| from diffusers import DiffusionPipeline |
| import gradio as gr |
| import torch |
| import cv2 |
| import os |
|
|
| MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD') |
|
|
| device = "cuda" if torch.cuda.is_available() else "cpu" |
|
|
| pipe = DiffusionPipeline.from_pretrained( |
| "CompVis/stable-diffusion-v1-4", |
| use_auth_token=MY_SECRET_TOKEN, |
| |
| |
| safety_checker=None, |
| custom_pipeline="interpolate_stable_diffusion", |
| ).to(device) |
| pipe.enable_attention_slicing() |
|
|
| def run(prompt1, seed1, prompt2, seed2, prompt3, seed3): |
| |
| frame_filepaths = pipe.walk( |
| prompts=[prompt1, prompt2, prompt3], |
| seeds=[seed1, seed2, seed3], |
| num_interpolation_steps=16, |
| output_dir='./dreams', |
| batch_size=4, |
| height=512, |
| width=512, |
| guidance_scale=8.5, |
| num_inference_steps=50, |
| ) |
| print(frame_filepaths) |
| |
| frame = cv2.imread(frame_filepaths[0]) |
| height, width, layers = frame.shape |
| fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v') |
| video = cv2.VideoWriter("out.mp4", fourcc, 24, (width,height)) |
| for image in frame_filepaths: |
| |
| video.write(cv2.imread(image)) |
| |
| video.release() |
| cv2.destroyAllWindows() |
| |
| |
| return "out.mp4", frame_filepaths |
|
|
| with gr.Blocks() as demo: |
| with gr.Column(): |
| gr.HTML(''' |
| <h1 style='font-size: 2em;text-align:center;font-weigh:900;'> |
| Stable Diffusion Interpolation • Community pipeline |
| </h1> |
| <p style='text-align: center;'><br /> |
| This community pipeline returns a list of images saved under the folder as defined in output_dir. <br /> |
| You can use these images to create videos of stable diffusion. |
| </p> |
| |
| <p style='text-align: center;'> |
| This demo can be run on a GPU of at least 8GB VRAM and should take approximately 5 minutes.<br /> |
| — |
| </p> |
| |
| ''') |
| with gr.Row(): |
| with gr.Column(): |
| with gr.Column(): |
| with gr.Row(): |
| intpol_prompt_1 = gr.Textbox(lines=1, label="prompt 1") |
| seed1 = gr.Slider(label = "Seed 1", minimum = 0, maximum = 2147483647, step = 1, randomize = True) |
| with gr.Row(): |
| intpol_prompt_2 = gr.Textbox(lines=1, label="prompt 2") |
| seed2 = gr.Slider(label = "Seed 2", minimum = 0, maximum = 2147483647, step = 1, randomize = True) |
| with gr.Row(): |
| intpol_prompt_3 = gr.Textbox(lines=1, label="prompt 3") |
| seed3 = gr.Slider(label = "Seed 3", minimum = 0, maximum = 2147483647, step = 1, randomize = True) |
| intpol_run = gr.Button("Run Interpolation") |
| |
| with gr.Column(): |
| video_output = gr.Video(label="Generated video", show_label=True) |
| gallery_output = gr.Gallery(label="Generated images", show_label=False).style(grid=2, height="auto") |
| |
| intpol_run.click(run, inputs=[intpol_prompt_1, seed1, intpol_prompt_2, seed2, intpol_prompt_3, seed3], outputs=[video_output, gallery_output]) |
| |
| demo.launch() |
