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from transformers import pipeline | |
import gradio as gr | |
import random | |
import string | |
import paddlehub as hub | |
import torch | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
from loguru import logger | |
language_translation_model = hub.Module(directory=f'./baidu_translate') | |
def getTextTrans(text, source='zh', target='en'): | |
def is_chinese(string): | |
for ch in string: | |
if u'\u4e00' <= ch <= u'\u9fff': | |
return True | |
return False | |
if not is_chinese(text) and target == 'en': | |
return text | |
try: | |
text_translation = language_translation_model.translate(text, source, target) | |
return text_translation | |
except Exception as e: | |
return text | |
space_ids = { | |
"spaces/stabilityai/stable-diffusion": "SD 2.1", | |
"spaces/runwayml/stable-diffusion-v1-5": "SD 1.5", | |
"spaces/stabilityai/stable-diffusion-1": "SD 1.0", | |
"dalle_mini_tab": "Dalle mini", | |
"spaces/IDEA-CCNL/Taiyi-Stable-Diffusion-Chinese": "Taiyi(太乙)", | |
} | |
tab_actions = [] | |
tab_titles = [] | |
extend_prompt_1 = True | |
extend_prompt_2 = True | |
extend_prompt_3 = True | |
thanks_info = "Thanks: " | |
if extend_prompt_1: | |
extend_prompt_pipe = pipeline('text-generation', model='yizhangliu/prompt-extend', max_length=77, pad_token_id=0) | |
thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/daspartho/prompt-extend' _blank><font style='color:blue;weight:bold;'>prompt-extend(1)</font></a>]" | |
if extend_prompt_2: | |
def load_prompter(): | |
prompter_model = AutoModelForCausalLM.from_pretrained("microsoft/Promptist") | |
tokenizer = AutoTokenizer.from_pretrained("gpt2") | |
tokenizer.pad_token = tokenizer.eos_token | |
tokenizer.padding_side = "left" | |
return prompter_model, tokenizer | |
prompter_model, prompter_tokenizer = load_prompter() | |
def extend_prompt_microsoft(in_text): | |
input_ids = prompter_tokenizer(in_text.strip()+" Rephrase:", return_tensors="pt").input_ids | |
eos_id = prompter_tokenizer.eos_token_id | |
outputs = prompter_model.generate(input_ids, do_sample=False, max_new_tokens=75, num_beams=8, num_return_sequences=8, eos_token_id=eos_id, pad_token_id=eos_id, length_penalty=-1.0) | |
output_texts = prompter_tokenizer.batch_decode(outputs, skip_special_tokens=True) | |
res = output_texts[0].replace(in_text+" Rephrase:", "").strip() | |
return res | |
thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/microsoft/Promptist' _blank><font style='color:blue;weight:bold;'>Promptist(2)</font></a>]" | |
if extend_prompt_3: | |
MagicPrompt = gr.Interface.load("spaces/Gustavosta/MagicPrompt-Stable-Diffusion") | |
thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/Gustavosta/MagicPrompt-Stable-Diffusion' _blank><font style='color:blue;weight:bold;'>MagicPrompt(3)</font></a>]" | |
do_dreamlike_photoreal = False | |
if do_dreamlike_photoreal: | |
def add_random_noise(prompt, noise_level=0.1): | |
# Get the percentage of characters to add as noise | |
percentage_noise = noise_level * 5 | |
# Get the number of characters to add as noise | |
num_noise_chars = int(len(prompt) * (percentage_noise/100)) | |
# Get the indices of the characters to add noise to | |
noise_indices = random.sample(range(len(prompt)), num_noise_chars) | |
# Add noise to the selected characters | |
prompt_list = list(prompt) | |
for index in noise_indices: | |
