Delete frame_gen.py

frame_gen.py

@@ -1,50 +0,0 @@
-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)