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# Agentic AI Vision System: Object Segmentation with SAM 3 and Qwen

**[PyImageSearch](https://daily.dev/sources/pyimagesearch)** · 35 min read · 2 upvotes · 0 comments

## Summary

A step-by-step tutorial on building an agentic AI vision system that combines SAM 3 (open-vocabulary segmentation) with Qwen2.5-VL (vision-language model) to perform iterative, self-correcting object segmentation. The system interprets natural language instructions, converts them into segmentation prompts, runs SAM 3, verifies results with the VLM, and refines prompts in a feedback loop until the correct object is segmented. Full Python code is provided covering model loading, VLM inference, SAM 3 text-prompted segmentation, the agentic loop with iterative refinement, and result visualization.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://pyimagesearch.com/2026/04/06/agentic-ai-vision-system-object-segmentation-with-sam-3-and-qwen/>

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- [SAM 3: Concept-Based Visual Understanding and Segmentation](https://daily.dev/posts/sam-3-concept-based-visual-understanding-and-segmentation-gwnb1xefs) · PyImageSearch · 2 upvotes · 0 comments

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Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#python](https://daily.dev/tags/python), [#computer-vision](https://daily.dev/tags/computer-vision), [#transformers](https://daily.dev/tags/transformers), [#agentic-ai](https://daily.dev/tags/agentic-ai)

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