Create multimodal_pipeline.py

multimodal_pipeline.py

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+import torch
+from diffusers import DiffusionPipeline, StableDiffusionImageVariationPipeline
+from PIL import Image
+import numpy as np
+import cv2
+
+class BootyShakerPipeline:
+    def __init__(self):
+        self.txt2video_pipe = DiffusionPipeline.from_pretrained("ChromiumPlutoniumAI/BootyShakerAI")
+        self.img2video_pipe = StableDiffusionImageVariationPipeline.from_pretrained("ChromiumPlutoniumAI/BootyShakerAI")
+        self.device = "cuda" if torch.cuda.is_available() else "cpu"
+        
+    def generate_from_text(self, prompt, num_frames=16, fps=8):
+        video = self.txt2video_pipe(
+            prompt,
+            num_inference_steps=50,
+            num_frames=num_frames
+        ).frames
+        return self.frames_to_video(video, fps)
+        
+    def generate_from_image(self, image, num_frames=16, fps=8):
+        if isinstance(image, str):
+            image = Image.open(image)
+        video = self.img2video_pipe(
+            image,
+            num_inference_steps=50,
+            num_frames=num_frames
+        ).frames
+        return self.frames_to_video(video, fps)
+        
+    def apply_alterations(self, video, style="bounce"):
+        styles = {
+            "bounce": self.bounce_effect,
+            "wave": self.wave_effect,
+            "shake": self.shake_effect
+        }
+        return styles[style](video)
+    
+    @staticmethod
+    def frames_to_video(frames, fps):
+        output_file = "output.mp4"
+        writer = cv2.VideoWriter(
+            output_file,
+            cv2.VideoWriter_fourcc(*"mp4v"),
+            fps,
+            (frames[0].shape[1], frames[0].shape[0])
+        )
+        for frame in frames:
+            writer.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))
+        writer.release()
+        return output_file