|
from transformers import pipeline, set_seed |
|
import gradio as grad, random, re |
|
|
|
|
|
gpt2_pipe = pipeline('text-generation', model='Gustavosta/MagicPrompt-Stable-Diffusion', tokenizer='gpt2') |
|
with open("ideas.txt", "r") as f: |
|
line = f.readlines() |
|
|
|
|
|
def generate(starting_text): |
|
for count in range(4): |
|
seed = random.randint(100, 1000000) |
|
set_seed(seed) |
|
|
|
if starting_text == "": |
|
starting_text: str = line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize() |
|
starting_text: str = re.sub(r"[,:\-β.!;?_]", '', starting_text) |
|
print(starting_text) |
|
|
|
response = gpt2_pipe(starting_text, max_length=random.randint(60, 90), num_return_sequences=4) |
|
response_list = [] |
|
for x in response: |
|
resp = x['generated_text'].strip() |
|
if resp != starting_text and len(resp) > (len(starting_text) + 4) and resp.endswith((":", "-", "β")) is False: |
|
response_list.append(resp+'\n') |
|
|
|
response_end = "\n".join(response_list) |
|
response_end = re.sub('[^ ]+\.[^ ]+','', response_end) |
|
response_end = response_end.replace("<", "").replace(">", "") |
|
|
|
if response_end != "": |
|
return response_end |
|
if count == 4: |
|
return response_end |
|
|
|
|
|
txt = grad.Textbox(lines=1, label="Initial Text", placeholder="English Text here") |
|
out = grad.Textbox(lines=4, label="Generated Prompts") |
|
|
|
examples = [] |
|
for x in range(8): |
|
examples.append(line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize()) |
|
|
|
title = "Stable Diffusion Prompt Generator" |
|
description = 'This is a demo of the model series: "MagicPrompt", in this case, aimed at: Stable Diffusion. To use it, simply submit your text or click on one of the examples.<b><br><br>To learn more about the model, go to the link: https://huggingface.co/Gustavosta/MagicPrompt-Stable-Diffusion<br>' |
|
article = "<div><center><img src='https://visitor-badge.glitch.me/badge?page_id=_Stable_Diffusion' alt='visitor badge'></center></div>" |
|
|
|
grad.Interface(fn=generate, |
|
inputs=txt, |
|
outputs=out, |
|
examples=examples, |
|
title=title, |
|
description=description, |
|
article=article, |
|
allow_flagging='never', |
|
cache_examples=False).queue(concurrency_count=1, api_open=False).launch(show_api=False, show_error=True) |
|
|