google-gemini/cookbook
Feb 2025 – Feb 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
3D ReconstructionComputer VisionData AnalysisPython Programming
Jacky Liang
PROFILE
Jacky Liang
Jacky Liang developed a multi-view correspondence and 2D point trajectory feature for the spatial understanding notebook in the google-gemini/cookbook repository. Leveraging Python and Jupyter Notebook, Jacky implemented multi-view geometry techniques to enable analysis of 3D scenes from multiple camera perspectives. This addition allows users to track and analyze spatial relationships across views, supporting advanced computer vision workflows and data analysis within interactive notebooks. The work focused on enhancing research throughput and demonstration readiness for multi-camera scenarios. While the contribution was limited to a single feature over one month, it demonstrated depth in 3D reconstruction and spatial data visualization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,514
Activity Months1
Your Network
36 peopleWork History
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 — google-gemini/cookbook: Focused on expanding spatial understanding capabilities with multi-view analysis. Key feature delivered: Multi-view correspondence and 2D point trajectories added to the spatial understanding notebook, enabling analysis of 3D scenes from multiple camera perspectives. Commit: 28fc33fbc2189a30a682148165ea6049ffa93db0 (Multi-view correspondence and 2D point trajectories (#478)). Major bugs fixed: none reported this month. Overall impact: enables cross-view analytics in notebooks, improves research throughput and demonstration readiness for multi-camera workflows. Technologies/skills demonstrated: Python-based notebooks, multi-view geometry, data visualization in notebooks, version-controlled feature delivery.
1 Commits • 1 Features
Feb 1, 2025February 2025 — google-gemini/cookbook: Focused on expanding spatial understanding capabilities with multi-view analysis. Key feature delivered: Multi-view correspondence and 2D point trajectories added to the spatial understanding notebook, enabling analysis of 3D scenes from multiple camera perspectives. Commit: 28fc33fbc2189a30a682148165ea6049ffa93db0 (Multi-view correspondence and 2D point trajectories (#478)). Major bugs fixed: none reported this month. Overall impact: enables cross-view analytics in notebooks, improves research throughput and demonstration readiness for multi-camera workflows. Technologies/skills demonstrated: Python-based notebooks, multi-view geometry, data visualization in notebooks, version-controlled feature delivery.
February 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
3D ReconstructionComputer VisionData AnalysisPython Programming
Repositories Contributed To
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