Spaces:
Paused
Paused
File size: 6,344 Bytes
7fb6157 391222d 7fb6157 e7d2d44 c09190f 391222d 80449f7 391222d c09190f 8252714 1c0a21f 3d381f7 ade087a 8252714 1b28bbd 7fb6157 391222d 7fb6157 c09190f 7fb6157 391222d ade087a e5b0363 ade087a 0ac1d72 c09190f 790ff50 c09190f 790ff50 c09190f ade087a 0ac1d72 ade087a 7fb6157 ade087a 369ed77 e5b0363 0ac1d72 e5b0363 369ed77 e5b0363 0ac1d72 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 |
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")
from share_btn import community_icon_html, loading_icon_html, share_js
def get_prompts(uploaded_image, track_duration, gen_intensity):
prompt = img_to_text(uploaded_image, "ViT-L (best for Stable Diffusion 1.*)", "fast", fn_index=1)[0]
music_result = generate_track_by_prompt(prompt, track_duration, gen_intensity)
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, maxit=20, loop=False):
if loop:
mode = "loop"
else:
mode = "track"
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": 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):
try:
pat = get_pat("[email protected]")
_, tags = get_tags_for_prompts(minilm, mubert_tags_embeddings, [prompt, ])[0]
result = get_track_by_tags(tags, pat, int(duration), gen_intensity, loop=False)
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
css = """
#col-container {max-width: 550px; margin-left: auto; margin-right: auto;}
a {text-decoration-line: underline; font-weight: 600;}
.footer {
margin-bottom: 45px;
margin-top: 10px;
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;
}
.animate-spin {
animation: spin 1s linear infinite;
}
@keyframes spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
#share-btn-container {
display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
}
#share-btn {
all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;right:0;
}
#share-btn * {
all: unset;
}
#share-btn-container div:nth-child(-n+2){
width: auto !important;
min-height: 0px !important;
}
#share-btn-container .wrap {
display: none !important;
}
"""
article = """
<div class="footer">
<p>
Demo by ๐ค <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a>
</p>
</div>
"""
with gr.Blocks(css=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")
with gr.Row():
track_duration = gr.Slider(minimum=20, maximum=120, value=30, step=5, label="Track duration", elem_id="duration-inp")
gen_intensity = gr.Radio(choices=["low", "medium", "high"], value="high", label="Complexity", show_label=False)
generate = gr.Button("Generate Music from Image")
music_output = gr.Audio(label="Result", type="filepath", elem_id="music-output")
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)
gr.HTML(article)
generate.click(get_prompts, inputs=[input_img,track_duration,gen_intensity], 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() |