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Running
on
Zero
Running
on
Zero
import spaces | |
import gradio as gr | |
import argparse | |
import sys | |
import time | |
import os | |
import random | |
from skyreelsinfer.offload import OffloadConfig | |
from skyreelsinfer import TaskType | |
from skyreelsinfer.skyreels_video_infer import SkyReelsVideoSingleGpuInfer | |
from diffusers.utils import export_to_video | |
from diffusers.utils import load_image | |
from PIL import Image | |
#predictor = None | |
#task_type = None | |
os.putenv("TOKENIZERS_PARALLELISM","False") | |
#@spaces.GPU(duration=120) | |
def init_predictor(): | |
global predictor | |
predictor = SkyReelsVideoSingleGpuInfer( | |
task_type= TaskType.I2V, | |
model_id="Skywork/SkyReels-V1-Hunyuan-I2V", | |
quant_model=False, | |
is_offload=False, | |
offload_config=OffloadConfig( | |
high_cpu_memory=True, | |
parameters_level=True, | |
compiler_transformer=False, | |
) | |
) | |
def generate_video(prompt, seed, image=None): | |
print(f"image:{type(image)}") | |
if seed == -1: | |
random.seed(time.time()) | |
seed = int(random.randrange(4294967294)) | |
kwargs = { | |
"prompt": prompt, | |
"height": 320, | |
"width": 320, | |
"num_frames": 64, | |
"num_inference_steps": 10, | |
"seed": seed, | |
"guidance_scale": 6.0, | |
"embedded_guidance_scale": 1.0, | |
"negative_prompt": "Aerial view, aerial view, overexposed, low quality, deformation, a poor composition, bad hands, bad teeth, bad eyes, bad limbs, distortion", | |
"cfg_for": False, | |
} | |
assert image is not None, "please input image" | |
kwargs["image"] = load_image(image=image).resize((320,320), Image.LANCZOS) | |
#global predictor | |
output = predictor.inference(kwargs) | |
save_dir = f"./result" | |
os.makedirs(save_dir, exist_ok=True) | |
video_out_file = f"{save_dir}/{prompt[:100].replace('/','')}_{seed}.mp4" | |
print(f"generate video, local path: {video_out_file}") | |
export_to_video(output, video_out_file, fps=24) | |
return video_out_file | |
def create_gradio_interface(): | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
image = gr.Image(label="Upload Image", type="filepath") | |
prompt = gr.Textbox(label="Input Prompt") | |
seed = gr.Number(label="Random Seed", value=-1) | |
submit_button = gr.Button("Generate Video") | |
output_video = gr.Video(label="Generated Video") | |
submit_button.click( | |
fn=generate_video, | |
inputs=[prompt, seed, image], | |
outputs=[output_video], | |
) | |
return demo | |
#init_predictor() | |
if __name__ == "__main__": | |
#import multiprocessing | |
#multiprocessing.freeze_support() | |
init_predictor() | |
demo = create_gradio_interface() | |
demo.launch() |