41 lines
1.2 KiB
Python
41 lines
1.2 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"
|
|
|
|
def ui(self, is_img2img):
|
|
file = gr.File(label="File with inputs", type='bytes')
|
|
|
|
return [file]
|
|
|
|
def run(self, p, data: bytes):
|
|
lines = [x.strip() for x in data.decode('utf8', errors='ignore').split("\n")]
|
|
lines = [x for x in lines if len(x) > 0]
|
|
|
|
batch_count = math.ceil(len(lines) / p.batch_size)
|
|
print(f"Will process {len(lines) * p.n_iter} images in {batch_count * p.n_iter} batches.")
|
|
|
|
p.do_not_save_grid = True
|
|
|
|
state.job_count = batch_count
|
|
|
|
images = []
|
|
for batch_no in range(batch_count):
|
|
state.job = f"{batch_no} out of {batch_count * p.n_iter}"
|
|
p.prompt = lines[batch_no*p.batch_size:(batch_no+1)*p.batch_size] * p.n_iter
|
|
proc = process_images(p)
|
|
images += proc.images
|
|
|
|
return Processed(p, images, p.seed, "")
|