mirror of
https://github.com/brycedrennan/imaginAIry
synced 2024-10-31 03:20:40 +00:00
84a73cb5a2
I tried it with the DDIM sampler and it didn't work.
Probably need to use the k-diffusion sampler with it
from a846393251/find_noise.py
needs https://github.com/crowsonkb/k-diffusion
177 lines
4.5 KiB
Python
177 lines
4.5 KiB
Python
import logging.config
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import click
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from imaginairy.api import load_model
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logger = logging.getLogger(__name__)
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def configure_logging(level="INFO"):
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fmt = "%(message)s"
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if level == "DEBUG":
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fmt = "%(asctime)s [%(levelname)s] %(name)s:%(lineno)d: %(message)s"
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LOGGING_CONFIG = {
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"version": 1,
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"disable_existing_loggers": True,
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"formatters": {
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"standard": {"format": fmt},
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},
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"handlers": {
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"default": {
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"level": "INFO",
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"formatter": "standard",
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"class": "logging.StreamHandler",
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"stream": "ext://sys.stdout", # Default is stderr
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},
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},
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"loggers": {
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"": { # root logger
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"handlers": ["default"],
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"level": "WARNING",
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"propagate": False,
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},
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"imaginairy": {"handlers": ["default"], "level": level, "propagate": False},
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"transformers.modeling_utils": {
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"handlers": ["default"],
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"level": "ERROR",
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"propagate": False,
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},
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},
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}
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logging.config.dictConfig(LOGGING_CONFIG)
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@click.command()
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@click.argument("prompt_texts", nargs=-1)
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@click.option(
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"--prompt-strength",
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default=7.5,
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show_default=True,
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help="How closely to follow the prompt. Image looks unnatural at higher values",
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)
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@click.option(
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"--init-image",
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help="Starting image.",
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)
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@click.option(
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"--init-image-strength",
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default=0.3,
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help="Starting image.",
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)
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@click.option("--outdir", default="./outputs", help="where to write results to")
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@click.option(
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"-r",
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"--repeats",
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default=1,
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type=int,
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help="How many times to repeat the renders. If you provide two prompts and --repeat=3 then six images will be generated",
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)
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@click.option(
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"-h",
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"--height",
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default=512,
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type=int,
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help="image height. should be multiple of 64",
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)
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@click.option(
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"-w", "--width", default=512, type=int, help="image width. should be multiple of 64"
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)
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@click.option(
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"--steps",
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default=40,
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type=int,
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show_default=True,
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help="How many diffusion steps to run. More steps, more detail, but with diminishing returns",
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)
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@click.option(
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"--seed",
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default=None,
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type=int,
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help="What seed to use for randomness. Allows reproducible image renders",
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)
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@click.option(
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"--sampler-type",
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default="PLMS",
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type=click.Choice(["PLMS", "DDIM"]),
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help="What sampling strategy to use",
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)
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@click.option("--ddim-eta", default=0.0, type=float)
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@click.option(
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"--log-level",
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default="INFO",
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type=click.Choice(["DEBUG", "INFO", "WARNING", "ERROR"]),
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help="What level of logs to show.",
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)
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@click.option(
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"--show-work",
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default=["none"],
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type=click.Choice(["none", "images", "video"]),
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multiple=True,
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help="Make a video showing the image being created",
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)
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@click.option(
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"--tile",
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is_flag=True,
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help="Any images rendered will be tileable. Unfortunately cannot be controlled at the per-image level yet",
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)
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def imagine_cmd(
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prompt_texts,
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prompt_strength,
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init_image,
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init_image_strength,
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outdir,
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repeats,
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height,
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width,
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steps,
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seed,
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sampler_type,
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ddim_eta,
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log_level,
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show_work,
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tile,
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):
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"""Render an image"""
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configure_logging(log_level)
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from imaginairy.api import imagine_image_files
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from imaginairy.schema import ImaginePrompt
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total_image_count = len(prompt_texts) * repeats
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logger.info(
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f"🤖🧠 received {len(prompt_texts)} prompt(s) and will repeat them {repeats} times to create {total_image_count} images."
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)
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prompts = []
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load_model(tile_mode=tile)
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for _ in range(repeats):
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for prompt_text in prompt_texts:
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prompt = ImaginePrompt(
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prompt_text,
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prompt_strength=prompt_strength,
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init_image=init_image,
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init_image_strength=init_image_strength,
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seed=seed,
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sampler_type=sampler_type,
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steps=steps,
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height=height,
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width=width,
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upscale=False,
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fix_faces=False,
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)
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prompts.append(prompt)
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imagine_image_files(
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prompts,
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outdir=outdir,
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ddim_eta=ddim_eta,
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record_step_images="images" in show_work,
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tile_mode=tile,
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)
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if __name__ == "__main__":
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imagine_cmd() # noqa
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