PostalDataPI
Smarty
Melissa Data Quality
OpenCV
Pandas
Scikit-learn
NumPy
Dataiku
Exploratory
htm.java
Figure Eight
PostalDataPI is a global postal code validation and enrichment API covering 240+ countries and territories. One API, one key, one flat rate โ $0.000028 per query with no tiers or subscriptions.
What you get back: Up to 18 metadata fields per postal code โ city, state/region, coordinates, timezone, three levels of administrative hierarchy, elevation, and more. Sub-5ms cached responses.
Works everywhere: US ZIP codes, UK postcodes, German PLZ, Japanese postal codes, Canadian FSAs, and 230+ more. Format normalization handles case, spacing, and hyphen variations automatically.
Get started in 60 seconds: 1,000 free queries on signup, no credit card required. SDKs for Python and Node.js. MCP server for AI agents (Claude, Cursor, etc.).
Built for developers: REST API, consistent JSON responses across all countries, OpenAPI spec, llms.txt for AI agent discovery.
PostalDataPI OpenCVBased on our record, OpenCV seems to be more popular. It has been mentiond 62 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
OpenCV is the world's largest open-source computer vision library, supported by the non-profit organization, Open Source Computer Vision Foundation. It offers a wide range of algorithms that cover a variety of tasks, from basic image processing to advanced object recognition and motion analysis. - Source: dev.to / 7 months ago
Google's Gemini and other multimodal models also fit here, especially for mixed-input apps. James Allsopp, Founder of Ask Zyro, suggests, "For anything involving images or mixed inputs, tools like Claude 3 Opus (great for handling long context) or Google's Gemini can work well, depending on what you need for your user interface." These frameworks excel in scenarios requiring visual understanding, such as augmented... - Source: dev.to / 11 months ago
To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isnโt just a tool, itโs a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that donโt just interpret visuals, but... - Source: dev.to / about 1 year ago
Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / about 1 year ago
Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / over 1 year ago
Smarty - Smarty provides address validation, autocomplete, geocoding and reverse geocoding services covering addresses in over 240+ countries.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Melissa Data Quality - Melissa helps companies to harness Big Data, legacy data, and people data (names, addresses, phone numbers, and emails).
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