prompt_list[index] = random.choice(string.ascii_letters + string.punctuation) | |
new_prompt = "".join(prompt_list) | |
return new_prompt | |
dreamlike_photoreal_2_0 = gr.Interface.load("models/dreamlike-art/dreamlike-photoreal-2.0") | |
dreamlike_image = gr.Image(label="Dreamlike Photoreal 2.0") | |
tab_actions.append(dreamlike_image) | |
tab_titles.append("Dreamlike_2.0") | |
thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0' _blank><font style='color:blue;weight:bold;'>dreamlike-photoreal-2.0</font></a>]" | |
for space_id in space_ids.keys(): | |
print(space_id, space_ids[space_id]) | |
try: | |
tab_title = space_ids[space_id] | |
tab_titles.append(tab_title) | |
if (tab_title == 'Dalle mini'): | |
tab_content = gr.Blocks(elem_id='dalle_mini') | |
tab_actions.append(tab_content) | |
else: | |
tab_content = gr.Interface.load(space_id) | |
tab_actions.append(tab_content) | |
thanks_info += f"[<a style='display:inline-block' href='https://huggingface.co/{space_id}' _blank><font style='color:blue;weight:bold;'>{tab_title}</font></a>]" | |
except Exception as e: | |
logger.info(f"load_fail__{space_id}_{e}") | |
start_work = """async() => { | |
function isMobile() { | |
try { | |
document.createEvent("TouchEvent"); return true; | |
} catch(e) { | |
return false; | |
} | |
} | |
function getClientHeight() | |
{ | |
var clientHeight=0; | |
if(document.body.clientHeight&&document.documentElement.clientHeight) { | |
var clientHeight = (document.body.clientHeight<document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight; | |
} else { | |
var clientHeight = (document.body.clientHeight>document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight; | |
} | |
return clientHeight; | |
} | |
function setNativeValue(element, value) { | |
const valueSetter = Object.getOwnPropertyDescriptor(element.__proto__, 'value').set; | |
const prototype = Object.getPrototypeOf(element); | |
const prototypeValueSetter = Object.getOwnPropertyDescriptor(prototype, 'value').set; | |
if (valueSetter && valueSetter !== prototypeValueSetter) { | |
prototypeValueSetter.call(element, value); | |
} else { | |
valueSetter.call(element, value); | |
} | |
} | |
window['tab_advanced'] = 0; | |
var gradioEl = document.querySelector('body > gradio-app').shadowRoot; | |
if (!gradioEl) { | |
gradioEl = document.querySelector('body > gradio-app'); | |
} | |
if (typeof window['gradioEl'] === 'undefined') { | |
window['gradioEl'] = gradioEl; | |
tabitems = window['gradioEl'].querySelectorAll('.tabitem'); | |
tabitems_title = window['gradioEl'].querySelectorAll('#tab_demo')[0].children[0].children[0].children; | |
window['dalle_mini_block'] = null; | |
window['dalle_mini_iframe'] = null; | |
for (var i = 0; i < tabitems.length; i++) { | |
if (tabitems_title[i].innerText.indexOf('SD') >= 0) { | |
tabitems[i].childNodes[0].children[0].style.display='none'; | |
for (var j = 0; j < tabitems[i].childNodes[0].children[1].children.length; j++) { | |
if (j != 1) { | |
tabitems[i].childNodes[0].children[1].children[j].style.display='none'; | |
} | |
} | |
if (tabitems_title[i].innerText.indexOf('SD 1') >= 0) { | |
for (var j = 0; j < 4; j++) { | |
tabitems[i].childNodes[0].children[1].children[3].children[1].children[j].children[2].removeAttribute("disabled"); | |
} | |
} else if (tabitems_title[i].innerText.indexOf('SD 2') >= 0) { | |
