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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 on_show(self, checkbox_txt, file, prompt_txt):
return [ gr.Checkbox.update(visible = True), gr.File.update(visible = not checkbox_txt), gr.TextArea.update(visible = checkbox_txt) ]
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, "")
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