srivastavask/cvlab-ai
Jan 2025 – May 2025
3 Months active
Languages Used
Jupyter NotebookPythonCSSHTMLJavaScript
Technical Skills
Code OrganizationComputer VisionData AnalysisData ScienceData VisualizationFile Management
DivyanshRana100
PROFILE
Divyanshrana100
Divyansh worked on the srivastavask/cvlab-ai repository, building a suite of image processing and computer vision tutorials and lab materials over three months. He developed Jupyter notebooks demonstrating techniques such as image resizing, histogram equalization, FFT visualization, and CNN-based classification using Python, OpenCV, and TensorFlow. His work included organizing and refactoring lab content, standardizing file structures, and cleaning legacy code to streamline onboarding and future maintenance. By integrating deep learning models and reproducible workflows, Divyansh enabled both instructional and research use cases, delivering a well-structured codebase that supports rapid prototyping, evaluation, and consistent student learning experiences.
Overall Statistics
Feature vs Bugs
78%Features
Repository Contributions
42Total
Bugs
2
Commits
42
Features
7
Lines of code
8,095
Activity Months3
Your Network
28 peopleSame Organization
@bennett.edu.in5
Work History
May 2025
25 Commits • 2 Features
May 1, 2025May 2025 — srivastavask/cvlab-ai: Bootstrapped the project, cleaned legacy code, and established a solid foundation for ongoing development. Key outcomes include initial project initialization with main entry point, a documented repository structure, and removal of outdated artifacts to reduce maintenance risk. These actions enable faster onboarding, clearer development workflows, and a cleaner baseline for future features.
25 Commits • 2 Features
May 1, 2025May 2025 — srivastavask/cvlab-ai: Bootstrapped the project, cleaned legacy code, and established a solid foundation for ongoing development. Key outcomes include initial project initialization with main entry point, a documented repository structure, and removal of outdated artifacts to reduce maintenance risk. These actions enable faster onboarding, clearer development workflows, and a cleaner baseline for future features.
May 2025
March 2025
4 Commits • 3 Features
Mar 1, 20252025-03 Monthly Summary for srivastavask/cvlab-ai focused on delivering end-to-end tutorials and a lab notebook to accelerate learning, prototyping, and evaluation in image processing and computer vision. The month emphasized business value by providing ready-to-run demonstrations, reproducible workflows, and evaluation artifacts that support both education and research use cases.
March 2025
4 Commits • 3 Features
Mar 1, 20252025-03 Monthly Summary for srivastavask/cvlab-ai focused on delivering end-to-end tutorials and a lab notebook to accelerate learning, prototyping, and evaluation in image processing and computer vision. The month emphasized business value by providing ready-to-run demonstrations, reproducible workflows, and evaluation artifacts that support both education and research use cases.
January 2025
13 Commits • 2 Features
Jan 1, 2025January 2025 performance for srivastavask/cvlab-ai: Delivered two major features—Image Processing Notebooks and Lab Content Organization & Cleanup—driving business value through richer instructional materials and improved repository hygiene. Key features delivered: 1) Image Processing Notebooks with OpenCV covering image resizing with interpolation, general transformations (translation, scaling, rotation, reflection, shear), and basic edge detection (Sobel on grayscale). 2) Lab Content Organization and Cleanup: restructuring notebooks into student-specific folders, standardized file naming, creating placeholders, removing unused files, and uploading asset files. Major bugs fixed: none reported during this period; focus on feature delivery and cleanup to reduce future defect risk. Overall impact: enhances learner onboarding, accelerates student progress, and reduces support overhead by delivering ready-to-use, consistent lab materials. Technologies/skills demonstrated: OpenCV image processing, Jupyter notebooks, Python-based notebook tooling, asset management, and disciplined version control with naming conventions and folder structures.
13 Commits • 2 Features
Jan 1, 2025January 2025 performance for srivastavask/cvlab-ai: Delivered two major features—Image Processing Notebooks and Lab Content Organization & Cleanup—driving business value through richer instructional materials and improved repository hygiene. Key features delivered: 1) Image Processing Notebooks with OpenCV covering image resizing with interpolation, general transformations (translation, scaling, rotation, reflection, shear), and basic edge detection (Sobel on grayscale). 2) Lab Content Organization and Cleanup: restructuring notebooks into student-specific folders, standardized file naming, creating placeholders, removing unused files, and uploading asset files. Major bugs fixed: none reported during this period; focus on feature delivery and cleanup to reduce future defect risk. Overall impact: enhances learner onboarding, accelerates student progress, and reduces support overhead by delivering ready-to-use, consistent lab materials. Technologies/skills demonstrated: OpenCV image processing, Jupyter notebooks, Python-based notebook tooling, asset management, and disciplined version control with naming conventions and folder structures.
January 2025
Activity
Loading activity data...
Quality Metrics
Correctness90.4%
Maintainability90.0%
Architecture87.8%
Performance87.4%
AI Usage23.6%
Skills & Technologies
Programming Languages
CSSHTMLJavaScriptJupyter NotebookPython
Technical Skills
AI IntegrationAI/ML IntegrationAPI IntegrationAutoencodersBackend DevelopmentCSSCode OrganizationComputer VisionConcurrencyData AnalysisData PreprocessingData ScienceData VisualizationDeep LearningE-commerce Search
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline