Spaces:
Running
Running
File size: 3,777 Bytes
74d2eb9 |
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 |
from pydub.silence import detect_nonsilent
from pydub import AudioSegment
import numpy as np
import re
import os
from rvc.lib.utils import format_title
def process_audio(file_path):
try:
# load audio file
song = AudioSegment.from_file(file_path)
# set silence threshold and duration
silence_thresh = -70 # dB
min_silence_len = 750 # ms, adjust as needed
# detect nonsilent parts
nonsilent_parts = detect_nonsilent(song, min_silence_len=min_silence_len, silence_thresh=silence_thresh)
# Create a new directory to store chunks
file_dir = os.path.dirname(file_path)
file_name = os.path.basename(file_path).split('.')[0]
file_name = format_title(file_name)
new_dir_path = os.path.join(file_dir, file_name)
os.makedirs(new_dir_path, exist_ok=True)
# Check if timestamps file exists, if so delete it
timestamps_file = os.path.join(file_dir, f"{file_name}_timestamps.txt")
if os.path.isfile(timestamps_file):
os.remove(timestamps_file)
# export chunks and save start times
segment_count = 0
for i, (start_i, end_i) in enumerate(nonsilent_parts):
chunk = song[start_i:end_i]
chunk_file_path = os.path.join(new_dir_path, f"chunk{i}.wav")
chunk.export(chunk_file_path, format="wav")
print(f"Segment {i} created!")
segment_count += 1
# write start times to file
with open(timestamps_file, "a", encoding="utf-8") as f:
f.write(f"{chunk_file_path} starts at {start_i} ms\n")
print(f"Total segments created: {segment_count}")
print(f"Split all chunks for {file_path} successfully!")
return "Finish", new_dir_path
except Exception as e:
print(f"An error occurred: {e}")
return "Error", None
def merge_audio(timestamps_file):
try:
# Extract prefix from the timestamps filename
prefix = os.path.basename(timestamps_file).replace('_timestamps.txt', '')
timestamps_dir = os.path.dirname(timestamps_file)
# Open the timestamps file
with open(timestamps_file, "r", encoding="utf-8") as f:
lines = f.readlines()
# Initialize empty list to hold audio segments
audio_segments = []
last_end_time = 0
print(f"Processing file: {timestamps_file}")
for line in lines:
# Extract filename and start time from line
match = re.search(r"(chunk\d+.wav) starts at (\d+) ms", line)
if match:
filename, start_time = match.groups()
start_time = int(start_time)
# Construct the complete path to the chunk file
chunk_file = os.path.join(timestamps_dir, prefix, filename)
# Add silence from last_end_time to start_time
silence_duration = max(start_time - last_end_time, 0)
silence = AudioSegment.silent(duration=silence_duration)
audio_segments.append(silence)
# Load audio file and append to list
audio = AudioSegment.from_wav(chunk_file)
audio_segments.append(audio)
# Update last_end_time
last_end_time = start_time + len(audio)
print(f"Processed chunk: {chunk_file}")
# Concatenate all audio_segments and export
merged_audio = sum(audio_segments)
merged_audio_np = np.array(merged_audio.get_array_of_samples())
#print(f"Exported merged file: {merged_filename}\n")
return merged_audio.frame_rate, merged_audio_np
except Exception as e:
print(f"An error occurred: {e}") |