Box Annotations in Sparrow for Structured Data Extraction

Check out my video on Box Annotations in Sparrow for Structured Data Extraction! I’ll show you how the Qwen2.5 vision model pulls bounding box annotations from images based on what you need. Plus, create simple descriptions and confidence score boxes. 

 

Structured Data Annotation with Qwen2.5 VL and MLX-VLM

Qwen2.5 VL can provide bounding box coordinates and confidence values for extracted structured data. This is useful for visual data review and reporting. I will explain with a practical example what prompt should be used to ensure Qwen2.5 returns this data. 

 

LLM Microservice with Instruction Calling

I describe the idea of implementing interaction with LLM through a concept of microservice with instruction calling. This works great for enterprise application use cases, such as data validation, workflor decisions.

 

Local LLM Instruction Processing with Sparrow

I explain how to execute instructions with a payload using a local LLM. This is useful when you want to process your data with an LLM and provide contextual instructions, specifying the desired outcome of what needs to be achieved.