app.py

from PIL import Image
import numpy as np
import gradio as gr
import paddlehub as hub
import urllib
import cv2
from datasets import load_dataset
import re
import os
import requests

from share_btn import community_icon_html, loading_icon_html, share_js

import torch

from spectro import wav_bytes_from_spectrogram_image
from diffusers import StableDiffusionPipeline

import io
from os import path
from pydub import AudioSegment
import moviepy.video.io.ImageSequenceClip
from moviepy.editor import *
import mutagen
from mutagen.mp3 import MP3

img_to_text = gr.Blocks.load(name="spaces/pharma/CLIP-Interrogator")

language_translation_model = hub.Module(name='baidu_translate')
language_recognition_model = hub.Module(name='baidu_language_recognition')

style_list = ['古风', '油画', '水彩', '卡通', '二次元', '浮世绘', '蒸汽波艺术', 'low poly', '像素风格', '概念艺术', '未来主义', '赛博朋克', '写实风格', '洛丽塔风格', '巴洛克风格', '超现实主义', '探索无限']
style_list_EN = ['Chinese Ancient Style', 'Oil painting', 'Watercolor', 'Cartoon', 'Anime', 'Ukiyoe', 'Vaporwave', 'low poly', 'Pixel Style', 'Conceptual Art', 'Futurism', 'Cyberpunk', 'Realistic style', 'Lolita style', 'Baroque style', 'Surrealism', '']

tips = {"en": "Tips: The input text will be translated into Chinese for generation", 
        "jp": "ヒント: 入力テキストは生成のために中国語に翻訳されます", 
        "kor": "힌트: 입력 텍스트는 생성을 위해 중국어로 번역됩니다"}

count = 0

model_id2 = "riffusion/riffusion-model-v1"
pipe2 = StableDiffusionPipeline.from_pretrained(model_id2, torch_dtype=torch.float16)
pipe2 = pipe2.to("cuda")


def translate_language_example(text_prompts, style_indx):
    return translate_language(text_prompts)

def translate_language(text_prompts):
    global count
    try:
        count += 1
        tips_text = None
        language_code = language_recognition_model.recognize(text_prompts)
        if language_code != 'zh':
            text_prompts = language_translation_model.translate(text_prompts, language_code, 'zh')
    except Exception as e:
        error_text = str(e)
        return {status_text:error_text, language_tips_text:gr.update(visible=False)}
    if language_code in tips:
        tips_text = tips[language_code]
    else:
        tips_text = tips['en']
    if language_code == 'zh':
        return {language_tips_text:gr.update(visible=False), translated_language:text_prompts, trigger_component: gr.update(value=count, visible=False)}
    else:
        return {language_tips_text:gr.update(visible=True, value=tips_text), translated_language:text_prompts, trigger_component:  gr.update(value=count, visible=False)}


word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
word_list = word_list_dataset["train"]['text']


def get_result(text_prompts, style_indx):
    style = style_list[style_indx]
    prompt = "," + style
    for filter in word_list:
        if re.search(rf"\b{filter}\b", text_prompts):
            raise gr.Error("Unsafe content found. Please try again with different prompts.")
        
    model_id = "runwayml/stable-diffusion-v1-5"
    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
    pipe = pipe.to("cuda")
    
    prompt = text_prompts
    image_output = pipe(prompt).images[0]
    
    print("file name: " + image_output.filename)
    
    # Encode your PIL Image as a JPEG without writing to disk
    imagefile = "imageoutput.png"
    #img_np = np.array(image_output[0])
    #img_nparray= cv2.cvtColor(img_np, cv2.COLOR_BGR2RGBA)
    #img_blue_correction = Image.fromarray(img_nparray)
    #img_blue_correction.save(imagefile, img_blue_correction.format)
    image_output[0].save(imagefile, image_output[0].format)
    
    interrogate_prompt = img_to_text(imagefile, fn_index=1)[0]
    print(interrogate_prompt)
    spec_image, music_output = get_music(interrogate_prompt + ", " + style_list_EN[style_indx])
    
    video_merged = merge_video(music_output, image_output)
    return {spec_result:spec_image, video_result:video_merged, status_text:'Success'}

