| import os |
| import torch |
| import numpy as np |
| import cv2 |
| from PIL import Image |
| from argparse import ArgumentParser |
| from model import DiffMorpherPipeline |
|
|
| parser = ArgumentParser() |
| parser.add_argument( |
| "--model_path", type=str, default="stabilityai/stable-diffusion-2-1-base", |
| help="Pretrained model to use (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--image_path_0", type=str, default="", |
| help="Path of the first image (default: %(default)s)") |
| parser.add_argument( |
| "--prompt_0", type=str, default="", |
| help="Prompt of the second image (default: %(default)s)") |
| parser.add_argument( |
| "--image_path_1", type=str, default="", |
| help="Path of the first image (default: %(default)s)") |
| parser.add_argument( |
| "--prompt_1", type=str, default="", |
| help="Prompt of the second image (default: %(default)s)") |
| parser.add_argument( |
| "--output_path", type=str, default="./results", |
| help="Path of the output image (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--save_lora_dir", type=str, default="./lora", |
| help="Path of the output lora directory (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--load_lora_path_0", type=str, default="", |
| help="Path of the lora directory of the first image (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--load_lora_path_1", type=str, default="", |
| help="Path of the lora directory of the second image (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--use_adain", action="store_true", |
| help="Use AdaIN (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--use_reschedule", action="store_true", |
| help="Use reschedule sampling (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--lamb", type=float, default=0.6, |
| help="Lambda for self-attention replacement (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--fix_lora_value", type=float, default=None, |
| help="Fix lora value (default: LoRA Interp., not fixed)" |
| ) |
| parser.add_argument( |
| "--save_inter", action="store_true", |
| help="Save intermediate results (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--num_frames", type=int, default=16, |
| help="Number of frames to generate (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--duration", type=int, default=100, |
| help="Duration of each frame (default: %(default)s ms)" |
| ) |
| parser.add_argument( |
| "--no_lora", action="store_true" |
| ) |
|
|
| args = parser.parse_args() |
|
|
| os.makedirs(args.output_path, exist_ok=True) |
| pipeline = DiffMorpherPipeline.from_pretrained( |
| args.model_path, torch_dtype=torch.float32) |
| pipeline.to("cuda") |
| images = pipeline( |
| img_path_0=args.image_path_0, |
| img_path_1=args.image_path_1, |
| prompt_0=args.prompt_0, |
| prompt_1=args.prompt_1, |
| save_lora_dir=args.save_lora_dir, |
| load_lora_path_0=args.load_lora_path_0, |
| load_lora_path_1=args.load_lora_path_1, |
| use_adain=args.use_adain, |
| use_reschedule=args.use_reschedule, |
| lamd=args.lamb, |
| output_path=args.output_path, |
| num_frames=args.num_frames, |
| fix_lora=args.fix_lora_value, |
| save_intermediates=args.save_inter, |
| use_lora=not args.no_lora |
| ) |
| images[0].save(f"{args.output_path}/output.gif", save_all=True, |
| append_images=images[1:], duration=args.duration, loop=0) |
|
|
