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| # built-in | |
| from inspect import signature | |
| import os | |
| import subprocess | |
| import logging | |
| import re | |
| import random | |
| from string import ascii_letters, digits, punctuation | |
| import requests | |
| import sys | |
| import warnings | |
| import time | |
| import asyncio | |
| from functools import partial | |
| # external | |
| import torch | |
| import gradio as gr | |
| from numpy import asarray as array | |
| from lxml.html import fromstring | |
| from diffusers.utils import export_to_gif, load_image | |
| from huggingface_hub import hf_hub_download | |
| from safetensors.torch import load_file, save_file | |
| from diffusers import AnimateDiffPipeline, MotionAdapter, DDIMScheduler, StableDiffusionPipeline | |
| # logging | |
| warnings.filterwarnings("ignore") | |
| root = logging.getLogger() | |
| root.setLevel(logging.DEBUG) | |
| handler = logging.StreamHandler(sys.stderr) | |
| handler.setLevel(logging.DEBUG) | |
| formatter = logging.Formatter('\n >>> [%(levelname)s] %(asctime)s %(name)s: %(message)s\n') | |
| handler.setFormatter(formatter) | |
| root.addHandler(handler) | |
| # constant data | |
| if torch.cuda.is_available(): | |
| device = "cuda" | |
| dtype = torch.float16 | |
| else: | |
| device = "cpu" | |
| dtype = torch.float16 | |
| base = "SG161222/Realistic_Vision_V6.0_B1_noVAE" | |
| adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-3", torch_dtype=dtype, device=device) | |
| # variable data | |
| last_motion="" | |
| result = [] | |
| # precision data | |
| seq=512 | |
| fast=True | |
| fps=18 | |
| width=896 | |
| height=896 | |
| step=30 | |
| accu=8.5 | |
| # ui data | |
| css="".join([""" | |
| input, input::placeholder { | |
| text-align: center !important; | |
| } | |
| *, *::placeholder { | |
| font-family: Suez One !important; | |
| } | |
| h1,h2,h3,h4,h5,h6 { | |
| width: 100%; | |
| text-align: center; | |
| } | |
| footer { | |
| display: none !important; | |
| } | |
| #col-container { | |
| margin: 0 auto; | |
| } | |
| .image-container { | |
| aspect-ratio: """,str(width),"/",str(height),""" !important; | |
| } | |
| .dropdown-arrow { | |
| display: none !important; | |
| } | |
| *:has(>.btn) { | |
| display: flex; | |
| justify-content: space-evenly; | |
| align-items: center; | |
| } | |
| .btn { | |
| display: flex; | |
| } | |
| """]) | |
| js=""" | |
| function custom(){ | |
| document.querySelector("div#prompt input").setAttribute("maxlength","38") | |
| document.querySelector("div#prompt2 input").setAttribute("maxlength","38") | |
| } | |
| """ | |
| # torch pipes | |
| image_pipe = StableDiffusionPipeline.from_pretrained(base, torch_dtype=dtype, safety_checker=None).to(device) | |
| pipe = AnimateDiffPipeline.from_pretrained(base, torch_dtype=dtype, motion_adapter=adapter).to(device) | |
| pipe.scheduler = DDIMScheduler( | |
| clip_sample=False, | |
| beta_start=0.00085, | |
| beta_end=0.012, | |
| beta_schedule="linear", | |
| timestep_spacing="trailing", | |
| steps_offset=1 | |
| ) | |
| pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-plus_sd15.bin") | |
| pipe.enable_free_init(method="butterworth", use_fast_sampling=fast) | |
| # functionality | |
| def run(cmd): | |
| return str(subprocess.run(cmd, shell=True, capture_output=True, env=None).stdout) | |
| def xpath_finder(str,pattern): | |
| try: | |
| return ""+fromstring(str).xpath(pattern)[0].text_content().lower().strip() | |
| except: | |
| return "" | |
| def translate(text,lang): | |
| if text == None or lang == None: | |
| return "" | |
| text = re.sub(f'[{punctuation}]', '', re.sub('[ ]+', ' ', text)).lower().strip() | |
| lang = re.sub(f'[{punctuation}]', '', re.sub('[ ]+', ' ', 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}' | |
| content = str(requests.get( | |
| url = url, | |
| headers = { | |
| 'User-Agent': random.choice(user_agents) | |
| } | |
| ).content) | |
| translated = text | |
| src_lang = xpath_finder(content,'//*[@class="source-language"]') | |
| trgt_lang = xpath_finder(content,'//*[@class="target-language"]') | |
| src_text = xpath_finder(content,'//*[@id="tw-source-text"]/*') | |
| trgt_text = xpath_finder(content,'//*[@id="tw-target-text"]/*') | |
| if trgt_lang == lang: | |
| translated = trgt_text | |
| ret = re.sub(f'[{punctuation}]', '', re.sub('[ ]+', ' ', translated)).lower().strip() | |
| return ret | |
| def generate_random_string(length): | |
| characters = str(ascii_letters + digits) | |
| return ''.join(random.choice(characters) for _ in range(length)) | |
| def pipe_generate(img,p1,p2,motion,time,title): | |
| global last_motion | |
| global pipe | |
