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https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
adjusted handling of from_file
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commit
8b9a520c5c
14
README.md
14
README.md
@ -185,7 +185,13 @@ innovative packaging for a squid's dinner -S137038382
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Then pass this file's name to dream.py when you invoke it:
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~~~~
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(ldm) ~/stable-diffusion$ python3 scripts/dream.py --from_file="path/to/prompts.txt"
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(ldm) ~/stable-diffusion$ python3 scripts/dream.py --from_file "path/to/prompts.txt"
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~~~~
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You may read a series of prompts from standard input by providing a filename of "-":
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~~~~
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(ldm) ~/stable-diffusion$ echo "a beautiful day" | python3 scripts/dream.py --from_file -
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~~~~
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## Shortcut for reusing seeds from the previous command
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@ -298,6 +304,10 @@ repository and associated paper for details and limitations.
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## Changes
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* v1.12 (28 August 2022)
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* Improved file handling, including ability to read prompts from standard input.
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(kudos to [Yunsaki](https://github.com/yunsaki)
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* v1.11 (26 August 2022)
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* NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
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* You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc.
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@ -601,7 +611,7 @@ to send me an email if you use and like the script.
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[Peter Kowalczyk](https://github.com/slix), [Henry Harrison](https://github.com/hwharrison),
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[xraxra](https://github.com/xraxra), [bmaltais](https://github.com/bmaltais), [Sean McLellan](https://github.com/Oceanswave),
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[nicolai256](https://github.com/nicolai256), [Benjamin Warner](https://github.com/warner-benjamin),
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[tildebyte](https://github.com/tildebyte),
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[tildebyte](https://github.com/tildebyte),[yunsaki](https://github.com/yunsaki)
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and [Tesseract Cat](https://github.com/TesseractCat)
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@ -548,13 +548,15 @@ class T2I:
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)
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else:
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print(
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'Using half precision math. Call with --full_precision to use slower but more accurate full precision.'
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'Using half precision math. Call with --full_precision to use more accurate but VRAM-intensive full precision.'
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)
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model.half()
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return model
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def _load_img(self, path):
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image = Image.open(path).convert('RGB')
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with Image.open(path) as img:
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image = img.convert("RGB")
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w, h = image.size
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print(f'loaded input image of size ({w}, {h}) from {path}')
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w, h = map(
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@ -64,13 +64,19 @@ def main():
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# gets rid of annoying messages about random seed
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logging.getLogger('pytorch_lightning').setLevel(logging.ERROR)
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# load the infile as a list of lines
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infile = None
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try:
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if opt.infile is not None:
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infile = open(opt.infile, 'r')
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except FileNotFoundError as e:
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print(e)
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exit(-1)
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if opt.infile:
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try:
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if os.path.isfile(opt.infile):
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infile = open(opt.infile,'r')
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elif opt.infile=='-': # stdin
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infile = sys.stdin
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else:
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raise FileNotFoundError(f'{opt.infile} not found.')
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except (FileNotFoundError,IOError) as e:
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print(f'{e}. Aborting.')
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sys.exit(-1)
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# preload the model
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t2i.load_model()
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@ -110,34 +116,31 @@ def main():
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print('Error loading GFPGAN:', file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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print(
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"\n* Initialization done! Awaiting your command (-h for help, 'q' to quit, 'cd' to change output dir, 'pwd' to print output dir)..."
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)
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if not infile:
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print(
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"\n* Initialization done! Awaiting your command (-h for help, 'q' to quit, 'cd' to change output dir, 'pwd' to print output dir)..."
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)
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log_path = os.path.join(opt.outdir, 'dream_log.txt')
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with open(log_path, 'a') as log:
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cmd_parser = create_cmd_parser()
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main_loop(t2i, opt.outdir, cmd_parser, log, infile)
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log.close()
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if infile:
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infile.close()
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cmd_parser = create_cmd_parser()
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main_loop(t2i, opt.outdir, cmd_parser, log_path, infile)
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def main_loop(t2i, outdir, parser, log, infile):
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def main_loop(t2i, outdir, parser, log_path, infile):
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"""prompt/read/execute loop"""
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done = False
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last_seeds = []
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while not done:
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try:
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command = infile.readline() if infile else input('dream> ')
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command = get_next_command(infile)
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except EOFError:
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done = True
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break
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if infile and len(command) == 0:
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done = True
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break
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# skip empty lines
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if not command.strip():
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continue
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if command.startswith(('#', '//')):
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continue
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@ -152,9 +155,6 @@ def main_loop(t2i, outdir, parser, log, infile):
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print(str(e))
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continue
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if len(elements) == 0:
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continue
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if elements[0] == 'q':
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done = True
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break
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@ -239,11 +239,22 @@ def main_loop(t2i, outdir, parser, log, infile):
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continue
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print('Outputs:')
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write_log_message(t2i, normalized_prompt, results, log)
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write_log_message(t2i, normalized_prompt, results, log_path)
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print('goodbye!')
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def get_next_command(infile=None) -> 'command string':
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if infile is None:
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command = input("dream> ")
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else:
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command = infile.readline()
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if not command:
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raise EOFError
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else:
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command = command.strip()
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print(f'#{command}')
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return command
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def load_gfpgan_bg_upsampler(bg_upsampler, bg_tile=400):
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import torch
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@ -309,19 +320,14 @@ def load_gfpgan_bg_upsampler(bg_upsampler, bg_tile=400):
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# return variants
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def write_log_message(t2i, prompt, results, logfile):
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### the t2i variable doesn't seem to be necessary here. maybe remove it?
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def write_log_message(t2i, prompt, results, log_path):
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"""logs the name of the output image, its prompt and seed to the terminal, log file, and a Dream text chunk in the PNG metadata"""
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last_seed = None
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img_num = 1
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seenit = {}
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log_lines = [f"{r[0]}: {prompt} -S{r[1]}\n" for r in results]
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print(*log_lines, sep="")
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for r in results:
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seed = r[1]
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log_message = f'{r[0]}: {prompt} -S{seed}'
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print(log_message)
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logfile.write(log_message + '\n')
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logfile.flush()
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with open(log_path, "a") as file:
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file.writelines(log_lines)
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def create_argv_parser():
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