def get_music(prompt):
  spec = pipe(prompt).images[0]
  print(spec)
  wav = wav_bytes_from_spectrogram_image(spec)
  with open("output.wav", "wb") as f:
    f.write(wav[0].getbuffer())
  return spec, 'output.wav'
  
def merge_video(music, img_list):
  #Convert to mp3   
    #music.export("audio.mp3", format="mp3")
    print('wav audio converted to mp3 audio' )
    print('now getting duration of this mp3 audio' )
    #getting audio clip's duration
    audio_length = int(MP3(music).info.length)
    print('Audio length is :',audio_length)
    
    file_name = 'video_no_audio.mp4'
    fps = 12
    slide_time = audio_length
    fourcc = cv2.VideoWriter.fourcc(*'MJPG')
    out = cv2.VideoWriter(file_name, fourcc, fps, (1024, 1024))
    
    for image in img_list:
        cv_img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
        for _ in range(slide_time * fps):
            #cv_img = cv2.resize(np.array(cv_img), (1024, 1024))
            out.write(cv_img)

    out.release()
    
    
    #String a list of images into a video and write to memory
    print('video clip created successfully from images') 
        
    # loading video file
    print('Starting video and audio merge')
    videoclip = VideoFileClip(file_name) #("/content/gdrive/My Drive/AI/my_video1.mp4")
    print('loading video-clip')
       
    # loading audio file
    audioclip = AudioFileClip(music) #.subclip(0, 15)
    print('loading mp3-format audio')  
    # adding audio to the video clip
    mergedclip = videoclip.set_audio(audioclip)
    print('video and audio merged successfully')  
    
    #Getting size and frame count of merged video file
    print('Getting size and frame count of merged video file')
    duration = mergedclip.duration
    frame_count = mergedclip.fps 
    print('duration is:',duration)
    print('frame count :', frame_count)
    mergedclip.to_videofile('mergedvideo.mp4')
    return 'mergedvideo.mp4'

title="文生图生音乐视频 Text to Image to Music to Video"

description="An AI art generation pipeline, which supports text-to-image-to-music task."

css = """
        .gradio-container {
            font-family: 'IBM Plex Sans', sans-serif;
        }
        .gr-button {
            color: white;
            border-color: black;
            background: black;
        }
        input[type='range'] {
            accent-color: black;
        }
        .dark input[type='range'] {
            accent-color: #dfdfdf;
        }
        .container {
            max-width: 730px;
            margin: auto;
            padding-top: 1.5rem;
        }
        #gallery {
            min-height: 22rem;
            margin-bottom: 15px;
            margin-left: auto;
            margin-right: auto;
            border-bottom-right-radius: .5rem !important;
            border-bottom-left-radius: .5rem !important;
        }
        #gallery>div>.h-full {
            min-height: 20rem;
        }
        .details:hover {
            text-decoration: underline;
        }
        .gr-button {
            white-space: nowrap;
        }
        .gr-button:focus {
            border-color: rgb(147 197 253 / var(--tw-border-opacity));
            outline: none;
            box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
            --tw-border-opacity: 1;
            --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
            --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
            --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
            --tw-ring-opacity: .5;
        }
        .footer {
            margin-bottom: 45px;
            margin-top: 35px;
            text-align: center;
            border-bottom: 1px solid #e5e5e5;
        }
        .footer>p {
            font-size: .8rem;
            display: inline-block;
            padding: 0 10px;
            transform: translateY(10px);
            background: white;
        }
        .dark .footer {
            border-color: #303030;
        }
        .dark .footer>p {
            background: #0b0f19;
        }
        .prompt h4{
            margin: 1.25em 0 .25em 0;
            font-weight: bold;
            font-size: 115%;
        }
"""

block = gr.Blocks(css=css)