| if img is None: | |
| img = image_pipe( | |
| prompt=p1, | |
| negative_prompt=p2, | |
| height=height, | |
| width=width, | |
| guidance_scale=accu, | |
| num_images_per_prompt=1, | |
| num_inference_steps=step, | |
| max_sequence_length=seq, | |
| need_safetycheck=False, | |
| generator=torch.Generator(device).manual_seed(0) | |
| ).images[0] | |
| if time == 0.0: | |
| return img | |
| if last_motion != motion: | |
| if last_motion != "": | |
| pipe.unload_lora_weights() | |
| if motion != "": | |
| pipe.load_lora_weights(motion, adapter_name="motion") | |
| pipe.fuse_lora() | |
| pipe.set_adapters("motion", [0.7]) | |
| last_motion = motion | |
| return pipe( | |
| prompt=p1, | |
| negative_prompt=p2, | |
| height=height, | |
| width=width, | |
| ip_adapter_image=img.convert("RGB"), | |
| num_inference_steps=step, | |
| guidance_scale=accu, | |
| num_frames=(fps*time) | |
| ).frames[0] | |
| def handle_generate(*_inp): | |
| inp = list(_inp) | |
| inp[1] = translate(inp[1],"english") | |
| inp[2] = translate(inp[2],"english") | |
| if inp[2] != "": | |
| arr = [] | |
| for wrd in inp[2].split(): | |
| arr.append(wrd) | |
| inp[2] = ", " + ", ".join(arr) | |
| inp[2] = f"creative, fake, error, dreamy, unreal, pixelated, bright, deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, weird, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, unspecified, general, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck{inp[2]}" | |
| _do = ['photographed', "environment", 'realistic', 'true', 'genuine', 'dynamic poze', 'authentic', 'deep field', 'reasonable', "natural", 'rough', "real world", 'best quality', 'focused', "highly detailed"] | |
| if inp[1] != "": | |
| for wrd in inp[1].split(): | |
| _do.append(wrd) | |
| inp[1] = ", ".join(_do) | |
| if inp[5] != "": | |
| _do.append(f'centered readable large bold written text: {inp[5]}') | |
| inp[1] = ", ".join(_do) | |
| print(f""" | |
| - - - - | |
| {inp[1]} | |
| {inp[2]} | |
| - - - - | |
| """) | |
| ln = len(result) | |
| pipe_out = [pipe_generate(*inp) for i in range(ln)] | |
| names = [] | |
| for i in pipe_out: | |
| name = generate_random_string(12) + ( ".png" if time == 0 else ".gif" ) | |
| if inp[4] == 0.0: | |
| i.save(name) | |
| else: | |
| export_to_gif(i,name,fps=fps) | |
| names.append( name ) | |
| return names | |
| def ui(): | |
| global result | |
| with gr.Blocks(theme=gr.themes.Soft(),css=css,js=js) as demo: | |
| gr.Markdown(f""" | |
| # MULTI-LANGUAGE GIF/PNG CREATOR | |
| """) | |
| with gr.Row(elem_id="col-container"): | |
| with gr.Column(): | |
| with gr.Row(): | |
| img = gr.Image(label="Upload photo",show_label=True,container=False,type="pil") | |
| with gr.Column(scale=0.66): | |
| with gr.Row(): | |
| title = gr.Textbox( | |
| placeholder="Logo title", | |
| container=False, | |
| max_lines=1 | |
| ) | |
| prompt = gr.Textbox( | |
| elem_id="prompt", | |
| placeholder="Included keywords", | |
| container=False, | |
| max_lines=1 | |
| ) | |
| with gr.Row(): | |
| prompt2 = gr.Textbox( | |
| elem_id="prompt2", | |
| placeholder="Excluded keywords", | |
| container=False, | |
| max_lines=1 | |
| ) | |
| with gr.Row(): | |
| time = gr.Slider( | |
| minimum=0.0, | |
| maximum=8.0, | |
| value=0.0, | |
| step=1.0, | |
| label="GIF/PNG Duration (0s = PNG)" | |
| ) | |
| with gr.Row(): | |
| motion = gr.Dropdown( | |
| label='GIF camera movement', | |
| show_label=True, | |
| container=False, | |
| choices=[ | |
| ("(No Effect)", ""), | |
| ("Zoom in", "guoyww/#animatediff-motion-lora-zoom-in"), | |
| ("Zoom out", "guoyww/#animatediff-motion-lora-zoom-out"), | |
| ("Tilt up", "guoyww/#animatediff-motion-lora-tilt-up"), | |
| ("Tilt down", "guoyww/#animatediff-motion-lora-tilt-down"), | |
| ("Pan left", "guoyww/#animatediff-motion-lora-pan-left"), | |
| ("Pan right", "guoyww/#animatediff-motion-lora-pan-right"), | |
| ("Roll left", "guoyww/#animatediff-motion-lora-rolling-anticlockwise"), | |
| ("Roll right", "guoyww/#animatediff-motion-lora-rolling-clockwise"), | |
| ], | |
| value="", | |
| interactive=True | |
| ) | |
| with gr.Row(): | |
| result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=True, type='filepath', show_share_button=False)) | |
| with gr.Row(): | |
| run_button = gr.Button("Start!",elem_classes="btn",scale=0) | |
| gr.on( | |
| triggers=[ | |
| run_button.click, | |
| prompt.submit, | |
| prompt2.submit | |
| ], | |
| fn=handle_generate, | |
| inputs=[img,prompt,prompt2,motion,time,title], | |
| outputs=result | |
| ) | |
| demo.queue().launch() | |
| # entry | |
| if __name__ == "__main__": | |
| os.chdir(os.path.abspath(os.path.dirname(__file__))) | |
| ui() | |
| # end |