sheet-music

name: sheet-music description: Find and download free piano sheet music. Use when asked about sheet music, piano music, or music scores.

Free Sheet Music Finder

A guide for finding, downloading, and enhancing free piano sheet music.

Part 1: Free Sheet Music Sites (Ranked)

Tier 1: Best Quality

Tier 2: Good Free Options

Key Insights from Reddit

• MuseScore: Filter by high ratings to find quality arrangements
• IMSLP: Best for classical, skip for modern pop
• Free sites for pop = gray area legally, but low risk for personal use
• Most free sites have low-res previews - use AI upscaling (see Part 3)

Part 2: Downloading Sheet Music Images

Many free sites only offer preview images. Here's how to download and combine them:

Download Multiple Pages

mkdir -p /tmp/sheet_music
for i in 1 2 3 4 5 6 7 8; do
  curl -s -o "/tmp/sheet_music/page_$i.jpg" "https://example.com/image-$i.jpg"
done

Combine Images into PDF

cd /tmp/sheet_music && uv run --with pillow python -c "
from PIL import Image
import os

images = []
for f in sorted([x for x in os.listdir('.') if x.endswith('.jpg')]):
    img = Image.open(f).convert('RGB')
    images.append(img)

images[0].save('output.pdf', save_all=True, append_images=images[1:])
print('Created output.pdf')
"

Common EveryonePiano Image URLs

https://www.everyonepiano.com/pianomusic/XXX/XXXXXXX/XXXXXXX-w-s-{1-N}.jpg

Where -w-s- = stave notation, -j-s- = numbered notation

Part 3: AI Upscaling for Low-Res Images

Many free sites provide tiny preview images (often 200x260 pixels). Use EDSR (Enhanced Deep Residual Networks) to upscale with AI.

When to Use

• Images are blurry or pixelated
• Source images are small thumbnails (under 500px)
• Basic upscaling (LANCZOS) isn't enough

One-Liner AI Upscale + PDF

cd /tmp/sheet_music && uv run --with super-image --with pillow python << 'EOF'
from super_image import EdsrModel, ImageLoader
from PIL import Image
import os

model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=4)
os.makedirs('upscaled', exist_ok=True)

images = []
for f in sorted([x for x in os.listdir('.') if x.endswith('.jpg')]):
    pil_img = Image.open(f)
    preds = model(ImageLoader.load_image(pil_img))
    ImageLoader.save_image(preds, f'upscaled/{f}')
    img = Image.open(f'upscaled/{f}').convert('RGB')
    images.append(img)

images[0].save('enhanced.pdf', save_all=True, append_images=images[1:])
print('Done! Created enhanced.pdf')
EOF

Results

• 200x260 → 800x1040 pixels (4x upscale)
• ~23KB → ~176KB per image (8x more detail)
• Uses deep learning to intelligently reconstruct detail

Why EDSR Works Better

EDSR was trained on millions of image pairs - it knows how to reconstruct fine details like text, lines, and musical notation.

Alternative Models

# Better quality (slower):
model = EdsrModel.from_pretrained('eugenesiow/edsr', scale=4)

# 2x upscale only:
model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)