113 lines
4.5 KiB
Python
113 lines
4.5 KiB
Python
import math
|
|
import os
|
|
import sys
|
|
import traceback
|
|
|
|
import modules.scripts as scripts
|
|
import gradio as gr
|
|
|
|
from modules.processing import Processed, process_images
|
|
from PIL import Image
|
|
from modules.shared import opts, cmd_opts, state
|
|
|
|
|
|
class Script(scripts.Script):
|
|
def title(self):
|
|
return "Prompts from file or textbox"
|
|
|
|
def ui(self, is_img2img):
|
|
# This checkbox would look nicer as two tabs, but there are two problems:
|
|
# 1) There is a bug in Gradio 3.3 that prevents visibility from working on Tabs
|
|
# 2) Even with Gradio 3.3.1, returning a control (like Tabs) that can't be used as input
|
|
# causes a AttributeError: 'Tabs' object has no attribute 'preprocess' assert,
|
|
# due to the way Script assumes all controls returned can be used as inputs.
|
|
# Therefore, there's no good way to use grouping components right now,
|
|
# so we will use a checkbox! :)
|
|
checkbox_txt = gr.Checkbox(label="Show Textbox", value=False)
|
|
file = gr.File(label="File with inputs", type='bytes')
|
|
prompt_txt = gr.TextArea(label="Prompts")
|
|
checkbox_txt.change(fn=lambda x: [gr.File.update(visible = not x), gr.TextArea.update(visible = x)], inputs=[checkbox_txt], outputs=[file, prompt_txt])
|
|
return [checkbox_txt, file, prompt_txt]
|
|
|
|
def process_string_tag(self, tag):
|
|
return tag[1:-2]
|
|
|
|
def process_int_tag(self, tag):
|
|
return int(tag)
|
|
|
|
def process_float_tag(self, tag):
|
|
return float(tag)
|
|
|
|
def process_boolean_tag(self, tag):
|
|
return True if (tag == "true") else False
|
|
|
|
prompt_tags = {
|
|
"sd_model": None,
|
|
"outpath_samples": process_string_tag,
|
|
"outpath_grids": process_string_tag,
|
|
"prompt_for_display": process_string_tag,
|
|
"prompt": process_string_tag,
|
|
"negative_prompt": process_string_tag,
|
|
"styles": process_string_tag,
|
|
"seed": process_int_tag,
|
|
"subseed_strength": process_float_tag,
|
|
"subseed": process_int_tag,
|
|
"seed_resize_from_h": process_int_tag,
|
|
"seed_resize_from_w": process_int_tag,
|
|
"sampler_index": process_int_tag,
|
|
"batch_size": process_int_tag,
|
|
"n_iter": process_int_tag,
|
|
"steps": process_int_tag,
|
|
"cfg_scale": process_float_tag,
|
|
"width": process_int_tag,
|
|
"height": process_int_tag,
|
|
"restore_faces": process_boolean_tag,
|
|
"tiling": process_boolean_tag,
|
|
"do_not_save_samples": process_boolean_tag,
|
|
"do_not_save_grid": process_boolean_tag
|
|
}
|
|
|
|
def run(self, p, checkbox_txt, data: bytes, prompt_txt: str):
|
|
if (checkbox_txt):
|
|
lines = [x.strip() for x in prompt_txt.splitlines()]
|
|
else:
|
|
lines = [x.strip() for x in data.decode('utf8', errors='ignore').split("\n")]
|
|
lines = [x for x in lines if len(x) > 0]
|
|
|
|
img_count = len(lines) * p.n_iter
|
|
batch_count = math.ceil(img_count / p.batch_size)
|
|
loop_count = math.ceil(batch_count / p.n_iter)
|
|
# These numbers no longer accurately reflect the total images and number of batches
|
|
print(f"Will process {img_count} images in {batch_count} batches.")
|
|
|
|
p.do_not_save_grid = True
|
|
|
|
state.job_count = batch_count
|
|
|
|
images = []
|
|
for loop_no in range(loop_count):
|
|
state.job = f"{loop_no + 1} out of {loop_count}"
|
|
# The following line may need revising to remove batch_size references
|
|
current_line = lines[loop_no*p.batch_size:(loop_no+1)*p.batch_size] * p.n_iter
|
|
|
|
# If the current line has no tags, parse the whole line as a prompt, else parse each tag
|
|
if(current_line[0][:2] != "--"):
|
|
p.prompt = current_line
|
|
else:
|
|
tokenized_line = current_line[0].split("--")
|
|
|
|
for tag in tokenized_line:
|
|
tag_split = tag.split(" ", 1)
|
|
if(tag_split[0] != ''):
|
|
value_func = self.prompt_tags.get(tag_split[0], None)
|
|
if(value_func != None):
|
|
value = value_func(self, tag_split[1])
|
|
setattr(p, tag_split[0], value)
|
|
else:
|
|
print(f"Unknown option \"{tag_split}\"")
|
|
|
|
proc = process_images(p)
|
|
images += proc.images
|
|
|
|
return Processed(p, images, p.seed, "")
|