Spaces:
Runtime error
Runtime error
| 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 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) | |
| 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}" | |
| p.prompt = lines[loop_no*p.batch_size:(loop_no+1)*p.batch_size] * p.n_iter | |
| proc = process_images(p) | |
| images += proc.images | |
| return Processed(p, images, p.seed, "") | |