Month: 2025-10 | Repository: luxonis/depthai-core Overview: Focused on expanding test coverage for Python bindings to improve reliability and prevent regressions in the PointCloudData API. Delivered targeted tests for the PointCloudData Python bindings to verify set/get point data for both uncolored and RGB point data, strengthening the stability of the Python interface and CI feedback for consumers. Impact: This work reduces post-release defects in the Python bindings, increases developer confidence, and accelerates integration for downstream applications relying on PointCloudData in Python. Greatest value delivered: Early detection of API regressions in the Python bindings, enabling faster debugging and safer releases. Notes: Commit d4a60552f2cf7f78e2ac6f5630ca295c3dae1429 corresponds to the added tests for PointCloudData bindings.

September 2025 monthly summary focusing on delivering stability, performance, and expandability across the DepthAI ecosystem. Key features include a library upgrade to stable 3.0.0 across oak-examples for consistent usage and reduced RC risk, and a stereo-depth example simplification by disabling the median filter. In depthai-core, CI/CD workflows were optimized with precheck gating and merged triggers to reduce CI load and accelerate feedback on PRs labeled testable. Additionally, Python bindings and cross-language samples for PointCloudData (setPoints, setPointsRGB) were added, together with associated tests and C++ examples, broadening accessibility to point-cloud processing. Overall impact: Faster feedback cycles, more predictable depth estimation pipelines, and expanded developer tooling for point-cloud workflows, enabling quicker experimentation and more reliable releases. Technologies/skills demonstrated include release management, CI/CD automation, Python/C++ bindings and samples, CMake configuration, and cross-repo coordination.