2026-07-21 –, Room 1.19 (Ground Floor, Shannon)
In the field of non-destructive testing, the French Alternative Energies and Atomic Energy Commission (CEA) entrusted CODRA with the specification and development of software for the automatic reconstruction of radiographic scenes from partial X-ray images.
The challenge was to assemble a full-field X-ray scene from multiple acquisitions obtained by moving a detector or juxtaposing imaging plates, without any prior metadata regarding position, orientation, or magnification.
The reconstruction processing pipeline includes several key steps:
- image pre-processing and denoising,
- robust blob detection,
- homography estimation for geometric correction,
- fusion of corrected sub-images into a coherent global scene.
The entire workflow was developed using open-source scientific Python libraries (NumPy, SciPy, scikit-image, OpenCV) and prototyped interactively with DataLab, an open-source platform for signal and image processing. DataLab was remotely controlled to dynamically visualize intermediate results, tune parameters, and validate geometric transformations step by step.
This project illustrates how the scientific Python ecosystem enables the development of industrial-grade imaging software, from interactive prototyping to automated deployment, using 100% open-source components.
This talk presents a real-world industrial application of scientific Python in the domain of X-ray imaging and geometric reconstruction.
Unlike traditional image stitching techniques that rely on overlapping textures or acquisition metadata, this method is entirely driven by content-based detection of patterns embedded in the scene. Each sub-image undergoes a sequence of transformations culminating in the estimation of a homography, allowing precise alignment within a global coordinate system.
A key aspect of the project was the ability to prototype, debug, and validate a highly parameterized image processing pipeline. Using DataLab, developers could:
- interactively inspect intermediate images,
- visualize detected patterns and geometric annotations,
- adjust thresholds and filtering parameters,
- compare transformation models in real time.
This is a novel approach that significantly accelerated development and debugging, enabling rapid iteration on the image processing pipeline. The live demonstration will showcase how DataLab facilitated the development process, providing insights into the algorithm's behavior and ensuring robustness before integration into a production software tool.
The talk will include:
- a walkthrough of the reconstruction strategy,
- a discussion of the image processing challenges involved,
- a live or recorded demonstration of the interactive prototyping environment with DataLab,
- reflections on software architecture and reproducibility in scientific imaging workflows.
This case study demonstrates how open-source scientific Python, especially when combined with interactive platforms like DataLab, can power advanced geometric reconstruction tasks in high-stakes industrial environments.
Pierre Raybaut is a physicist and software engineer — with a background in optics and photonics engineering and a PhD in femtosecond lasers — known for creating Spyder, the Scientific Python IDE, as well as Python(x,y) and WinPython, tools that helped establish Python as a first-class language for scientific computing.
He started his career as a research engineer at THALES Avionics, then spent over a decade at the French Alternative Energies and Atomic Energy Commission (CEA) as lead software developer, project manager for the Laser Mégajoule timing and fiducial system, and head of a research laboratory. Since 2018, he has been at CODRA, an industrial software company based in France, where he serves as Executive Vice President.
Pierre remains an active open-source contributor. Beyond Spyder, he created guidata, PlotPy, the PlotPyStack ecosystem, and DataLab, an open-source platform for scientific and technical data processing and visualization.
Domaines science et structure de la matière, mesures physiques et micro-électronique informatique industrielle, ingénieur au CEA. Collaborations scientifiques dans le domaine des expériences plasmas laser-matière, instabilités paramétriques, instabilités hydrodynamiques, équations d’état. Contribution au programmes NIF et LMJ. Activités actuelles dans le cadre de la sécurité globale, radiographies à basse et haute énergies.