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2dcc9a2 7209751 2dcc9a2 b9e43cc 2dcc9a2 c17de37 2dcc9a2 b9674fb 2dcc9a2 | 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 | import torch
from diffusers import AnimateDiffPipeline, DDIMScheduler, MotionAdapter
from diffusers.utils import export_to_gif
from moviepy.editor import VideoFileClip, concatenate_videoclips
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16)
pipeline = AnimateDiffPipeline.from_pretrained("emilianJR/epiCRealism", motion_adapter=adapter, torch_dtype=torch.float16)
scheduler = DDIMScheduler.from_pretrained(
"emilianJR/epiCRealism",
subfolder="scheduler",
clip_sample=False,
timestep_spacing="linspace",
beta_schedule="linear",
steps_offset=1,
)
pipeline.scheduler = scheduler
pipeline.enable_vae_slicing()
#pipeline.enable_model_cpu_offload()
def gen_movie(frames_desc):
frames_desc = frames_desc[0]
x = 1
for frame_description in frames_desc:
output = pipeline(
prompt="frame_description",
negative_prompt="high resolution",
num_frames=16,
guidance_scale=7.5,
num_inference_steps=50,
generator=torch.Generator("cpu").manual_seed(0),
)
frames = output.frames[0]
export_to_gif(frames, f'animation{x}.gif')
x += 1
# List to store VideoFileClip objects for each input GIF
video_clips = []
# Load each input GIF file and append it to the list
for x in range(1,2):
video_clips.append(VideoFileClip(f'animation{x}.gif'))
# Concatenate the video clips to create a single video
final_clip = concatenate_videoclips(video_clips)
# Export the final video to a new MP4 file
final_clip.write_videofile("combined_video.mp4", codec="libx264", fps=24)
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