Testing stable-diffusion-xl 0.9 generation pipelines using simple random prompts (Script needs official HF repo access permission to work)

sdxl_09_gen_test.py

from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
import torch


#////////////////////////////////////////////////////////////////
guidance_scale=7.5
steps_base=50
steps_refiner=50
width=1024
height=1024
base_model_id_str = "sdxl_09"
prompt_suffix = ", Very detailed, clean, high quality, sharp image"
neg_prompt = "text, watermark, grainy, blurry, unfocused, nsfw, naked, nude, noisy image, deformed, distorted, pixelated"
#////////////////////////////////////////////////////////////////
pipe1 = None
pipe2 = None
#////////////////////////////////////////////////////////////////

def load():
    global pipe1, pipe2

    # scheduler = DPMSolverMultistepScheduler(
    #     beta_start=0.00085,
    #     beta_end=0.012,
    #     beta_schedule="scaled_linear",
    #     num_train_timesteps=1000,
    #     trained_betas=None,
    #     thresholding=False,
    #     algorithm_type="dpmsolver++",
    #     solver_type="midpoint",
    #     lower_order_final=True,
    # )

    pipe1 = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16")#, scheduler=scheduler)
    pipe1.to("cuda")
    pipe1.enable_xformers_memory_efficient_attention()
    pipe2 = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16")
    pipe2.to("cuda")
    pipe2.enable_xformers_memory_efficient_attention()

def generate(prompt, file_prefix ,samples, seed):
    global pipe1, pipe2

    torch.manual_seed(seed)
    prompt += prompt_suffix
    base_model_latents = pipe1([prompt] * samples, negative_prompt = [neg_prompt] * samples, num_inference_steps=steps_base, guidance_scale=guidance_scale, height=height, width=width, output_type="latent")["images"]
    torch.manual_seed(seed)
    refiner_model_images = pipe2([prompt] * samples, negative_prompt = [neg_prompt] * samples, num_inference_steps=steps_refiner, image=base_model_latents)["images"]
    for idx, image in enumerate(refiner_model_images):
        image.save(f"{file_prefix}-{idx}-{seed}--{width}x{height}--{guidance_scale}--{base_model_id_str}.jpg")

def main():
    load()

    generate("A livingroom", "01_LivingRoom", 2, 7777)
    generate("A nice town", "02_NiceTown", 2, 555)
    generate("Nicolas Cage, in \"The Minions\" movie", "03_NicolasCage", 4, 42)
    generate("Gal Gadot as wonderwoman", "04_GalGadot", 2, 42)
    generate("Marge Simpson", "05_MargeSimpson", 2, 42)
    generate("A beautiful woman", "06_BeautifulWoman", 2, 42)
    generate("A magical landscape", "07_MagicalLandscape", 4, 42)
    generate("Cute dog, will lick you to sleep", "08_CuteDog", 2, 42)
    generate("An oil on canvas portrait of Snoop Dogg, Mark Ryden", "09_SnoopDog", 2, 777)
    generate("A flemish baroque painting of Kermit from the muppet show", "10_KermitFlemishBaroque", 2, 42)
    generate("Gal Gadot in Avatar", "11_GalGadotAvatar", 2, 777)
    generate("Ninja turtles, Naoto Hattori", "12_TMNT", 2, 312)
    generate("An anime town", "12_AnimeTown", 2, 777)
    generate("Family guy taking selfies at the beach", "13_FamilyGuy", 2, 555)
    generate("Pikachu as Rick and morty, Eric Wallis", "14_PikachuRnM", 2, 777)
    generate("Pikachu as Spongebob, Eric Wallis", "15_PikachuSpongeBob", 2, 42)
    generate("An oil painting of Miss. Piggy from the muppets as the Mona Lisa", "16_MsPiggyMonaLisa", 2, 42)
    generate("Rick Sanchez from the TV show \"Rick and Morty\"", "17_RickSanchez", 2, 42)
    generate("An paiting of Southpark with rainbow", "18_Southpark", 2, 777)
    generate("An oil painting of Phineas and Pherb hamering on a new machine, Eric Wallis", "19_PhineasPherb", 2, 777)
    generate("Bender, Saturno Butto", "20_Bender", 2, 777)
    generate("A psychedelic image of Bojack Horseman", "21_Bojack", 2, 777)
    generate("A movie poster for Gravity Falls Cthulhu stories", "22_GravityFalls", 2, 777)
    generate("A vibrant oil painting portrait of She-Ra", "23_Shira", 2, 512)
#

if __name__ == '__main__':
    main()