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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("[email protected]")
_, 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>
"""
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() |