Spaces:
Runtime error
Runtime error
File size: 4,557 Bytes
7dd5ec2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 |
import gradio as gr
from text_to_video import model_t2v_fun,setup_seed
from omegaconf import OmegaConf
import torch
import imageio
import os
import cv2
import torchvision
config_path = "./base/configs/sample.yaml"
args = OmegaConf.load("./base/configs/sample.yaml")
device = "cuda" if torch.cuda.is_available() else "cpu"
# ------- get model ---------------
model_t2V = model_t2v_fun(args)
model_t2V.to(device)
if device == "cuda":
model_t2V.enable_xformers_memory_efficient_attention()
# model_t2V.enable_xformers_memory_efficient_attention()
css = """
h1 {
text-align: center;
}
#component-0 {
max-width: 730px;
margin: auto;
}
"""
def infer(prompt, seed_inp, ddim_steps):
setup_seed(seed_inp)
videos = model_t2V(prompt, video_length=16, height = 320, width= 512, num_inference_steps=ddim_steps, guidance_scale=7).video
print(videos[0].shape)
if not os.path.exists(args.output_folder):
os.mkdir(args.output_folder)
torchvision.io.write_video(args.output_folder + prompt.replace(' ', '_') + '-.mp4', videos[0], fps=8)
# imageio.mimwrite(args.output_folder + prompt.replace(' ', '_') + '.mp4', videos[0], fps=8)
# video = cv2.VideoCapture(args.output_folder + prompt.replace(' ', '_') + '.mp4')
# video = imageio.get_reader(args.output_folder + prompt.replace(' ', '_') + '.mp4', 'ffmpeg')
# video = model_t2V(prompt, seed_inp, ddim_steps)
return args.output_folder + prompt.replace(' ', '_') + '-.mp4'
print(1)
# def clean():
# return gr.Image.update(value=None, visible=False), gr.Video.update(value=None)
def clean():
return gr.Video.update(value=None)
title = """
<div style="text-align: center; max-width: 700px; margin: 0 auto;">
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
"
>
<h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
Intern·Vchitect (Text-to-Video)
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
Apply Intern·Vchitect to generate a video
</p>
</div>
"""
# print(1)
with gr.Blocks(css='style.css') as demo:
gr.Markdown("<font color=red size=10><center>LaVie</center></font>")
with gr.Row(elem_id="col-container"):
with gr.Column():
prompt = gr.Textbox(value="a teddy bear walking on the street", label="Prompt", placeholder="enter prompt", show_label=True, elem_id="prompt-in", min_width=200, lines=2)
ddim_steps = gr.Slider(label='Steps', minimum=50, maximum=300, value=50, step=1)
seed_inp = gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1, value=400, elem_id="seed-in")
# with gr.Row():
# # control_task = gr.Dropdown(label="Task", choices=["Text-2-video", "Image-2-video"], value="Text-2-video", multiselect=False, elem_id="controltask-in")
# ddim_steps = gr.Slider(label='Steps', minimum=50, maximum=300, value=250, step=1)
# seed_inp = gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1, value=123456, elem_id="seed-in")
# ddim_steps = gr.Slider(label='Steps', minimum=50, maximum=300, value=250, step=1)
with gr.Column():
submit_btn = gr.Button("Generate video")
clean_btn = gr.Button("Clean video")
# submit_btn = gr.Button("Generate video", size='sm')
# video_out = gr.Video(label="Video result", elem_id="video-output", height=320, width=512)
video_out = gr.Video(label="Video result", elem_id="video-output")
# with gr.Row():
# video_out = gr.Video(label="Video result", elem_id="video-output", height=320, width=512)
# submit_btn = gr.Button("Generate video", size='sm')
# video_out = gr.Video(label="Video result", elem_id="video-output", height=320, width=512)
inputs = [prompt, seed_inp, ddim_steps]
outputs = [video_out]
# control_task.change(change_task_options, inputs=[control_task], outputs=[canny_opt, hough_opt, normal_opt], queue=False)
# submit_btn.click(clean, inputs=[], outputs=[video_out], queue=False)
clean_btn.click(clean, inputs=[], outputs=[video_out], queue=False)
submit_btn.click(infer, inputs, outputs)
# share_button.click(None, [], [], _js=share_js)
print(2)
demo.queue(max_size=12).launch(server_name="0.0.0.0", server_port=7860)
|