• 11 min read
What is YOLOv4? A Detailed Breakdown
In this guide, we discuss what YOLOv4 is, the architecture of YOLOv4, and how the model performs.
• 8 min read
What is YOLOv7? A Complete Guide.
In this guide, we discuss what YOLOv7 is, how the model works, and the novel model architecture changes in YOLOv7.
• 6 min read
Detecting Complex and Amorphous Features of Marine Sponges
In this post, Andy Portalatin describes work done for his master's thesis toward detecting complex and amorphous features of marine sponges.
• 9 min read
How to Detect Brand Logos in Videos
Learn how to detect brand logos in Roboflow with a custom-trained object detection model that you can run on videos.
• 6 min read
Comparing Custom Models to Google Cloud Vision API
In this guide, we go over how to evaluate object detection models on Roboflow Universe versus Google Cloud Vision.
• 8 min read
How to Detect Objects with YOLOv8
Learn how to detect objects with YOLOv8 using pre-trained and custom-trained object detection models.
• 7 min read
Automatically Label Product SKUs with Autodistill
In this guide, we show how to automatically label product SKUs (with a manual review stage) using Autodistill.
• 3 min read
Roboflow Video Inference with Custom Annotators
SUMMARY
This tutorial builds a video inference pipeline for logistics monitoring by loading a pre-trained object detection model from Roboflow Universe and running it frame-by-frame on a warehouse video. Custom visual overlays including bounding boxes, class labels, and object tracking are applied to each frame using the
• 5 min read
What is Object Recognition?
In this guide, we discuss what object recognition is, how it works, and how to start using object recognition to solve problems.
• 4 min read
What is Zero-Shot Object Detection?
Learn what zero-shot object detection is, applications for zero-shot object detection, and how to get started with Grounding DINO, a zero-shot model.
• 4 min read
DINO-GPT4-V: Use GPT-4V in a Two-Stage Detection Model
In this guide, we introduce DINO-GPT4V, a model that uses Grounding DINO to detect general objects and GPT-4V to refine labels.
• 5 min read
Experiments with GPT-4V for Object Detection
See our experiments that explore GPT-4V's object detection capabilities.
• 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
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