• 7 min read
Launch: Roboflow Logistics Pre-trained Object Detection Model
The Roboflow Logistics Model, trained on 99,238 images across 20 classes, offers a domain-specific advantage for logistics vision use cases.
• 9 min read
Enhancing Child Safety with Computer Vision
SUMMARY
Object detection can add a real-time monitoring layer to child safety by alerting caregivers when a child enters a defined hazard zone, such as the area around a swimming pool. This tutorial walks through setting up Roboflow Inference to run a trained detection model, defining polygon boundaries around
• 10 min read
Aerial Fire Detection with Drone Imagery and Computer Vision
In this article, Timothy Malche shows the steps he followed to build an aerial fire detection system with drone imagery and computer vision.
• 6 min read
Using Computer Vision to Improve Railway Safety
In this guide, we show how to use computer vision to identify hazardous situations on railways for use in building safety systems.
• 11 min read
Improving Vision Model Performance Using Roboflow & Tenyks
SUMMARY
A collaboration between Roboflow and Tenyks showing that model performance gains often come from fixing data, not tuning architecture. Using a traffic sign detection model as the test scenario, the workflow covers training a baseline, auditing the Roboflow dataset with Tenyks to surface label errors and class imbalances, correcting
• 4 min read
How to Use SAHI to Detect Small Objects
In this guide, we show how to use the SAHI implementation in the supervision Python package to detect small objects in images.
• 7 min read
Using Computer Vision for Online Exam Proctoring
SUMMARY
This tutorial builds an online exam proctoring system that uses a webcam and Roboflow Inference to detect when a student picks up a phone during a remote assessment. A pre-trained phone detection model from Roboflow Universe is deployed via the Inference API, and the live webcam feed is
• 6 min read
How to Use Computer Vision to Monitor Inventory: Inventory Management AI
SUMMARY
This tutorial builds an inventory monitoring pipeline that extracts video frames at defined time intervals, runs each frame through Roboflow Inference Server against a model trained on packaged shelf items, and outputs structured CSV files (per-object detections, counts per interval, counts by class) along with bar charts showing
• 8 min read
How to Reduce Dataset Size Without Losing Accuracy
Learn how to reduce the size of your computer vision dataset without losing accuracy.
• 7 min read
What is Mask R-CNN? The Ultimate Guide.
In this guide, we discuss what Mask R-CNN is, how it works, where the model performs well, and what limitations exist with the model.
• 8 min read
How to Train RTMDet on a Custom Dataset
Learn how to train a RTMDet computer vision model on a custom dataset.
• 5 min read
Using Stable Diffusion and SAM to Modify Image Contents Zero Shot
SUMMARY
Combining Grounding DINO for zero-shot object detection, SAM for pixel-precise segmentation, and Stable Diffusion for inpainting produces a fully text-driven image editor that requires no manual masking or selection tools. The pipeline takes a text description of the object to modify, uses Grounding DINO to locate
• 6 min read
A LLaMa 2, Midjourney & Autodistill Computer Vision Pipeline
Combine the use of Midjourney, Autodistill, LLaMa 2 and Roboflow to create a object detection model without data collection or labeling.
• 10 min read
How to Use Computer Vision for Environment Monitoring
SUMMARY
Satellite and drone imagery analyzed by computer vision models can measure environmental change at a scale and frequency that manual scientific monitoring cannot match, turning pixel data into quantifiable ESG metrics like built-up area, deforestation extent, water coverage, and crop health. This guide walks through building a remote
• 7 min read
Build a Chess Game Recorder with Computer Vision
SUMMARY
Clio, built by the team at A1H1, is a portable chess recording device that uses computer vision instead of embedded sensors to digitize over-the-board games, bringing the cost well below the roughly $500 USD of sensor-equipped commercial sets. The system handles two distinct problems: detecting the
• 5 min read
Improve Accuracy: Polygon Annotations for Object Detection
SUMMARY
Polygon annotations consistently outperform bounding boxes for object detection when objects have irregular shapes, because polygons eliminate background noise that bounding boxes include. An experiment comparing both annotation types, combined with augmentations (rotation, saturation, cutout, bounding box shear) and pretrained weight initialization, showed meaningful mAP gains at each step.
• 9 min read
Pose Estimation Algorithms: History and Evolution
SUMMARY
Pose estimation, the computer vision task of detecting key body joints in images and video, has progressed from hand-crafted geometric methods in the 1990s through graphical models in the 2000s to convolutional neural network approaches that now dominate the field. This overview traces that arc, covering traditional methods,
• 5 min read
How to Use Generative AI to Augment Computer Vision Data
Dive deep into Kopikat.co, a tool for generative data augmentation created by OpenCV.ai to improve the quality of datasets.
• 4 min read
Detecting Objects with DETIC vs Custom Training
Learn how to evaluate large foundation models and how custom model training can improve performance.
• 4 min read
How to Train DETR on a Custom Dataset
Learn how to train a DETR model on a custom dataset.
• 5 min read
How to Deploy YOLOv8 Using Intel's OpenVINO and Amazon SageMaker
Learn how to deploy an Ultralytics yOLOv8 model using OpenVINO and AWS SageMaker.
• 6 min read
How to Train a YOLOv8 Classification Model
In this guide, we walk through how to train a classification model using YOLOv8 and a dataset hosted on Roboflow.
• 8 min read
Automated Computer Vision Inspection of Physical Pipelines
In this guide, we show how to identify various types of pipeline defects using computer vision.
• 7 min read
How to Train YOLO-NAS on a Custom Dataset
YOLO-NAS is the latest state-of-the-art real-time object detection model. Learn how to train YOLO-NAS on your custom data.
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