SEMView - Scientific TIFF Explorer & Optimizer

Release: v2.1.0 — 2026-05-20

A cross-platform GUI application designed as an all-in-one studio for analyzing, viewing, and optimizing scientific TIFF images (specifically tailored for SEM devices). It serves as both a hierarchical metadata viewer and a powerful batch-processing optimizer, seamlessly converting oversized RGB-encoded grayscale files back to optimized single-channel TIFFs without losing structural or proprietary scientific metadata.

What's New in v2.1.0

• Checkbox File Selection: Select multiple files or entire folders inside the directory browser for bulk batch processing.
• Customizable Databar Height: Map any metadata row (such as custom DatabarHeight keys) using a context menu in the Extra Tags table (in addition to PixelSizeX and PixelSizeY).
• Improved Element Clicks: Replaced coordinate hit testing with robust Treeview element-based click identification to ensure reliable checkbox toggles.
• System Root Defaults: Directory browser defaults to logical drives ("This PC" on Windows, "/" on Linux) if no history exists.
• New Icons & Design: Custom-designed folder/file icons with visual checkbox indicators and mountain-themed file icons.

Features

• Unified Studio Interface:
  • File Browser: Expandable directory tree to preview files instantly.
  • Image Preview: Dynamic live-scale image viewer that handles multiple bit-depths.
  • Metadata Explorer: Tabbed table views showing both standard tags and nested proprietary tags (e.g. FEI_HELIOS SEM metadata).
• Core Conversion Engine:
  • TIFF Optimization: Converts bloated 3-channel RGB storing purely grayscale data into single-channel grayscale TIFFs.
  • Compression Choices: ZIP (Deflate, recommended), LZW, or Uncompressed.
  • Configurable Filters: Checkboxes allowing you to skip naturally colored RGB images or force grayscale math across any image.
• Batch Processing:
  • Convert selected files or process entire directory trees recursively directly from the internal file browser.
  • See real-time progress bars, skip logs, and cancel ongoing intensive conversions anytime.
• Metadata Protection:
  • Preserves resolution strings and actively bypasses decoding on complex proprietary tags to re-inject raw byte data, guaranteeing preservation for scientific instruments.

Installation

Option 1: Standalone Executable (Windows & Linux)

You can download the pre-built executables from the Releases page:

• SEMView for Linux or SEMView.exe for Windows.
• Simply run the executable directly. No Python needed!

Option 2: Python Installation

Prerequisites:

• Python 3.7+

Setup:

1. Clone or download the repository.
2. (Optional) Create a virtual environment:

   python -m venv .venv

3. Install dependencies:

   pip install -r requirements.txt

Usage

Launch the application:

python gui.py

GUI Workflow

1. Browse: Use the File Browser pane on the left to navigate your filesystem.
2. Inspect: Click on any .tif or .tiff file.
   • The preview window will render the image securely irrespective of bit-depth.
   • The Metadata tabs on the right will parse standard image logic and nested INI/JSON device parameters.
3. Configure Options:
   • Output Mode: Choose to Add a Suffix, dump copies to a new Output Folder, or strictly Replace Original Files.
   • Compression: Select ZIP (default), LZW, or No Compression.
   • Skip Color Images: Keep this checked to avoid destroying RGB data if a multi-color image is accidentally fed in.
   • Force RGB to Grayscale: Keep this checked to convert images mathematically to a single channel.
4. Convert:
   • Check the boxes next to files/folders and click "Process" to batch-convert all selected items.
   • If no items are checked, clicking "Process" will fall back to processing the currently highlighted/selected file.
5. Logs: Check the bottom log screen tracking skipped files, errors, and successful completions.

Command Line Usage

For scripting, you can call the engine directly from the command line:

python core/convert_tif.py input.tif output.tif

Advanced batch processing scripts can be crafted by looping this base call.

Troubleshooting

• Module Not Found: Ensure you installed tifffile, numpy, and pillow using pip install -r requirements.txt.
• Files Skipped During Batch: By default, the app skips purely 2D grayscale arrays (already optimized) and mismatching RGB colorful arrays. Check the log if you expected them to be processed (or uncheck "Skip Color Images").
• Missing Tags: Some basic core tags (like ImageWidth) inherently change when images undergo matrix processing. The tool intelligently filters them to allow tifffile to rebuild them safely while forcefully passing complex scientific tags untouched.