Spaces:
Runtime error
Runtime error
File size: 7,761 Bytes
7fb6157 391222d 7fb6157 e7d2d44 c09190f 391222d 6c0447a 7c7eec0 391222d c09190f 0aab8e8 9129aed 1bd1938 36960e6 7c7eec0 56c3696 36960e6 3f72ed6 56c3696 26beae3 10bb51b 391222d 2b0bcc0 9129aed 7fb6157 6c0447a 734997b 3f72ed6 7893b18 734997b 2a4cc4c 734997b e7e1117 00a9fa5 09e56af 38d399f 30800e2 38d399f 5431daf bdf739a 3622a55 30800e2 bdf739a 82d80a3 bdf739a 892410c bdf739a 892410c 82d80a3 6c0447a 1bd1938 7fb6157 1bd1938 7fb6157 1019525 cd6f6d9 7fb6157 9129aed 7fb6157 1d45d8a 0aaa7a9 7fb6157 c09190f 7fb6157 391222d 0ac1d72 c5bd206 0ac1d72 064b63f 439e8e0 03d90ab 439e8e0 064b63f 559bd0e 0ac1d72 03e0e2d 7fb6157 c819c3d 7fb6157 ade087a e5b0363 2500455 34eddaa e5b0363 faf112e 92ac6d6 c819c3d e0dcf65 0ac1d72 c819c3d 34eddaa 7fb6157 391222d 54b4948 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 |
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
MUBERT_LICENSE = os.environ.get('MUBERT_LICENSE')
MUBERT_TOKEN = os.environ.get('MUBERT_TOKEN')
#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
from utils import get_tags_for_prompts, get_mubert_tags_embeddings
minilm = SentenceTransformer('all-MiniLM-L6-v2')
mubert_tags_embeddings = get_mubert_tags_embeddings(minilm)
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, 'best', 4, fn_index=1)[0]
print(prompt)
pat = get_pat_token()
music_result = get_music(pat, prompt, track_duration, gen_intensity, gen_mode)
#music_result = generate_track_by_prompt(pat, prompt, track_duration, gen_intensity, gen_mode)
#print(pat)
return music_result, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
def get_pat_token():
r = httpx.post('https://api-b2b.mubert.com/v2/GetServiceAccess',
json={
"method": "GetServiceAccess",
"params": {
"email":"mail@mail.com",
"phone":"+11234567890",
"license": MUBERT_LICENSE,
"token": MUBERT_TOKEN,
}
})
rdata = json.loads(r.text)
#print(rdata)
#assert rdata['status'] == 1, "probably incorrect e-mail"
#pat = rdata['data']['pat']
print(rdata['data']['pat'])
return rdata['data']['pat']
def get_music(pat, prompt, track_duration, gen_intensity, gen_mode):
r = httpx.post('https://api-b2b.mubert.com/v2/TTMRecordTrack',
json={
"method": "TTMRecordTrack",
"params":
{
"text": prompt,
"pat": pat,
"mode":"track",
"duration":track_duration,
}
})
rdata = json.loads(r.text)
track=rdata['data']['tasks'][0]['download_link']
print(track)
#assert rdata['status'] == 1, "probably incorrect e-mail"
#track = rdata['data']['tasks']['download_link']
#print(track)
return track
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)
print(rdata)
#assert rdata['status'] == 1, rdata['error']['text']
trackurl = rdata['data']['tasks'][0]
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(pat, prompt, duration, gen_intensity, gen_mode):
try:
_, 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>
</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")
#text_status = gr.Textbox(label="status")
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() |