A curated collection of tools, scripts, and resources for Google NotebookLM — watermark removal, audio processing, prompt engineering, and more.
🌐 Try the Online Tool → — Free, browser-local, no upload needed
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Google NotebookLM is an incredible AI research tool that generates podcasts, slide decks, videos, and infographics from your documents. But the free tier adds visible watermarks to all exports — and the official removal option (NotebookLM Ultra) costs $250/month.
This repo collects free, open-source, privacy-first tools to solve this problem.
- Online Tools
- Scripts
- Watermark Detection
- Gemini Image Tools
- Audio Processing
- Metadata & Privacy
- NotebookLM Prompts
- Resources
| Tool | Formats | Privacy | Free |
|---|---|---|---|
| NotebookLM Remover | Video, PDF, PPTX, Infographic, Gemini Image, Audio, Metadata | 100% browser-local | ✅ |
| SlideClean | Local Python | ✅ | |
| SlideDeckcleaner.com | Server-side | ✅ |
💡 NotebookLM Remover is the most comprehensive option — it handles 8 format types and runs entirely in your browser using WebAssembly. Your files never leave your device.
# scripts/remove_watermark.py
# Removes NotebookLM watermark from images using connected component analysis
from PIL import Image
import numpy as np
def remove_watermark(image_path, output_path):
"""Remove NotebookLM logo from bottom-right corner."""
img = np.array(Image.open(image_path))
h, w = img.shape[:2]
# Scan bottom-right region (22% width, 8% height)
scan_x = int(w * 0.78)
scan_y = int(h * 0.92)
region = img[scan_y:, scan_x:]
# Detect dark pixels (watermark)
gray = np.mean(region, axis=2)
bg_gray = np.median(gray)
mask = gray < (bg_gray - 60)
# Fill with gradient from surrounding pixels
for y in range(region.shape[0]):
for x in range(region.shape[1]):
if mask[y, x]:
# Sample from above the watermark region
sample_y = max(0, scan_y - 10)
img[scan_y + y, scan_x + x] = img[sample_y, scan_x + x]
Image.fromarray(img).save(output_path)
print(f"Cleaned: {output_path}")
# Usage
remove_watermark("slide_with_watermark.png", "slide_clean.png")#!/bin/bash
# scripts/batch_process.sh
# Convert all PDFs in a folder, remove watermarks, rebuild
for pdf in ./input/*.pdf; do
echo "Processing: $pdf"
# Use the online tool API or local script
python scripts/remove_watermark.py "$pdf" "./output/$(basename $pdf)"
doneNotebookLM watermarks are located at predictable positions:
| Format | Position | Size (1080p) |
|---|---|---|
| Video | Bottom-right | x=1104, y=656, w=770, h=62 |
| Video (720p) | Bottom-right | x=736, y=437, w=513, h=41 |
| PDF/PPTX | Bottom-right corner | ~350×80px scan area |
| Infographic | Bottom-right corner | Variable |
| Video ending | Last 2.5 seconds | "Made with Google" screen |
The online tool uses:
- Connected component analysis on dark pixels in the scan area
- Adaptive threshold (background median - 60/45/80 multi-pass)
- Smart filtering by area, aspect ratio, and position
- Gradient fill interpolation from surrounding pixels
Gemini AI images embed a visible sparkle watermark. The removal is mathematically lossless using alpha channel reversal:
original_pixel = (watermarked_pixel - α × 255) / (1 - α)
This formula perfectly restores the original pixels — no AI inpainting, no quality loss.
| Image Size | Alpha Template |
|---|---|
| ≤1024px | 48px margins |
| >1024px | 96px margins |
| Standard sizes | 1024×1024, 1536×1024, 2816×1536 |
Try Gemini Watermark Remover →
NotebookLM Audio Overview podcasts include intro/outro segments. Tools to trim them:
- NotebookLM Podcast Trimmer — Browser-based, supports MP3/M4A/WAV
- FFmpeg one-liner:
# Trim first 15 seconds and last 20 seconds ffmpeg -i podcast.mp3 -ss 15 -to $(ffprobe -v error -show_entries format=duration -of csv=p=0 podcast.mp3 | awk '{print $1-20}') -c copy trimmed.mp3
AI-generated images contain metadata that reveals their origin (C2PA, EXIF, XMP). To strip it:
- Image Metadata Cleaner — Browser-based, strips all readable metadata
- ExifTool:
exiftool -all= image.jpg - Python:
from PIL import Image; img = Image.open("in.jpg"); img.save("out.jpg")
Effective prompts for NotebookLM content generation:
Create a professional 10-slide presentation about [topic].
Use clear headings, bullet points, and include data visualizations.
Target audience: [audience]. Tone: [formal/casual].
Generate a podcast-style discussion about [topic].
Make it conversational between two hosts.
Duration: approximately 10 minutes.
Include key takeaways at the end.
Create an infographic summarizing [topic].
Use a vertical layout with icons and statistics.
Color scheme: [colors]. Style: [modern/minimal/bold].
See prompts/ for the full prompt collection.
- NotebookLM — Google's AI notebook
- NotebookLM Help
- NotebookLM Plans
- r/notebooklm — Reddit community
- NotebookLM Remover — Free online watermark remover (8 formats, 9 languages)
| Feature | Free Tier | Ultra ($250/mo) | NotebookLM Remover |
|---|---|---|---|
| Watermark on slides | ✅ Yes | ❌ No | ❌ Removed free |
| Watermark on video | ✅ Yes | ❌ No | ❌ Removed free |
| "Made with Google" ending | ✅ Yes | ❌ No | ❌ Trimmed free |
| Privacy | Server-side | Server-side | 100% browser-local |
| Cost | Free | $250/month | Free |
Contributions welcome! See contributing.md.
This work is licensed under CC0 1.0 Universal.