File size: 6,523 Bytes
51fb8ef
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
import time
import base64
import gradio as gr
from sentence_transformers import SentenceTransformer

import httpx
import json

import os
import requests
import urllib

from os import path
from pydub import AudioSegment

#img_to_text = gr.Blocks.load(name="spaces/pharma/CLIP-Interrogator")
img_to_text = gr.Blocks.load(name="spaces/fffiloni/CLIP-Interrogator-2")

from share_btn import community_icon_html, loading_icon_html, share_js

def get_prompts(uploaded_image, track_duration, gen_intensity, gen_mode):
  print("calling clip interrogator")
  #prompt = img_to_text(uploaded_image, "ViT-L (best for Stable Diffusion 1.*)", "fast", fn_index=1)[0]
  prompt = img_to_text(uploaded_image, 'fast', 4, fn_index=1)[0]
  print(prompt)
  music_result = generate_track_by_prompt(prompt, track_duration, gen_intensity, gen_mode)
  print(music_result)
  return music_result[0], gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)

from utils import get_tags_for_prompts, get_mubert_tags_embeddings, get_pat

minilm = SentenceTransformer('all-MiniLM-L6-v2')
mubert_tags_embeddings = get_mubert_tags_embeddings(minilm)


def get_track_by_tags(tags, pat, duration, gen_intensity, gen_mode, maxit=20):
    
    r = httpx.post('https://api-b2b.mubert.com/v2/RecordTrackTTM',
                   json={
                       "method": "RecordTrackTTM",
                       "params": {
                           "pat": pat,
                           "duration": duration,
                           "format": "wav",
                           "intensity":gen_intensity,
                           "tags": tags,
                           "mode": gen_mode
                       }
                   })

    rdata = json.loads(r.text)
    assert rdata['status'] == 1, rdata['error']['text']
    trackurl = rdata['data']['tasks'][0]['download_link']

    print('Generating track ', end='')
    for i in range(maxit):
        r = httpx.get(trackurl)
        if r.status_code == 200:
            return trackurl
        time.sleep(1)


def generate_track_by_prompt(prompt, duration, gen_intensity, gen_mode):
    try:
        pat = get_pat("prodia@prodia.com")
        _, tags = get_tags_for_prompts(minilm, mubert_tags_embeddings, [prompt, ])[0]
        result = get_track_by_tags(tags, pat, int(duration), gen_intensity, gen_mode)
        print(result)
        return result, ",".join(tags), "Success"
    except Exception as e:
        return None, "", str(e)

def convert_mp3_to_wav(mp3_filepath):
 
  url = mp3_filepath
  save_as = "file.mp3"
  
  data = urllib.request.urlopen(url)

  f = open(save_as,'wb')
  f.write(data.read())
  f.close()
  
  wave_file="file.wav"
  
  sound = AudioSegment.from_mp3(save_as)
  sound.export(wave_file, format="wav")
  
  return wave_file

article = """
    
    <div class="footer">
        <p>
         
        Follow <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a> for future updates 🤗
        </p>
    </div>
    
    <div id="may-like-container" style="display: flex;justify-content: center;flex-direction: column;align-items: center;margin-bottom: 30px;">
        <p style="font-size: 0.8em;margin-bottom: 4px;">You may also like: </p>
        <div id="may-like" style="display: flex;flex-wrap: wrap;align-items: center;height: 20px;">
            <svg height="20" width="122" style="margin-left:4px;margin-bottom: 6px;">       
                 <a href="https://huggingface.co/spaces/fffiloni/spectrogram-to-music" target="_blank">
                    <image href="https://img.shields.io/badge/🤗 Spaces-Riffusion-blue" src="https://img.shields.io/badge/🤗 Spaces-Riffusion-blue.png" height="20"/>
                 </a>
            </svg>
            <svg height="20" width="192" style="margin-left:4px;margin-bottom: 6px;">       
                 <a href="https://huggingface.co/spaces/Mubert/Text-to-Music" target="_blank">
                    <image href="https://img.shields.io/badge/🤗 Spaces-Mubert_Text_to_Music-blue" src="https://img.shields.io/badge/🤗 Spaces-Mubert_Text_to_Music-blue.png" height="20"/>
                 </a>
            </svg>
        </div>
    </div>

    
"""

with gr.Blocks(css="style.css") as demo:
    with gr.Column(elem_id="col-container"):
        
        gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
                <div
                style="
                    display: inline-flex;
                    align-items: center;
                    gap: 0.8rem;
                    font-size: 1.75rem;
                "
                >
                <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
                    Image to Music
                </h1>
                </div>
                <p style="margin-bottom: 10px; font-size: 94%">
                Sends an image in to <a href="https://huggingface.co/spaces/pharma/CLIP-Interrogator" target="_blank">CLIP Interrogator</a>
                to generate a text prompt which is then run through 
                <a href="https://huggingface.co/Mubert" target="_blank">Mubert</a> text-to-music to generate music from the input image!
                </p>
            </div>""")
    
        input_img = gr.Image(type="filepath", elem_id="input-img")
        music_output = gr.Audio(label="Result", type="filepath", elem_id="music-output").style(height="5rem")
        
        with gr.Group(elem_id="share-btn-container"):
            community_icon = gr.HTML(community_icon_html, visible=False)
            loading_icon = gr.HTML(loading_icon_html, visible=False)
            share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)

        with gr.Accordion(label="Music Generation Options", open=False):
            track_duration = gr.Slider(minimum=20, maximum=120, value=30, step=5, label="Track duration", elem_id="duration-inp")
            with gr.Row():
                gen_intensity = gr.Dropdown(choices=["low", "medium", "high"], value="medium", label="Intensity")
                gen_mode = gr.Radio(label="mode", choices=["track", "loop"], value="track")
        
        generate = gr.Button("Generate Music from Image")

        gr.HTML(article)
    
    generate.click(get_prompts, inputs=[input_img,track_duration,gen_intensity,gen_mode], outputs=[music_output, share_button, community_icon, loading_icon], api_name="i2m")
    share_button.click(None, [], [], _js=share_js)

demo.queue(max_size=32, concurrency_count=20).launch()