tabitems[i].children[0].children[1].children[3].children[0].click(); | |
} | |
} else if (tabitems_title[i].innerText.indexOf('Taiyi') >= 0) { | |
tabitems[i].children[0].children[0].children[1].style.display='none'; | |
tabitems[i].children[0].children[0].children[0].children[0].children[1].style.display='none'; | |
} else if (tabitems_title[i].innerText.indexOf('Dreamlike') >= 0) { | |
tabitems[i].childNodes[0].children[0].children[1].style.display='none'; | |
} else if (tabitems_title[i].innerText.indexOf('Dalle mini') >= 0) { | |
window['dalle_mini_block']= tabitems[i]; | |
} | |
} | |
tab_demo = window['gradioEl'].querySelectorAll('#tab_demo')[0]; | |
tab_demo.style.display = "block"; | |
tab_demo.setAttribute('style', 'height: 100%;'); | |
const page1 = window['gradioEl'].querySelectorAll('#page_1')[0]; | |
const page2 = window['gradioEl'].querySelectorAll('#page_2')[0]; | |
btns_1 = window['gradioEl'].querySelector('#input_col1_row3').children; | |
btns_1_split = 100 / btns_1.length; | |
for (var i = 0; i < btns_1.length; i++) { | |
btns_1[i].setAttribute('style', 'min-width:0px;width:' + btns_1_split + '%;'); | |
} | |
page1.style.display = "none"; | |
page2.style.display = "block"; | |
prompt_work = window['gradioEl'].querySelectorAll('#prompt_work'); | |
for (var i = 0; i < prompt_work.length; i++) { | |
prompt_work[i].style.display='none'; | |
} | |
window['prevPrompt'] = ''; | |
window['doCheckPrompt'] = 0; | |
window['checkPrompt'] = function checkPrompt() { | |
try { | |
prompt_work = window['gradioEl'].querySelectorAll('#prompt_work'); | |
if (prompt_work.length > 0 && prompt_work[0].children.length > 1) { | |
prompt_work[0].children[1].style.display='none'; | |
prompt_work[0].style.display='block'; | |
} | |
text_value = window['gradioEl'].querySelectorAll('#prompt_work')[0].querySelectorAll('textarea')[0].value; | |
progress_bar = window['gradioEl'].querySelectorAll('.progress-bar'); | |
if (window['doCheckPrompt'] === 0 && window['prevPrompt'] !== text_value && progress_bar.length == 0) { | |
console.log('_____new prompt___[' + text_value + ']_'); | |
window['doCheckPrompt'] = 1; | |
window['prevPrompt'] = text_value; | |
tabitems = window['gradioEl'].querySelectorAll('.tabitem'); | |
for (var i = 0; i < tabitems.length; i++) { | |
if (tabitems_title[i].innerText.indexOf('Dalle mini') >= 0) { | |
if (window['dalle_mini_block']) { | |
if (window['dalle_mini_iframe'] === null) { | |
window['dalle_mini_iframe'] = document.createElement('iframe'); | |
window['dalle_mini_iframe'].height = 1000; | |
window['dalle_mini_iframe'].width = '100%'; | |
window['dalle_mini_iframe'].id = 'dalle_iframe'; | |
window['dalle_mini_block'].appendChild(window['dalle_mini_iframe']); | |
} | |
window['dalle_mini_iframe'].src = 'https://yizhangliu-dalleclone.hf.space/index.html?prompt=' + encodeURI(text_value); | |
console.log('dalle_mini'); | |
} | |
continue; | |
} | |
inputText = null; | |
if (tabitems_title[i].innerText.indexOf('SD') >= 0) { | |
text_value = window['gradioEl'].querySelectorAll('#prompt_work')[0].querySelectorAll('textarea')[0].value; | |
inputText = tabitems[i].children[0].children[1].children[0].querySelectorAll('.gr-text-input')[0]; | |
} else if (tabitems_title[i].innerText.indexOf('Taiyi') >= 0) { | |
text_value = window['gradioEl'].querySelectorAll('#prompt_work_zh')[0].querySelectorAll('textarea')[0].value; | |