examples = [
    [
        '蒙娜丽莎，赛博朋克，宝丽来，33毫米',
        '蒸汽波艺术(Vaporwave)'
    ],
    [
        '一条由闪电制成的令人敬畏的龙',
        '概念艺术(Conceptual Art)'
    ],
    [
        'An awesome dragon made of lightning',
        '概念艺术(Conceptual Art)'
    ],
    [
        '嫦娥在时代广场，戏曲',
        '写实风格(Realistic style)'
    ],
    [
        'Peking Opera at New York',
        '探索无限(Explore infinity)'
    ],
    [
        '古风少女',
        '水彩(Watercolor)'
    ],
    [
        '辐射游戏角色',
         '探索无限(Explore infinity)'
    ],
    [
        'Fallout game character',
         '探索无限(Explore infinity)'
    ],
    [
        'Traditional Chinese Painting',
        '古风(Ancient Style)'
    ],
    [
        '原神游戏截图，pixiv, 二次元绘画作品',
        '二次元(Anime)'
    ],
    [
        'Genshin Impact Game Screenshot, pixiv, Anime Painting Artworks',
        '二次元(Anime)'
    ],
    [
        '原神角色设定, 哪吒, pixiv, 二次元绘画',
        '二次元(Anime)'
    ],
    [
        'Genshin Impact Character Design, Harry Potter, pixiv, Anime Painting',
        '二次元(Anime)'
    ],
    [
        '巨狼，飘雪，蓝色大片烟雾，毛发细致，烟雾缭绕，高清，3d，cg感，侧面照',
         '探索无限(Explore infinity)'
    ],
    [
        '汉服少女，中国山水画，青山绿水，溪水长流，古风，科技都市，丹青水墨，中国风',
         '赛博朋克(Cyberpunk)'
    ],
    [
        '戴着墨镜的赛博朋克女孩肖像，在夕阳下的城市中, 油画风格',
        '赛博朋克(Cyberpunk)'
    ],
    [
        'Portrait of a cyberpunk girl with sunglasses, in the city sunset, oil painting',
        '赛博朋克(Cyberpunk)'
    ],
    [
        '暗黑破坏神',
         '探索无限(Explore infinity)'
    ],
    [
        '火焰，凤凰，少女，未来感，高清，3d，精致面容，cg感，古风，唯美，毛发细致，上半身立绘',
         '探索无限(Explore infinity)'
    ],
    [
        '浮世绘日本科幻哑光绘画，概念艺术，动漫风格神道寺禅园英雄动作序列，包豪斯',
         '探索无限(Explore infinity)'
    ],
    [
        '一只猫坐在椅子上，戴着一副墨镜,海盗风格',
        '探索无限(Explore infinity)'
    ],
    [
        '稲妻で作られた畏敬の念を抱かせる竜、コンセプトアート',
        '油画(Oil painting)'
    ],
    [
        '번개로 만든 경외스러운 용, 개념 예술',
        '油画(Oil painting)'
    ],
    [
        '梵高猫头鹰',
        '蒸汽波艺术(Vaporwave)'
    ],
    [
        '萨尔瓦多·达利描绘古代文明的超现实主义梦幻油画',
        '写实风格(Realistic style)'
    ],
    [
        '夕阳日落时，阳光落在云层上，海面波涛汹涌，风景，胶片感',
        '探索无限(Explore infinity)'
    ],
    [
        'Sunset, the sun falls on the clouds, the sea is rough, the scenery is filmy',
        '油画(Oil painting)'
    ],
    [
        '夕日が沈むと、雲の上に太陽の光が落ち、海面は波が荒く、風景、フィルム感',
        '油画(Oil painting)'
    ],
    [
        '석양이 질 때 햇빛이 구름 위에 떨어지고, 해수면의 파도가 용솟음치며, 풍경, 필름감',
        '油画(Oil painting)'
    ],
]

