Tingopix

From the Latin tingō (to dye, to colour) and pix (picture element). Colour, at the pixel level.

Tingopix is an open DIY film scanner project for small-gauge film — 8mm, Regular 8, Super 8, and 16mm. It was born out of a simple goal: to digitize home movies and archival film at a quality level that does justice to the original material, without the cost of commercial equipment.

The project is rooted in the Kinograph community, where the build has been documented since before the first line of code was written. It is designed to be reproducible by individuals and small institutions pursuing the preservation of cine-doméstico — home movies and community film collections that deserve better than consumer-grade telecine.

Philosophy

• Archival first. The scanner is a pure data-acquisition bridge. Output is linear, unprocessed, and lossless. Debayering, grading, and delivery are handled downstream in the software of your choice.
• Sensel-native. Tingopix captures and preserves true sensor values before any irreversible processing is applied. What is stored is what the sensor actually measured — nothing more, nothing less.
• Open and attributable. Everything here — hardware, software, and documentation — is published for others to study, build, and improve upon, with attribution.
• Honest about trade-offs. Speed is sacrificed for quality. This is a slow scanner. That is a deliberate choice.
• Gentle on film. Tension-controlled transport designed to be safe for fragile, aging reels that may never run through a projector again.

Archival Context

The following was submitted as a conference session proposal:

Domestic Sensel-Native Archiving: A Recipe for Uncooked Scanning

In the world of film digitization, “raw” image data is inherently “cooked” the moment it is captured. This concept, championed by Reto Kromer at the No Time To Wait series, provides the context for this session: a practical how-to of “uncooked” sensel-native archiving via a DIY 8mm cinefilm scanner. By treating the scanner as a pure data-acquisition bridge, we argue that sensel-data provides the most honest digital representation of the film’s content, within the inherent constraints of a given sensor’s color filter array spectral sensitivity — and demonstrably within the budget of an individual builder. This method creates a fixed, immutable datapoint that is free of typical unknown “hallucinations” introduced by traditional debayering at the point of capture. Our open-source implementation sidesteps other hardware constraints by utilizing the full quantization range of the sensor’s native Bayer mosaic. We present a choice of scanning strategies: producing an “Honest” 1/4-resolution Binned TIFF for a ready-to-use result based strictly on measured values, or a Sensel-TIFF to preserve the option for post-scan debayering choice. This latter approach allows future image representations to evolve with algorithm improvements without ever altering the original, authoritative sensel-record.

The theoretical foundation for this pipeline is Reto Kromer’s lightning talk The Photon Path: from Sensel Values to Pixel Values, presented at No Time to Wait 6 (Den Haag, October 2022) (slides, video). The sensel concept was coined by Charles Poynton for the IMAGO Photon Path Diagram. See reto.ch for his broader body of work on raw data preservation.

Projects

v1 — RPi 4 + IMX477 HQ Camera

The first Tingopix scanner. Operational as of 2026.

Built around a Raspberry Pi 4 and the Sony IMX477 HQ camera module, v1 achieves archival-quality results comparable to commercial scanners costing many times more — at a build cost in line with other community projects.

What makes it different

Most DIY film scanners output a processed RGB image or a standard video file. Tingopix v1 goes further:

• Direct Sensel-RAW capture — 12-bit Bayer data from the IMX477, bypassing picamera2’s RGB pipeline entirely. No irreversible processing on the scanner.
• Calibrated color science — Black Level Correction (BLC), Clipping, and a Color Correction Matrix (CCM) using Rolf Henkel’s scientific tuning file for the RPi HQ sensor, incorporated into picamera2.
• Embedded sprocket metadata — sprocket location data is captured at a separate light level and embedded directly into the rightmost pixels of the RAW array, carrying registration data without a separate file.
• Dual output paths — an Honest Binned TIFF (1/4 resolution, strictly measured values, suitable for HD delivery and upconversion) for immediate usable results; and a full Sensel-TIFF for post-scan debayering to TIFF16 or lossless OpenEXR — the maximum resolution path to professional post-production and color correction.
• Multi-exposure / per-channel capture — separate captures per RGB channel for maximum dynamic range, with or without light intensity control.
• Vision-based frame registration — sprocket hole detection via blue-channel projection profile on a dedicated ROI, enabling electronic stabilization with no physical film gate.
• Hardware → software architecture — mechanical complexity is deliberately minimized; computation and vision do the work that hardware sensors and encoders would otherwise require.

Hardware

Software Stack

File Output Summary

All files are saved as Linear. Gamma is selected and applied in the color grading software. Bit depth: 12–16 bit.

Scan Performance

Status

v1 is operational. The codebase is being cleaned up and documented for public release on this repository. If you are interested in building one, opening an issue or a discussion here is the best way to accelerate that process — knowing there are builders waiting is the strongest incentive to prioritize documentation over development.

Community

• Kinograph Forums — forums.kinograph.cc — where this project grew up
• Blog — tingopix.blogspot.com
• Reddit — r/tingopix
• Website — tingopix.github.io
• Youtube — @tingopix
• Instagram — @tingopix

Acknowledgements

Special thanks to:

• Reto Kromer (AV Preservation by reto.ch) — for his foundational work on sensel-native archival principles, which provide the theoretical context for Tingopix’s pipeline. See the Archival Context section above for the specific citation.
• Rolf Henkel (cpixip) — for his work with the RPi HQ sensor, for sharing his insights into picamera2, and for his scientific tuning file, which is used in the Tingopix color processing pipeline.
• Matthew Epler (matthewepler) — for creating and maintaining the Kinograph forum, which makes projects like this possible.
• The Kinograph community — for years of shared knowledge and open collaboration.

License

Attribution: please credit Tingopix and link to this repository.

A recipe for uncooked scanning.