inputText = tabitems[i].children[0].children[0].children[1].querySelectorAll('.gr-text-input')[0]; | |
} | |
if (inputText) { | |
setNativeValue(inputText, text_value); | |
inputText.dispatchEvent(new Event('input', { bubbles: true })); | |
} | |
} | |
setTimeout(function() { | |
btns = window['gradioEl'].querySelectorAll('button'); | |
for (var i = 0; i < btns.length; i++) { | |
if (['Generate image','Run', '生成图像(Generate)'].includes(btns[i].innerText)) { | |
btns[i].click(); | |
} | |
} | |
window['doCheckPrompt'] = 0; | |
}, 10); | |
} | |
} catch(e) { | |
} | |
} | |
window['checkPrompt_interval'] = window.setInterval("window.checkPrompt()", 100); | |
} | |
return false; | |
}""" | |
switch_tab_advanced = """async() => { | |
window['tab_advanced'] = 1 - window['tab_advanced']; | |
if (window['tab_advanced']==0) { | |
action = 'none'; | |
} else { | |
action = 'block'; | |
} | |
tabitems = window['gradioEl'].querySelectorAll('.tabitem'); | |
tabitems_title = window['gradioEl'].querySelectorAll('#tab_demo')[0].children[0].children[0].children; | |
for (var i = 0; i < tabitems.length; i++) { | |
if (tabitems_title[i].innerText.indexOf('SD') >= 0) { | |
//tabitems[i].childNodes[0].children[1].children[0].style.display=action; | |
//tabitems[i].childNodes[0].children[1].children[4].style.display=action; | |
for (var j = 0; j < tabitems[i].childNodes[0].children[1].children.length; j++) { | |
if (j != 1) { | |
tabitems[i].childNodes[0].children[1].children[j].style.display=action; | |
} | |
} | |
} else if (tabitems_title[i].innerText.indexOf('Taiyi') >= 0) { | |
tabitems[i].children[0].children[0].children[1].style.display=action; | |
} | |
} | |
return false; | |
}""" | |
def prompt_extend(prompt, PM): | |
prompt_en = getTextTrans(prompt, source='zh', target='en') | |
if PM == 1: | |
extend_prompt_en = extend_prompt_pipe(prompt_en+',', num_return_sequences=1)[0]["generated_text"] | |
elif PM == 2: | |
extend_prompt_en = extend_prompt_microsoft(prompt_en) | |
elif PM == 3: | |
extend_prompt_en = MagicPrompt(prompt_en) | |
if (prompt != prompt_en): | |
logger.info(f"extend_prompt__1_PM=[{PM}]_") | |
extend_prompt_out = getTextTrans(extend_prompt_en, source='en', target='zh') | |
else: | |
logger.info(f"extend_prompt__2_PM=[{PM}]_") | |
extend_prompt_out = extend_prompt_en | |
return extend_prompt_out | |
def prompt_extend_1(prompt): | |
extend_prompt_out = prompt_extend(prompt, 1) | |
return extend_prompt_out | |
def prompt_extend_2(prompt): | |
extend_prompt_out = prompt_extend(prompt, 2) | |
return extend_prompt_out | |
def prompt_extend_3(prompt): | |
extend_prompt_out = prompt_extend(prompt, 3) | |
return extend_prompt_out | |
def prompt_draw_1(prompt, noise_level): | |
prompt_en = getTextTrans(prompt, source='zh', target='en') | |
if (prompt != prompt_en): | |
logger.info(f"draw_prompt______1__") | |
prompt_zh = prompt | |
else: | |
logger.info(f"draw_prompt______2__") | |
prompt_zh = getTextTrans(prompt, source='en', target='zh') | |
prompt_with_noise = add_random_noise(prompt_en, noise_level) | |
dreamlike_output = dreamlike_photoreal_2_0(prompt_with_noise) | |
return prompt_en, prompt_zh, dreamlike_output | |
def prompt_draw_2(prompt): | |
prompt_en = getTextTrans(prompt, source='zh', target='en') | |
if (prompt != prompt_en): | |
logger.info(f"draw_prompt______1__") | |
prompt_zh = prompt | |
else: | |
logger.info(f"draw_prompt______2__") | |
