Update frame_gen.py

frame_gen.py

@@ -0,0 +1,49 @@
+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):
+    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++
+
+    
+    # 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(1,11):
+        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)