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 spaces
import torch
import gradio as gr
from numpy import asarray as array
from lxml.html import fromstring
from diffusers.utils import export_to_video, load_image
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file, save_file
from diffusers import FluxPipeline, CogVideoXImageToVideoPipeline
from PIL import Image, ImageDraw, ImageFont

# logging

warnings.filterwarnings("ignore")
root = logging.getLogger()
root.setLevel(logging.WARN)
handler = logging.StreamHandler(sys.stderr)
handler.setLevel(logging.WARN)
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"
else:
    device = "cpu"

base = "black-forest-labs/FLUX.1-schnell"

# variable data



# precision data

seq=512
width=4320
height=4320
image_steps=8
img_accu=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").addEventListener("keydown",function(e){
        e.target.setAttribute("last_value",e.target.value);
    });
    document.querySelector("div#prompt input").addEventListener("input",function(e){
        if( e.target.value.toString().match(/[^ a-zA-Z,]|( |,){2,}/gsm) ){
            e.target.value = e.target.getAttribute("last_value");
            e.target.removeAttribute("last_value");
        }
    });

    document.querySelector("div#prompt2 input").addEventListener("keydown",function(e){
        e.target.setAttribute("last_value",e.target.value);
    });
    document.querySelector("div#prompt2 input").addEventListener("input",function(e){
        if( e.target.value.toString().match(/[^ a-zA-Z,]|( |,){2,}/gsm) ){
            e.target.value = e.target.getAttribute("last_value");
            e.target.removeAttribute("last_value");
        }
    });
}
"""

# torch pipes

image_pipe = FluxPipeline.from_pretrained(base, torch_dtype=torch.bfloat16).to(device)
image_pipe.enable_model_cpu_offload()

# functionality

def generate_random_string(length):
    characters = str(ascii_letters + digits)
    return ''.join(random.choice(characters) for _ in range(length))

@spaces.GPU()
def pipe_generate(p1,p2):
    return image_pipe(
            prompt=p1,
            negative_prompt=p2,
            height=height,
            width=width,
            guidance_scale=img_accu,
            num_images_per_prompt=1,
            num_inference_steps=image_steps,
            max_sequence_length=seq,
            generator=torch.Generator(device).manual_seed(int(str(random.random()).split(".")[1]))
    ).images[0]

def handle_generate(artist,song,genre,lyrics):

    pos_artist = re.sub("([ \t\n]){1,}", " ", artist).strip()
    pos_song = re.sub("([ \t\n]){1,}", " ", song).strip()
    pos_song = ' '.join(word[0].upper() + word[1:] for word in pos_song.split())
    pos_genre = re.sub(f'[{punctuation}]', '', re.sub("([ \t\n]){1,}", " ", genre)).upper().strip()
    pos_lyrics = re.sub(f'[{punctuation}]', '', re.sub("([ \t\n]){1,}", " ", genre)).lower().strip()
    neg = f"Textual Labeled Distorted Discontinuous Ugly Blurry"
    pos = f'Realistic Natural Genuine Reasonable Detailed { pos_genre } GENRE SONG COVER FOR { pos_song }: "{ pos_lyrics }"'

    print(f"""
        Positive: {inp[1]}

        Negative: {inp[2]}
    """)
    
    img = pipe_generate(pos,neg)

    draw = ImageDraw.Draw(img)

    rows = 1
    labes_distance = 1 // 3

    textheight=min(( width // 10 ), ( height // 5 ))
    font = ImageFont.truetype(r"Alef-Bold.ttf", textheight)
    textwidth = draw.textlength(pos_song,font)
    x = (width - textwidth) // 2
    y = (height - (textheight * rows // 2)) // 2
    y = y - (y // labes_distance)
    draw.text((x, y), pos_song, (255,255,255), font=font)

    textheight=min(( width // 12 ), ( height // 6 ))
    font = ImageFont.truetype(r"Alef-Bold.ttf", textheight)
    textwidth = draw.textlength(pos_artist,font)
    x = (width - textwidth) // 2
    y = (height - (textheight * rows // 2)) // 2
    y = y + (y // labes_distance)
    draw.text((x, y), pos_artist, (255,255,255), font=font)
    
    name = generate_random_string(12) + ".png"
    img.save(name)
    return name

def ui():
    with gr.Blocks(theme=gr.themes.Citrus(),css=css,js=js) as demo:
        gr.Markdown(f"""
            # Song Cover Image Generator
        """)
        with gr.Row():
            with gr.Column():
                artist = gr.Textbox(
                    placeholder="Artist name",
                    container=False,
                    max_lines=1
                )
            with gr.Column():
                song = gr.Textbox(
                    placeholder="Song name",
                    container=False,
                    max_lines=1
                )
            with gr.Column():
                genre = gr.Textbox(
                    placeholder="Genre",
                    container=False,
                    max_lines=1
                )
        with gr.Row():
            lyrics = gr.Textbox(
                placeholder="Lyrics (English)",
                container=False,
                max_lines=1
            )
        with gr.Row():
            cover = gr.Image(interactive=False,container=False,elem_classes="image-container", label="Result", show_label=True, type='filepath', show_share_button=False)
        with gr.Row():
            run = gr.Button("Generate",elem_classes="btn")

        gr.on(
            triggers=[
                run.click
            ],
            fn=handle_generate,
            inputs=[artist,song,genre,lyrics],
            outputs=[cover]
        )
        demo.queue().launch()

# entry

if __name__ == "__main__":
    ui()

# end