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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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ba295b3268
* Add a textbox option to Prompts from file (ease of use and it makes it much easier to use on a mobile device) * Fix the fact that Prompts from file was sometimes passing an empty batch.
56 lines
2.3 KiB
Python
56 lines
2.3 KiB
Python
import math
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import os
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import sys
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import traceback
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import modules.scripts as scripts
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import gradio as gr
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from modules.processing import Processed, process_images
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from PIL import Image
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from modules.shared import opts, cmd_opts, state
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class Script(scripts.Script):
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def title(self):
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return "Prompts from file or textbox"
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def ui(self, is_img2img):
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# This checkbox would look nicer as two tabs, but there are two problems:
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# 1) There is a bug in Gradio 3.3 that prevents visibility from working on Tabs
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# 2) Even with Gradio 3.3.1, returning a control (like Tabs) that can't be used as input
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# causes a AttributeError: 'Tabs' object has no attribute 'preprocess' assert,
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# due to the way Script assumes all controls returned can be used as inputs.
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# Therefore, there's no good way to use grouping components right now,
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# so we will use a checkbox! :)
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checkbox_txt = gr.Checkbox(label="Show Textbox", value=False)
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file = gr.File(label="File with inputs", type='bytes')
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prompt_txt = gr.TextArea(label="Prompts")
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checkbox_txt.change(fn=lambda x: [gr.File.update(visible = not x), gr.TextArea.update(visible = x)], inputs=[checkbox_txt], outputs=[file, prompt_txt])
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return [checkbox_txt, file, prompt_txt]
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def run(self, p, checkbox_txt, data: bytes, prompt_txt: str):
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if (checkbox_txt):
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lines = [x.strip() for x in prompt_txt.splitlines()]
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else:
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lines = [x.strip() for x in data.decode('utf8', errors='ignore').split("\n")]
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lines = [x for x in lines if len(x) > 0]
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img_count = len(lines) * p.n_iter
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batch_count = math.ceil(img_count / p.batch_size)
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loop_count = math.ceil(batch_count / p.n_iter)
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print(f"Will process {img_count} images in {batch_count} batches.")
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p.do_not_save_grid = True
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state.job_count = batch_count
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images = []
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for loop_no in range(loop_count):
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state.job = f"{loop_no + 1} out of {loop_count}"
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p.prompt = lines[loop_no*p.batch_size:(loop_no+1)*p.batch_size] * p.n_iter
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proc = process_images(p)
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images += proc.images
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return Processed(p, images, p.seed, "")
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