Pierre Raybaut
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.
CODRA
Executive Vice President
@pierreraybaut
Session
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.