app.py

# 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
from PIL import Image, ImageDraw, ImageFont

# 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] != "":
        draw = ImageDraw.Draw(pipe_out)
        textheight=32
        font = ImageFont.truetype(r"OpenSans-Bold.ttf", textheight)
        textwidth = draw.textlength(inp[5])
        x = (width - textwidth) // 2
        y = (height - textheight) // 2
        draw.text((x, y), inp[5],font=font)
        
    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