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| import os | |
| import re | |
| import spaces | |
| import random | |
| import string | |
| import torch | |
| import requests | |
| import gradio as gr | |
| import numpy as np | |
| from lxml.html import fromstring | |
| from pathos.threading import ThreadPool as Pool | |
| from diffusers import AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler | |
| from diffusers.utils import export_to_gif | |
| from huggingface_hub import hf_hub_download | |
| from safetensors.torch import load_file | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| dtype = torch.float16 | |
| step = 8 | |
| repo = "ByteDance/AnimateDiff-Lightning" | |
| ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors" | |
| #base = "emilianJR/epiCRealism" | |
| base = "black-forest-labs/FLUX.1-dev" | |
| adapter = MotionAdapter().to(device, dtype) | |
| adapter.load_state_dict(load_file(hf_hub_download(repo ,ckpt), device=device)) | |
| pipe = AnimateDiffPipeline.from_pretrained(base, motion_adapter=adapter, torch_dtype=dtype).to(device) | |
| pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", beta_schedule="linear") | |
| def translate(text,lang): | |
| if text == None or lang == None: | |
| return "" | |
| text = re.sub(f'[{string.punctuation}]', '', re.sub('[\s+]', ' ', text)).lower().strip() | |
| lang = re.sub(f'[{string.punctuation}]', '', re.sub('[\s+]', ' ', lang)).lower().strip() | |
| if text == "" or lang == "": | |
| return "" | |
| if len(text) > 38: | |
| raise Exception("Translation Error: Too long text!") | |
| user_agents = [ | |
| 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36', | |
| 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36', | |
| 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36', | |
| 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.1 Safari/605.1.15', | |
| 'Mozilla/5.0 (Macintosh; Intel Mac OS X 13_1) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.1 Safari/605.1.15' | |
| ] | |
| padded_chars = re.sub("[(^\-)(\-$)]","",text.replace("","-").replace("- -"," ")).strip() | |
| query_text = f'Please translate {padded_chars}, into {lang}' | |
| url = f'https://www.google.com/search?q={query_text}' | |
| print(url) | |
| resp = requests.get( | |
| url = url, | |
| headers = { | |
| 'User-Agent': random.choice(user_agents) | |
| } | |
| ) | |
| content = resp.content | |
| html = fromstring(content) | |
| translated = text | |
| try: | |
| src_lang = html.xpath('//*[@class="source-language"]')[0].text_content().lower().strip() | |
| trgt_lang = html.xpath('//*[@class="target-language"]')[0].text_content().lower().strip() | |
| src_text = html.xpath('//*[@id="tw-source-text"]/*')[0].text_content().lower().strip() | |
| trgt_text = html.xpath('//*[@id="tw-target-text"]/*')[0].text_content().lower().strip() | |
| if trgt_lang == lang: | |
| translated = trgt_text | |
| except: | |
| print(f'Translation Warning: Failed To Translate!') | |
| ret = re.sub(f'[{string.punctuation}]', '', re.sub('[\s+]', ' ', translated)).lower().strip() | |
| print(ret) | |
| return ret | |
| def generate_random_string(length): | |
| characters = string.ascii_letters + string.digits | |
| return ''.join(random.choice(characters) for _ in range(length)) | |
| def Piper(_do,_dont): | |
| return pipe( | |
| _do, | |
| height=256, | |
| width=768, | |
| negative_prompt=_dont, | |
| num_inference_steps=step, | |
| guidance_scale=7 | |
| ) | |
| def infer(prompt_en,prompt2_en): | |
| name = generate_random_string(12)+".png" | |
| if prompt_en == "": | |
| _do = 'film' | |
| else: | |
| _do = f'filmed { prompt_en }' | |
| if prompt2_en == "": | |
| _dont = 'complex scene, ugly human body, partial human body, smooth texture, fictional content, blurred content, amputated human body, distorted palm fingers, missing legs, unreal eyes, squinting eyes, text anywhere, prints anywhere' | |
| else: | |
| _dont = f'{prompt2_en} anywhere, complex scene, ugly human body, partial human body, smooth texture, fictional content, blurred content, amputated human body, distorted palm fingers, missing legs, unreal eyes, squinting eyes, text anywhere, prints anywhere' | |
| export_to_gif(Piper(_do,_dont).frames[0],name) | |
| return name | |
| css=""" | |
| input, input::placeholder { | |
| text-align: center !important; | |
| } | |
| *, *::placeholder { | |
| direction: rtl !important; | |
| font-family: Suez One !important; | |
| } | |
| h1,h2,h3,h4,h5,h6,span,p,pre { | |
| width: 100% !important; | |
| text-align: center !important; | |
| display: block !important; | |
| } | |
| footer { | |
| display: none !important; | |
| } | |
| #col-container { | |
| margin: 0 auto !important; | |
| max-width: 15cm !important; | |
| } | |
| .image-container { | |
| aspect-ratio: 768 / 256 !important; | |
| } | |
| .dropdown-arrow { | |
| display: none !important; | |
| } | |
| *:has(.btn), .btn { | |
| width: 100% !important; | |
| margin: 0 auto !important; | |
| } | |
| """ | |
| js=""" | |
| function custom(){ | |
| document.querySelector("div#prompt input").setAttribute("maxlength","27"); | |
| document.querySelector("div#prompt2 input").setAttribute("maxlength","27"); | |
| } | |
| """ | |
| with gr.Blocks(theme=gr.themes.Soft(),css=css,js=js) as demo: | |
| result = [] | |
| with gr.Column(elem_id="col-container"): | |
| gr.Markdown(f""" | |
| # GIF AI | |
| """) | |
| with gr.Row(): | |
| prompt = gr.Textbox( | |
| elem_id="prompt", | |
| placeholder="WHAT TO CREATE...", | |
| container=False, | |
| rtl=True, | |
| max_lines=1 | |
| ) | |
| with gr.Row(): | |
| prompt2 = gr.Textbox( | |
| elem_id="prompt2", | |
| placeholder="WHAT TO AVOID...", | |
| container=False, | |
| rtl=True, | |
| max_lines=1 | |
| ) | |
| with gr.Row(): | |
| run_button = gr.Button("START",elem_classes="btn",scale=0) | |
| with gr.Row(): | |
| result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False)) | |
| with gr.Row(): | |
| result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False)) | |
| def _ret(idx,p1,p2): | |
| print(f'Starting {idx}: {p1} {p2}') | |
| v = infer(p1,p2) | |
| print(f'Finished {idx}: {v}') | |
| return v | |
| def _rets(p1,p2): | |
| p1_en = translate(p1,"english") | |
| p2_en = translate(p2,"english") | |
| ln = len(result) | |
| idxs = list(range(ln)) | |
| p1s = [p1_en for _ in idxs] | |
| p2s = [p2_en for _ in idxs] | |
| return list(Pool(ln).imap( _ret, idxs, p1s, p2s )) | |
| run_button.click(fn=_rets,inputs=[prompt,prompt2],outputs=result) | |
| demo.queue().launch() |