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Testing Seed Values
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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))
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)
print(f"total Segments to Generate: {total_segments} for {duration} seconds. Each segment is {segment_duration} seconds")
# If melody_segments is shorter than total_segments, repeat the segments until the total_segments is reached
if len(melody_segments) < total_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
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)