""" LongCat Video Continuation (VC) Example Script This script demonstrates LongCat VC inference using the FastVideo Python API. LongCat VC takes an input video and generates a continuation of it. It runs both basic generation (50 steps) and distill+refine generation (16 steps distill + 50 steps refinement to 720p). Usage: python examples/inference/basic/basic_longcat_vc.py Prerequisites: - Ensure the input video exists at assets/motorcycle.mp4 (or provide your own video) """ import glob import os from fastvideo import VideoGenerator # Common prompts and settings matching the shell script examples PROMPT = ("A person rides a motorcycle along a long, straight road that stretches between " "a body of water and a forested hillside. The rider steadily accelerates, keeping " "the motorcycle centered between the guardrails, while the scenery passes by on " "both sides. The video captures the journey from the rider's perspective, emphasizing " "the sense of motion and adventure.") NEGATIVE_PROMPT = ("Bright tones, overexposed, static, blurred details, subtitles, style, works, " "paintings, images, static, overall gray, worst quality, low quality, JPEG compression " "residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, " "deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, " "three legs, many people in the background, walking backwards") # Input video path VIDEO_PATH = "assets/motorcycle.mp4" # Number of conditioning frames from the input video NUM_COND_FRAMES = 13 SEED = 42 def basic_generation(): """ Run basic LongCat VC generation (50 steps at 480p). This uses the full 50-step denoising process for highest quality. """ print("=" * 60) print("LongCat VC: Basic Generation (50 steps, 480p)") print("=" * 60) # Check if video exists if not os.path.exists(VIDEO_PATH): raise FileNotFoundError(f"Video not found at {VIDEO_PATH}. " "Please provide a valid video path.") generator = VideoGenerator.from_pretrained( "FastVideo/LongCat-Video-VC-Diffusers", num_gpus=1, use_fsdp_inference=False, # set to True if GPU is out of memory dit_cpu_offload=False, vae_cpu_offload=True, text_encoder_cpu_offload=True, pin_cpu_memory=False, enable_bsa=False, ) output_path = "outputs_video/longcat_vc_basic" generator.generate_video( prompt=PROMPT, negative_prompt=NEGATIVE_PROMPT, video_path=VIDEO_PATH, num_cond_frames=NUM_COND_FRAMES, output_path=output_path, save_video=True, height=480, width=832, num_frames=93, num_inference_steps=50, fps=15, guidance_scale=4.0, seed=SEED, ) print(f"\nBasic generation complete! Video saved to: {output_path}") generator.shutdown() def distill_refine_generation(): """ Run LongCat VC with distill+refine pipeline (16 steps + refinement to 720p). This uses the distilled LoRA for fast 480p generation (16 steps), then refines to 720p using the refinement LoRA with BSA enabled. """ print("\n" + "=" * 60) print("LongCat VC: Distill + Refine Pipeline") print("=" * 60) # Check if video exists if not os.path.exists(VIDEO_PATH): raise FileNotFoundError(f"Video not found at {VIDEO_PATH}. " "Please provide a valid video path.") # Stage 1: Distilled generation (16 steps at 480p) print("\n[Stage 1] Distilled generation (16 steps, 480p)") print("-" * 40) generator = VideoGenerator.from_pretrained( "FastVideo/LongCat-Video-VC-Diffusers", num_gpus=1, use_fsdp_inference=True, dit_cpu_offload=False, vae_cpu_offload=True, text_encoder_cpu_offload=True, pin_cpu_memory=False, enable_bsa=False, lora_path="FastVideo/LongCat-Video-T2V-Distilled-LoRA", lora_nickname="distilled", ) distill_output_path = "outputs_video/longcat_vc_distill" generator.generate_video( prompt=PROMPT, negative_prompt=NEGATIVE_PROMPT, video_path=VIDEO_PATH, num_cond_frames=NUM_COND_FRAMES, output_path=distill_output_path, save_video=True, height=480, width=832, num_frames=93, num_inference_steps=16, fps=15, guidance_scale=1.0, seed=SEED, ) print(f"Distilled generation complete! Video saved to: {distill_output_path}") generator.shutdown() # Stage 2: Refinement (480p -> 720p) print("\n[Stage 2] Refinement (480p -> 720p with BSA)") print("-" * 40) # Find the actual saved video file from stage 1 video_files = glob.glob(os.path.join(distill_output_path, "*.mp4")) if not video_files: raise FileNotFoundError(f"No video file found in {distill_output_path}") # Use the most recently created video file distill_video_path = max(video_files, key=os.path.getmtime) print(f"Using stage 1 video: {distill_video_path}") # Create a new generator with refinement LoRA and BSA enabled # Note: Refinement uses the T2V model (not VC) since it's upscaling the generated video refine_generator = VideoGenerator.from_pretrained( "FastVideo/LongCat-Video-T2V-Diffusers", num_gpus=1, use_fsdp_inference=True, dit_cpu_offload=True, vae_cpu_offload=True, text_encoder_cpu_offload=True, pin_cpu_memory=False, enable_bsa=True, bsa_sparsity=0.875, bsa_chunk_q=[4, 4, 8], bsa_chunk_k=[4, 4, 8], lora_path="FastVideo/LongCat-Video-T2V-Refinement-LoRA", lora_nickname="refinement", ) refine_output_path = "outputs_video/longcat_vc_refine_720p" refine_generator.generate_video( prompt=PROMPT, negative_prompt=NEGATIVE_PROMPT, output_path=refine_output_path, save_video=True, refine_from=distill_video_path, t_thresh=0.5, spatial_refine_only=False, num_cond_frames=0, # For refinement, no conditioning frames height=720, width=1280, num_inference_steps=50, fps=30, guidance_scale=1.0, seed=SEED, ) print(f"Refinement complete! Video saved to: {refine_output_path}") refine_generator.shutdown() def main(): """Run both basic and distill+refine generation pipelines.""" print("\n" + "=" * 60) print("LongCat Video Continuation Example") print("=" * 60 + "\n") # Run basic generation basic_generation() # Run distill+refine pipeline distill_refine_generation() print("\n" + "=" * 60) print("All generations complete!") print("=" * 60) if __name__ == "__main__": main()