prompt_zh = getTextTrans(prompt, source='en', target='zh') | |
return prompt_en, prompt_zh | |
with gr.Blocks(title='Text-to-Image') as demo: | |
with gr.Group(elem_id="page_1", visible=True) as page_1: | |
with gr.Box(): | |
with gr.Row(): | |
start_button = gr.Button("Let's GO!", elem_id="start-btn", visible=True) | |
start_button.click(fn=None, inputs=[], outputs=[], _js=start_work) | |
with gr.Group(elem_id="page_2", visible=False) as page_2: | |
with gr.Row(elem_id="prompt_row0"): | |
with gr.Column(id="input_col1"): | |
with gr.Row(elem_id="input_col1_row1"): | |
prompt_input0 = gr.Textbox(lines=2, label="Original prompt", visible=True) | |
with gr.Row(elem_id="input_col1_row2"): | |
prompt_work = gr.Textbox(lines=1, label="prompt_work", elem_id="prompt_work", visible=True) | |
with gr.Row(elem_id="input_col1_row3"): | |
with gr.Column(elem_id="input_col1_row2_col0"): | |
draw_btn_0 = gr.Button(value = "Generate(original)", elem_id="draw-btn-0") | |
if extend_prompt_1: | |
with gr.Column(elem_id="input_col1_row2_col1"): | |
extend_btn_1 = gr.Button(value = "Extend_1",elem_id="extend-btn-1") | |
if extend_prompt_2: | |
with gr.Column(elem_id="input_col1_row2_col2"): | |
extend_btn_2 = gr.Button(value = "Extend_2",elem_id="extend-btn-2") | |
if extend_prompt_3: | |
with gr.Column(elem_id="input_col1_row2_col3"): | |
extend_btn_3 = gr.Button(value = "Extend_3",elem_id="extend-btn-3") | |
with gr.Column(id="input_col2"): | |
prompt_input1 = gr.Textbox(lines=2, label="Extend prompt", visible=True) | |
draw_btn_1 = gr.Button(value = "Generate(extend)", elem_id="draw-btn-1") | |
with gr.Row(elem_id="prompt_row1"): | |
with gr.Column(id="input_col3"): | |
with gr.Row(elem_id="input_col3_row2"): | |
prompt_work_zh = gr.Textbox(lines=1, label="prompt_work_zh", elem_id="prompt_work_zh", visible=False) | |
with gr.Row(elem_id='tab_demo', visible=True).style(height=200): | |
tab_demo = gr.TabbedInterface(tab_actions, tab_titles) | |
if do_dreamlike_photoreal: | |
with gr.Row(): | |
noise_level=gr.Slider(minimum=0.1, maximum=3, step=0.1, label="Dreamlike noise Level: [Higher noise level produces more diverse outputs, while lower noise level produces similar outputs.]") | |
with gr.Row(): | |
switch_tab_advanced_btn = gr.Button(value = "Switch_tab_advanced", elem_id="switch_tab_advanced_btn") | |
switch_tab_advanced_btn.click(fn=None, inputs=[], outputs=[], _js=switch_tab_advanced) | |
with gr.Row(): | |
gr.HTML(f"<p>{thanks_info}</p>") | |
if extend_prompt_1: | |
extend_btn_1.click(fn=prompt_extend_1, inputs=[prompt_input0], outputs=[prompt_input1]) | |
if extend_prompt_2: | |
extend_btn_2.click(fn=prompt_extend_2, inputs=[prompt_input0], outputs=[prompt_input1]) | |
if extend_prompt_3: | |
extend_btn_3.click(fn=prompt_extend_3, inputs=[prompt_input0], outputs=[prompt_input1]) | |
if do_dreamlike_photoreal: | |
draw_btn_0.click(fn=prompt_draw_1, inputs=[prompt_input0, noise_level], outputs=[prompt_work, prompt_work_zh, dreamlike_image]) | |
draw_btn_1.click(fn=prompt_draw_1, inputs=[prompt_input1, noise_level], outputs=[prompt_work, prompt_work_zh, dreamlike_image]) | |
else: | |
draw_btn_0.click(fn=prompt_draw_2, inputs=[prompt_input0], outputs=[prompt_work, prompt_work_zh]) | |
draw_btn_1.click(fn=prompt_draw_2, inputs=[prompt_input1], outputs=[prompt_work, prompt_work_zh]) | |
demo.queue() | |
demo.launch() | |