Gerb2tiff Tips: Best Settings for High-Quality TIFFs

Automating PCB Renderings with Gerb2tiffPrinted circuit board (PCB) designers, manufacturing engineers, and documentation specialists often need high-quality bitmap images of PCB layers for fabrication checks, customer previews, assembly guides, and marketing materials. Gerb2tiff is a lightweight, purpose-built tool that converts Gerber files (the standard file format for PCB manufacturing data) into TIFF images. Automating PCB renderings with Gerb2tiff can save time, reduce manual errors, and provide consistent outputs for production workflows. This article explains what gerb2tiff does, why automation helps, typical pipelines, configuration tips, examples, and troubleshooting.

---

What gerb2tiff does and why it matters

Gerber files (.gbr, .GBR, .gbx, .gbrx, .gbr+) describe copper, silkscreen, solder mask, and other PCB layers using vector-like commands. Gerb2tiff rasterizes those vector layer descriptions into TIFF images at user-specified resolutions, with options for layer stacking, color mapping, transparency, and cropping. TIFF is a widely supported, high-quality bitmap format that preserves detail and supports lossless compression — useful for printing, inspection, documentation, and automated visual checks.

Automating gerb2tiff conversions matters because:

• Repetitive manual conversion is time-consuming and error-prone.
• Automated scripts ensure consistent DPI and color mapping across batches.
• Integration into CI/CD-like manufacturing pipelines enables gate checks (e.g., verifying copper pours, identifying missing drill hits) before sending files to fabrication.
• Automated archiving of rendered images creates a visual record tied to every revision.

---

Typical automation use cases

• Batch rendering of all PCB revisions to TIFF for archive or release notes.
• Generating layer images for visual diffs between versions (useful in design reviews).
• Creating high-resolution images for assembly instructions, silkscreen proofs, or marketing renders.
• Feeding TIFFs into image analysis/inspection tools to detect anomalies automatically.
• Integrating into Git hooks or CI systems to render and upload previews when Gerber files change.

---

Core components of an automated pipeline

A robust automation pipeline typically includes:

• Source ingestion: Gerber, drill (Excellon), and any layer configuration files are collected from design output folders or a VCS (git).
• Conversion engine: gerb2tiff invoked with consistent options (DPI, color mapping, layer order, crop).
• Post-processing: image cropping, labeling, color adjustments, or conversion to other formats (PNG/PDF) if needed.
• Storage and distribution: saving the resulting TIFFs to a file server, artifact storage, or embedding them into release notes.
• Notifications/QA: optional steps such as running image-based checks, generating diffs, or notifying stakeholders.

---

Example automation approaches

1. Simple shell script (Linux/macOS)

• Use a shell script to find Gerber files, run gerb2tiff with preset arguments, and save outputs to a structured directory per board and revision.

1. CI pipeline (GitHub Actions, GitLab CI)

• When Gerber files are pushed, a CI job can run gerb2tiff, commit generated previews to a preview branch or upload them as job artifacts for reviewers.

1. Integration with fabrication portals

• Automatically render TIFF previews for each upload and attach them to the job or send as part of the BOM/package sent to manufacturers.

1. Image analysis integration

• After rendering, pass TIFFs to automated visual-inspection tools or custom scripts (OpenCV, ImageMagick) to check metrics like annular ring sizes, paste mask alignment, or component footprint coverage.

---

Recommended gerb2tiff options and settings

• DPI / resolution: Choose >=300 DPI for print-quality and ≥600 DPI when fine traces or vias must be inspected.
• Layer order and compositing: Define a consistent stacking order (e.g., copper, mask, silkscreen) and use transparency where helpful.
• Color mapping: Use contrasting colors for mask vs copper to ease automated analysis (e.g., copper black, mask green).
• Cropping and margins: Include a small margin to show board edges or exclude excessive whitespace if embedding images into documents.
• Compression: Use TIFF with LZW or no compression when maximum fidelity is needed; choose compression if storage is constrained.

---

Sample workflows

Below are concise, conceptual workflows you can adapt.

• Local batch render:

  1. Export Gerber and drill files from your CAD tool into a versioned folder.
  2. Run a script that iterates through Gerber files and calls gerb2tiff with standardized options.
  3. Save output TIFFs to /renders/{board-name}/{rev}/

• Git-driven preview generation:

  1. Add a CI job that triggers on pushes to the repository of exported Gerbers.
  2. CI checks out the repo, runs gerb2tiff, and uploads TIFFs as artifacts or pushes them into a previews branch.
  3. Reviewers download artifacts or view previews in the CI UI.

• Automated QA with OpenCV:

  1. Render copper and mask TIFFs.
  2. Use OpenCV scripts to detect anomalies (missing copper islands, unexpected clearances).
  3. If anomalies exceed thresholds, fail the pipeline and notify the designer.

---

Practical tips for reliability

• Canonicalize input filenames so scripts can predict layer roles (e.g., *_TOP.gbr, *_BOT.gbr, *_MASK.gbr).
• Validate Gerber integrity before rendering (basic checks for expected commands and coordinate ranges).
• Version the rendering configuration (DPI, color mapping) so older TIFFs can be reproduced exactly.
• Keep a manifest alongside renders that records board name, Gerber commit hash, rendering options, and timestamp.
• Test the pipeline with edge-case Gerbers — very large boards, microvias, custom aperture macros — to ensure gerb2tiff behaves as expected.

---

Troubleshooting common issues

• Missing elements in TIFF: Check that the correct Gerber layer files were supplied and that aperture definitions are present.
• Incorrect scaling: Verify DPI settings and units (inches vs mm) used by gerb2tiff match the Gerber units.
• Performance on large boards: Increase memory or process large boards in tiles; consider lower temporary DPI during checks.
• Colors or transparency look wrong: Confirm layer ordering and any post-processing steps that may alter pixel channels.

---

Example: simple shell script (conceptual)

1. Structure:

• gerbers/
  • boardA_rev1/
    • BOARD_TOP.gbr
    • BOARD_BOT.gbr
    • BOARD_MASK.gbr

1. Script outline:

• Iterate board directories, run gerb2tiff with fixed DPI and color mapping, write to renders/boardA_rev1/*.tiff (Adaptation to your environment and gerb2tiff command-line options is required.)

---

Closing notes

Automating PCB renderings with gerb2tiff reduces manual effort, enforces consistency, and enables downstream automation like visual QA and automated documentation. Start with a small, reproducible pipeline for one board, record your rendering options, and expand to CI or production workflows once stable.