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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="" | |
| # precision data | |
| seq=512 | |
| fast=True | |
| fps=30 | |
| width=896 | |
| height=896 | |
| step=100 | |
| accu=9.0 | |
| # 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(int(str(random.random()).split(".")[1])) | |
| ).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] != "": | |
| inp[2] = " which is related to: " + inp[2] + "." | |
| inp[2] = f"The content which is faked and errored and dreamy and unreal and off topic and pixelated and deformed iris and deformed pupils and semi-realistic and cgi and 3d and render and sketch and cartoon and drawing and anime and cropped and out of frame and worst quality and low quality and jpeg artifacts and ugly and duplicate and weird and morbid and mutilated and extra fingers and mutated hands and poorly drawn hands and poorly drawn face and mutation and deformed and blurry and dehydrated and bad anatomy and bad proportions and extra limbs and cloned face and disfigured and unspecified and gross and proportions and malformed limbs and missing arms and missing legs and extra arms and extra legs and fused fingers and too many fingers and long neck content{inp[2]}" | |
| if inp[1] != "": | |
| inp[1] = " which is related to: " + inp[1] + "." | |
| inp[1] = f'The content which is photographed and realistic and true and genuine and dynamic poze and authentic and deep field and reasonable and natural and best quality and focused and highly detailed content{inp[1]}' | |
| print(f""" | |
| Positive: {inp[1]} | |
| Negative: {inp[2]} | |
| """) | |
| pipe_out = pipe_generate(*inp) | |
| if inp[5] != "": | |
| name = generate_random_string(12) + ( ".png" if time == 0 else ".gif" ) | |
| if inp[4] == 0.0: | |
| pipe_out.save(name) | |
| else: | |
| export_to_gif(pipe_out,name,fps=fps) | |
| return name | |
| 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=600.0, | |
| value=0.0, | |
| step=5.0, | |
| 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 = 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 |