/man-skiing"
unet = UNet3DConditionModel.from_pretrained(my_model_path, subfolder='unet', torch_dtype=torch.float16).to('cuda')
pipe = TuneAVideoPipeline.from_pretrained(pretrained_model_path, unet=unet, torch_dtype=torch.float16).to("cuda")
pipe.enable_xformers_memory_efficient_attention()
pipe.enable_vae_slicing()

prompt = "spider man is skiing"
ddim_inv_latent = torch.load(f"{my_model_path}/inv_latents/ddim_latent-500.pt").to(torch.float16)
video = pipe(prompt, latents=ddim_inv_latent, video_length=24, height=512, width=512, num_inference_steps=50, guidance_scale=12.5).videos

save_videos_grid(video, f"./{prompt}.gif")

Results

Pretrained T2I (Stable Diffusion)

Input Video	Output Video

"A man is skiing"	"Wonder Woman, is skiing"	"A little girl is skiing "

"A rabbit is eating a watermelon"	"A cat is eating a watermelon on the table"	"A puppy is eating a cheeseburger on the table, comic style"

"A jeep car is moving on the road"	"A car is moving on the road, cartoon style"	"A car is moving on the snow"

saba99/Video-Genrator-text-to-video