audiocraft/utils/extend.py

import torch
import math
from audiocraft.models import MusicGen
import numpy as np
from PIL import Image, ImageDraw, ImageFont, ImageColor
import string
import tempfile
import os
import textwrap

def separate_audio_segments(audio, segment_duration=30, overlap=1):
    sr, audio_data = audio[0], audio[1]

    total_samples = len(audio_data)
    segment_samples = sr * segment_duration
    overlap_samples = sr * overlap

    segments = []
    start_sample = 0

    while total_samples >= segment_samples:
        end_sample = start_sample + segment_samples
        segment = audio_data[start_sample:end_sample]
        segments.append((sr, segment))

        start_sample += segment_samples - overlap_samples
        total_samples -= segment_samples - overlap_samples

    # Collect the final segment
    if total_samples > 0:
        segment = audio_data[-segment_samples:]
        segments.append((sr, segment))
    print(f"separate_audio_segments: {len(segments)} segments")
    return segments

def generate_music_segments(text, melody, MODEL, seed, duration:int=10, overlap:int=1, segment_duration:int=30):
    # generate audio segments
    melody_segments = separate_audio_segments(melody, segment_duration, overlap) 
    
    # Create a list to store the melody tensors for each segment
    melodys = []
    output_segments = []
    
    # Calculate the total number of segments
    total_segments = max(math.ceil(duration / segment_duration),1)
    # account for overlap
    duration = duration + (max((total_segments - 1),0) * overlap)
    total_segments = max(math.ceil(duration / segment_duration),1)
    #calc excess duration
    excess_duration = segment_duration - (total_segments * segment_duration - duration)
    print(f"total Segments to Generate: {total_segments} for {duration} seconds. Each segment is {segment_duration} seconds. Excess {excess_duration}")

    # If melody_segments is shorter than total_segments, repeat the segments until the total_segments is reached
    if len(melody_segments) < total_segments:
        #fix melody_segments
        for i in range(total_segments - len(melody_segments)):
            segment = melody_segments[i]
            melody_segments.append(segment)
        print(f"melody_segments: {len(melody_segments)} fixed")

    # Iterate over the segments to create list of Meldoy tensors
    for segment_idx in range(total_segments):
        print(f"segment {segment_idx + 1} of {total_segments} \r")
        sr, verse = melody_segments[segment_idx][0], torch.from_numpy(melody_segments[segment_idx][1]).to(MODEL.device).float().t().unsqueeze(0)

        print(f"shape:{verse.shape} dim:{verse.dim()}")
        if verse.dim() == 2:
            verse = verse[None]
        verse = verse[..., :int(sr * MODEL.lm.cfg.dataset.segment_duration)]
        # Append the segment to the melodys list
        melodys.append(verse)

    torch.manual_seed(seed)
    for idx, verse in enumerate(melodys):
        print(f"Generating New Melody Segment {idx + 1}: {text}\r")
        output = MODEL.generate_with_chroma(
            descriptions=[text],
            melody_wavs=verse,
            melody_sample_rate=sr,
            progress=True
        )

        # Append the generated output to the list of segments
        #output_segments.append(output[:, :segment_duration])
        output_segments.append(output)
        print(f"output_segments: {len(output_segments)}: shape: {output.shape} dim {output.dim()}")
    return output_segments, excess_duration

def save_image(image):
    """
    Saves a PIL image to a temporary file and returns the file path.

    Parameters:
    - image: PIL.Image
        The PIL image object to be saved.

    Returns:
    - str or None: The file path where the image was saved,
        or None if there was an error saving the image.

    """
    temp_dir = tempfile.gettempdir()
    temp_file = tempfile.NamedTemporaryFile(suffix=".png", dir=temp_dir, delete=False)
    temp_file.close()
    file_path = temp_file.name

    try:
        image.save(file_path)
        
    except Exception as e:
        print("Unable to save image:", str(e))
        return None
    finally:
        return file_path

def hex_to_rgba(hex_color):
    try:
        # Convert hex color to RGBA tuple
        rgba = ImageColor.getcolor(hex_color, "RGBA")
    except ValueError:
        # If the hex color is invalid, default to yellow
        rgba = (255,255,0,255)
    return rgba

def add_settings_to_image(title: str = "title", description: str = "", width: int = 768, height: int = 512, background_path: str = "", font: str = "arial.ttf", font_color: str = "#ffffff"):
    # Create a new RGBA image with the specified dimensions
    image = Image.new("RGBA", (width, height), (255, 255, 255, 0))
    # If a background image is specified, open it and paste it onto the image
    if background_path == "":
        background = Image.new("RGBA", (width, height), (255, 255, 255, 255))
    else:
        background = Image.open(background_path).convert("RGBA")

    #Convert font color to RGBA tuple
    font_color = hex_to_rgba(font_color)

    # Calculate the center coordinates for placing the text
    text_x = width // 2
    text_y = height // 2
    # Draw the title text at the center top
    title_font = ImageFont.truetype(font, 26)  # Replace with your desired font and size
    title_text = '\n'.join(textwrap.wrap(title, width // 12))
    title_x, title_y, title_text_width, title_text_height = title_font.getbbox(title_text)
    title_x = max(text_x - (title_text_width // 2), title_x, 0)
    title_y = text_y - (height // 2) + 10  # 10 pixels padding from the top
    title_draw = ImageDraw.Draw(image)
    title_draw.multiline_text((title_x, title_y), title, fill=font_color, font=title_font, align="center")
    # Draw the description text two lines below the title
    description_font = ImageFont.truetype(font, 16)  # Replace with your desired font and size
    description_text = '\n'.join(textwrap.wrap(description, width // 12))
    description_x, description_y, description_text_width, description_text_height = description_font.getbbox(description_text)
    description_x = max(text_x - (description_text_width // 2), description_x, 0)
    description_y = title_y + title_text_height + 20  # 20 pixels spacing between title and description
    description_draw = ImageDraw.Draw(image)
    description_draw.multiline_text((description_x, description_y), description_text, fill=font_color, font=description_font, align="center")
    # Calculate the offset to center the image on the background
    bg_w, bg_h = background.size
    offset = ((bg_w - width) // 2, (bg_h - height) // 2)
    # Paste the image onto the background
    background.paste(image, offset, mask=image)

    # Save the image and return the file path
    return save_image(background)