with block:
    gr.HTML(
        """
            <div style="text-align: center; max-width: 650px; margin: 0 auto;">
              <div
                style="
                  display: inline-flex;
                  gap: 0.8rem;
                  font-size: 1.75rem;
                  margin-bottom: 10px;
                  margin-left: 220px;
                  justify-content: center;
                "
              >
              </div> 
              <div
                style="
                  display: inline-flex;
                  align-items: center;
                  gap: 0.8rem;
                  font-size: 1.75rem;
                  margin-bottom: 10px;
                  justify-content: center;
                ">
              <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 15px;">文生图生音乐视频</h1>
              </div> 
              <div
                style="
                  display: inline-flex;
                  align-items: center;
                  gap: 0.8rem;
                  font-size: 1.75rem;
                  margin-bottom: 10px;
                  justify-content: center;
                ">
               <h1 style="font-weight: 900; margin-bottom: 7px;">Text to Image to Music to Video</h1>
              </div> 
              <p style="margin-bottom: 10px; font-size: 94%">
                Powered by <a href="https://huggingface.co/spaces/PaddlePaddle/ERNIE-ViLG" target="_blank">ERNIE-ViLG 2.0</a>, <a href="https://huggingface.co/spaces/Mubert/Text-to-Music" target="_blank">Mubert AI</a>, <a href="https://huggingface.co/spaces/pharma/CLIP-Interrogator" target="_blank">CLIP Interrogator</a> and fffiloni's <a href="https://huggingface.co/spaces/fffiloni/img-to-music" target="_blank">Image to Music</a> projects
              </p>
            </div>
        """
    )
    with gr.Group():
        with gr.Box():
            with gr.Row().style(mobile_collapse=False, equal_height=True):
                text = gr.Textbox(
                    label="Prompt",
                    show_label=False,
                    max_lines=1,
                    placeholder="Enter your prompt, multiple languages are supported now.",
                ).style(
                    border=(True, False, True, True),
                    rounded=(True, False, False, True),
                    container=False,
                )

                btn = gr.Button("Generate image").style(
                    margin=False,
                    rounded=(False, True, True, False),
                )
        language_tips_text = gr.Textbox(label="language tips", show_label=False, visible=False, max_lines=1)
        styles = gr.Dropdown(label="风格(style)", choices=['古风(Ancient Style)', '油画(Oil painting)', '水彩(Watercolor)', 
        '卡通(Cartoon)', '二次元(Anime)', '浮世绘(Ukiyoe)', '蒸汽波艺术(Vaporwave)', 'low poly', 
        '像素风格(Pixel Style)', '概念艺术(Conceptual Art)', '未来主义(Futurism)', '赛博朋克(Cyberpunk)', '写实风格(Realistic style)', 
        '洛丽塔风格(Lolita style)', '巴洛克风格(Baroque style)', '超现实主义(Surrealism)', '探索无限(Explore infinity)'], value='探索无限(Explore infinity)', type="index")
        status_text = gr.Textbox(
            label="处理状态(Process status)",
            show_label=True,
            max_lines=1,
            interactive=False
        )
        
        spec_result = gr.Image()
        video_result = gr.Video(type=None, label='Final Merged video')
        
        trigger_component = gr.Textbox(vaule="", visible=False) # This component is used for triggering inference funtion.
        translated_language = gr.Textbox(vaule="", visible=False)
        
        
        ex = gr.Examples(examples=examples, fn=translate_language_example, inputs=[text, styles], outputs=[language_tips_text, status_text, trigger_component, translated_language], cache_examples=False)
        ex.dataset.headers = [""]

        
        text.submit(translate_language, inputs=[text], outputs=[language_tips_text, status_text, trigger_component, translated_language])
        btn.click(translate_language, inputs=[text], outputs=[language_tips_text, status_text, trigger_component, translated_language])
        trigger_component.change(fn=get_result, inputs=[translated_language, styles], outputs=[spec_result, video_result, status_text])
        
        
        gr.Markdown(
            """  
      Space by [@DGSpitzer](https://www.youtube.com/channel/UCzzsYBF4qwtMwJaPJZ5SuPg)❤️ [@大谷的游戏创作小屋](https://space.bilibili.com/176003)
      [![Twitter Follow](https://img.shields.io/twitter/follow/DGSpitzer?label=%40DGSpitzer&style=social)](https://twitter.com/DGSpitzer)
      ![visitors](https://visitor-badge.glitch.me/badge?page_id=dgspitzer_txt2img2video)
            """
        )
        gr.HTML('''
        <div class="footer">
                    <p>Model：<a href="https://github.com/PaddlePaddle/PaddleHub" style="text-decoration: underline;" target="_blank">PaddleHub</a> and <a href="https://wenxin.baidu.com/ernie-vilg" style="text-decoration: underline;" target="_blank">文心大模型</a>
                    </p>
        </div>
        ''')

block.queue(concurrency_count=128).launch()