• 14 min read
mAP@0.5 vs. mAP@0.5:0.95: What’s the Difference?
mAP@0.5 uses a single 0.50 IoU threshold; mAP@0.5:0.95 averages ten thresholds from 0.50 to 0.95. See how each is calculated and when to use it.
Blog
Dikshant Shah
I develop end-to-end computer vision pipelines by integrating multiple machine learning models, such as SAM 3 and RF-DETR, to solve diverse real world use cases.
Latest Posts by Dikshant Shah
• 27 min read
Zero-Shot vs. Fine-Tuned Models: When to Train Your Own
Zero-shot vs fine-tuned models: prototype with SAM 3, auto-label your dataset, then train RF-DETR for the accuracy and speed production needs.
• 8 min read
Outsourced Data Labeling in Roboflow
Roboflow offers outsourced labeling via approved partners. Receive the custom annotations you need to train high-quality models.
• 23 min read
Optical Character Recognition (OCR): How It Works
hat optical character recognition is, how OCR works in 5 steps, Tesseract vs EasyOCR vs PaddleOCR vs VLMs, and how to build an OCR pipeline in Roboflow.
• 9 min read
Synthetic Image Generation in Roboflow Workflows with Stability AI
In this guide, learn how to use Roboflow to generate synthetic data with DALL-E and GPT-4 Vision for use in training vision models.
• 15 min read
Best Vision Systems for Manufacturing
Rule-based cameras flag good parts as bad and break when your line changes. See the best vision systems for manufacturing and what scales.
• 13 min read
How to Train a YOLOv11 Object Detection Model on a Custom Dataset
Learn how to train a YOLOv11 object detection model with a custom dataset.
• 9 min read
How to Create a Synthetic Dataset for Computer Vision
Accelerate computer vision model development by generating synthetic images. Learn to build an automated Stability AI pipeline in Roboflow.
• 7 min read
How to Use Tiling During Inference
Discover how image tiling improves small object detection. Learn to apply it during training and inference using Roboflow Workflows.
• 12 min read
How to Deploy Computer Vision Models Offline
In this guide, we walk through how to deploy computer vision models offline using Roboflow Inference.
• 13 min read
How to Train a YOLO26 Oriented Bounding Box (OBB) Model
Learn how to train a YOLO26 Oriented Bounding Boxes model with a dataset labeled on Roboflow.
• 18 min read
How to Use Roboflow for Video-Heavy Pipelines
Learn to build high-throughput video pipelines with ByteTrack, Time-in-Zone logic, and Roboflow Workflows for cloud or edge.
• 14 min read
A Complete Guide to Instance Segmentation
We are excited to release support for instance segmentation projects on Roboflow. In this guide, you will learn the key concepts and practical tools behind instance segmentation
• 14 min read
How to Deploy Computer Vision
In this definitive guide, we break down the decisions required to build a production-grade vision system.
• 12 min read
Zero-Shot Pose Estimation for Robotics
Learn how to use YOLO26-Pose and Roboflow Workflows to build and deploy high-performance, zero-shot pose estimation pipelines for real-time robotics.
• 9 min read
Comparing Cloud and On-Device Inference for Computer Vision Models
Learn how to architect a unified vision pipeline that leverages the speed of edge inference for real-time action while escalating high-complexity tasks to frontier cloud models.
• 9 min read
Detect Small Objects with Roboflow Workflows
Learn how to use Roboflow Workflows to detect small objects with a computer vision model and the SAHI inference technique.
• 11 min read
No-Code Computer Vision API Development
In this guide, you’ll use Roboflow Workflows’ drag-to-connect blocks to build a complete object detection API - then deploy in minutes.
• 6 min read
How to Use Qwen3-VL in Roboflow
In this guide, build an image-understanding workflow in Roboflow that turns Qwen3-VL into a production-ready vision agent you can run via API or on your own GPU.
• 6 min read
When to Use Contrast as a Preprocessing Step
See how contrast preprocessing improves edge detection and boosts model accuracy.
• 8 min read
Depth Anything 3 for Depth Estimation
In this guide, learn what makes DA3 different, where it shines, and how to build a working depth estimation pipeline in Roboflow Workflows that generates real 3D insight in minutes.
• 6 min read
You Might Be Resizing Your Images Incorrectly
Resizing images incorrectly can distort objects and degrade model performance. Learn how to resize images without distortion: aspect ratios, padding strategies, and practical tips to ensure your models learn from clean, consistent visuals.
• 15 min read
Explore the Best Depth Estimation Models
Depth estimation gives machines a 3D understanding of the world. See today’s leading depth estimation models, and learn how to run Depth Anything V2 inside Roboflow Workflows.
• 11 min read
Python Object Detection
Learn Python object detection step-by-step using Roboflow Inference. Run RF-DETR and fine-tuned models from Roboflow Universe on images and videos with ease.
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