mirror of
https://github.com/brycedrennan/imaginAIry
synced 2024-10-31 03:20:40 +00:00
340a90bacd
Addresses #40
292 lines
7.8 KiB
Python
292 lines
7.8 KiB
Python
import logging.config
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import click
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from click_shell import shell
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from imaginairy import LazyLoadingImage, generate_caption
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from imaginairy.api import imagine_image_files
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from imaginairy.samplers.base import SAMPLER_TYPE_OPTIONS
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from imaginairy.schema import ImaginePrompt
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from imaginairy.suppress_logs import suppress_annoying_logs_and_warnings
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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. filepath or url",
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)
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@click.option(
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"--init-image-strength",
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default=0.6,
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show_default=True,
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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("--upscale", is_flag=True)
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@click.option("--fix-faces", is_flag=True)
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@click.option(
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"--fix-faces-fidelity",
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default=None,
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help="How faithful to the original should face enhancement be. 1 = best fidelity, 0 = best looking face",
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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(SAMPLER_TYPE_OPTIONS),
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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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"--quiet",
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"-q",
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is_flag=True,
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help="Suppress logs. Alias of `--log-level ERROR`",
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)
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@click.option(
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"--show-work",
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default=False,
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is_flag=True,
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help="Output a debug images to `steps` folder.",
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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.",
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)
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@click.option(
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"--mask-image",
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help="A mask to use for inpainting. White gets painted, Black is left alone.",
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)
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@click.option(
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"--mask-prompt",
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help=(
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"Describe what you want masked and the AI will mask it for you. "
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"You can describe complex masks with AND, OR, NOT keywords and parentheses. "
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"The strength of each mask can be modified with {*1.5} notation. \n\n"
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"Examples: \n"
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"car AND (wheels{*1.1} OR trunk OR engine OR windows OR headlights) AND NOT (truck OR headlights){*10}\n"
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"fruit|fruit stem"
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),
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)
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@click.option(
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"--mask-mode",
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default="replace",
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type=click.Choice(["keep", "replace"]),
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help="Should we replace the masked area or keep it?",
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)
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@click.option(
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"--mask-modify-original",
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default=True,
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is_flag=True,
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help="After the inpainting is done, apply the changes to a copy of the original image",
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)
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@click.option(
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"--caption",
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default=False,
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is_flag=True,
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help="Generate a text description of the generated image",
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)
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@click.option(
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"--precision",
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help="evaluate at this precision",
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type=click.Choice(["full", "autocast"]),
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default="autocast",
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)
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@click.option(
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"--model-weights-path",
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help="path to model weights file. by default we use stable diffusion 1.4",
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type=click.Path(exists=True),
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default=None,
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)
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@click.pass_context
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def imagine_cmd(
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ctx,
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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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upscale,
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fix_faces,
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fix_faces_fidelity,
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sampler_type,
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ddim_eta,
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log_level,
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quiet,
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show_work,
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tile,
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mask_image,
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mask_prompt,
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mask_mode,
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mask_modify_original,
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caption,
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precision,
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model_weights_path,
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):
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"""Have the AI generate images. alias:imagine"""
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if ctx.invoked_subcommand is not None:
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return
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suppress_annoying_logs_and_warnings()
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if quiet:
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log_level = "ERROR"
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configure_logging(log_level)
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total_image_count = len(prompt_texts) * repeats
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logger.info(
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f"🤖🧠 imaginAIry 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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if init_image and init_image.startswith("http"):
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init_image = LazyLoadingImage(url=init_image)
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if mask_image and mask_image.startswith("http"):
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mask_image = LazyLoadingImage(url=mask_image)
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if fix_faces_fidelity is not None:
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fix_faces_fidelity = float(fix_faces_fidelity)
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prompts = []
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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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mask_image=mask_image,
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mask_prompt=mask_prompt,
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mask_mode=mask_mode,
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mask_modify_original=mask_modify_original,
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upscale=upscale,
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fix_faces=fix_faces,
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fix_faces_fidelity=fix_faces_fidelity,
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tile_mode=tile,
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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=show_work,
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output_file_extension="jpg",
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print_caption=caption,
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precision=precision,
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model_weights_path=model_weights_path,
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)
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@shell(prompt="imaginAIry> ", intro="Starting imaginAIry...")
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def aimg():
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pass
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@click.argument("image_filepaths", nargs=-1)
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@aimg.command()
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def describe(image_filepaths):
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"""Generate text descriptions of images"""
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imgs = []
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for p in image_filepaths:
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if p.startswith("http"):
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img = LazyLoadingImage(url=p)
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else:
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img = LazyLoadingImage(filepath=p)
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imgs.append(img)
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for img in imgs:
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print(generate_caption(img.copy()))
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aimg.add_command(imagine_cmd, name="imagine")
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if __name__ == "__main__":
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imagine_cmd() # noqa
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