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 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) pat = get_pat_token() #music_result = get_music(prompt, track_duration, gen_intensity, gen_mode) #music_result = generate_track_by_prompt(pat, prompt, track_duration, gen_intensity, gen_mode) #print(pat) return pat, 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_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) return "done" def get_music(prompt, track_duration, gen_intensity, gen_mode): r = httpx.post('https://api-b2b.mubert.com/v2/TTMRecordTrack', json={ "method": "TTMRecordTrack", "params": { "text":prompt, "pat": "aW1ndG9tdXNpYy4xNzA4Nzg5MS40ZGIxNGM0YjM2NDY4ZDM2OWQ3ZjQ4NTg1NmNiNjg0N2NmYjJmMDZhLjEuMw", "mode":"track", "duration":track_duration, "bitrate":"192" } }) rdata = json.loads(r.text) print(rdata) #assert rdata['status'] == 1, "probably incorrect e-mail" #track = rdata['data']['tasks']['download_link'] #print(track) return "done" 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]['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("mail@mail.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 = """
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Sends an image in to CLIP Interrogator to generate a text prompt which is then run through Mubert text-to-music to generate music from the input image!