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| import os | |
| import argparse | |
| from PIL import Image | |
| from luciddreamer import LucidDreamer | |
| if __name__ == "__main__": | |
| ### option | |
| parser = argparse.ArgumentParser(description='Arguments for LucidDreamer') | |
| # Input options | |
| parser.add_argument('--image', '-img', type=str, default='examples/Image015_animelakehouse.jpg', help='Input image for scene generation') | |
| parser.add_argument('--text', '-t', type=str, default='examples/Image015_animelakehouse.txt', help='Text prompt for scene generation') | |
| parser.add_argument('--neg_text', '-nt', type=str, default='', help='Negative text prompt for scene generation') | |
| # Camera options | |
| parser.add_argument('--campath_gen', '-cg', type=str, default='lookdown', choices=['lookdown', 'lookaround', 'rotate360'], help='Camera extrinsic trajectories for scene generation') | |
| parser.add_argument('--campath_render', '-cr', type=str, default='llff', choices=['back_and_forth', 'llff', 'headbanging'], help='Camera extrinsic trajectories for video rendering') | |
| # Inpainting options | |
| parser.add_argument('--model_name', type=str, default=None, help='Model name for inpainting(dreaming)') | |
| parser.add_argument('--seed', type=int, default=1, help='Manual seed for running Stable Diffusion inpainting') | |
| parser.add_argument('--diff_steps', type=int, default=50, help='Number of inference steps for running Stable Diffusion inpainting') | |
| # Save options | |
| parser.add_argument('--save_dir', '-s', type=str, default='', help='Save directory') | |
| args = parser.parse_args() | |
| ### input (example) | |
| rgb_cond = Image.open(args.image) | |
| if args.text.endswith('.txt'): | |
| with open(args.text, 'r') as f: | |
| txt_cond = f.readline() | |
| else: | |
| txt_cond = args.text | |
| if args.neg_text.endswith('.txt'): | |
| with open(args.neg_text, 'r') as f: | |
| neg_txt_cond = f.readline() | |
| else: | |
| neg_txt_cond = args.neg_text | |
| # Make default save directory if blank | |
| if args.save_dir == '': | |
| img_name = os.path.splitext(os.path.basename(args.image))[0] | |
| args.save_dir = f'./outputs/{img_name}_{args.campath_gen}_{args.seed}' | |
| if not os.path.exists(args.save_dir): | |
| os.makedirs(args.save_dir, exist_ok=True) | |
| if args.model_name is not None and args.model_name.endswith('safetensors'): | |
| print('Your model is saved in safetensor form. Converting to HF models...') | |
| from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt | |
| pipe = download_from_original_stable_diffusion_ckpt( | |
| checkpoint_path_or_dict=args.model_name, | |
| from_safetensors=True, | |
| device='cuda', | |
| ) | |
| pipe.save_pretrained('stablediffusion/', safe_serialization=False) | |
| args.model_name = f'stablediffusion/{args.model_name}' | |
| ld = LucidDreamer(for_gradio=False, save_dir=args.save_dir) | |
| ld.create(rgb_cond, txt_cond, neg_txt_cond, args.campath_gen, args.seed, args.diff_steps, model_name=args.model_name) | |
| ld.render_video(args.campath_render) | |