This is my Object Detection project using YOLOv8 on a COCO subset. I prepared the dataset, trained the model, performed inference and visualization, and evaluated its performance. The repo demonstrates the complete workflow with results and metrics for effective object detection.

Object Detection using YOLOv8 trained on MS-COCO dataset (GUI included)

Streamlit deployment of YOLOv8 object detection (COCO dataset)

Object Detection using YOLOv8 on COCO dataset + real-world test image

This is a demo of YOLOv8 object detection model optimized with OpenVINO Toolkit. (uses simple COCO dataset)

A Traffic Management Solution For Indian Roads - YOLOv8 and COCO Object Detection, as well as Use of a Novel Priority Algorithm

Developed an object detection pipeline using YOLOv8 on the COCO dataset, with evaluation via mAP, IoU, and calibration metrics. Performed error analysis with TIDE to identify detection weaknesses across object scales.

Real-Time Object Detection System using YOLOv8 and Streamlit that detects objects in images and videos using a pretrained deep learning model trained on the COCO dataset.

Industry-oriented deep learning object detection system using YOLOv8 & COCO dataset — detects and localizes multiple objects in real-time images with bounding boxes, confidence scores, and mAP evaluation metrics

Real-time object detection web app powered by YOLOv8 — detects 80 COCO classes via image upload or live webcam. Deployed with Flask. Detected 29 objects in a single image with 92% confidence.

This repository showcases object detection using YOLOv8 and Python. It covers model training on a custom COCO dataset, evaluating performance, and performing object detection on sample images. The trained model is exported in ONNX format for flexible deployment. Perfect for getting started with YOLO-based object detection tasks!

This project uses the YOLOv8 (You Only Look Once) deep learning model to perform real-time object detection using your webcam. Built with Python and OpenCV, it detects 80+ common objects from the COCO dataset and displays bounding boxes, class labels, and confidence scores live on the video feed.

YOLOv8, a state-of-the-art object detection model, excels in speed and accuracy, identifying objects it is trained to recognize. Pre-trained on the COCO dataset, it detects common objects like people and vehicles but lacks the ability to identify license plates. To address this, the model is fine-tuned with a labeled dataset for 100 epochs, enablin

echnical benchmark comparing YOLOv8 (2024) and YOLO26 (2026, NMS-Free) across three inference modes on a Tesla T4 GPU: Oriented Bounding Box (OBB) for aerial/satellite imagery, Standard Detection (COCO) for general-purpose video, and SAHI (Slicing Aided Hyper Inference) for small-object recall enhancement.

This system detects road potholes using a YOLOv8 object detection model trained with the COCO dataset. A camera is used to processe footage and when a pothole is detected, a signal is send through a serial port to notify a connected device. The system provides a comprehensive solution for safe navigation and road maintenance.

Powerful Object Detection in a Blink Ultralytics' YOLOv8 blends lightning-fast processing with pinpoint accuracy for object detection in images and videos also cameras.

A comprehensive analysis of the impact of image preprocessing techniques on object detection accuracy using YOLOv8, with side-by-side visual comparisons and performance metrics.

Object Detection using YOLOv8, Ultralytics, and COCO dataset

YOLOv8 Object Detection Web App - Upload videos and detect objects using COCO-trained YOLOv8

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Complete end-to-end pipeline: COCO dataset conversion, YOLOv8 training, real-time inference & interactive Gradio dashboard. Features automated data preprocessing, performance metrics visualization, FPS monitoring & web-based detection interface. Ready for production deployment.

This project demonstrates how to perform object detection using YOLOv8 on a selected subset of the COCO dataset using Google Colab. The goal of this project is educational: to help beginners understand how object detection works by training YOLO on a small number of COCO classes (e.g., person and car) instead of the full dataset.

End-to-end object detection pipeline using COCO dataset and YOLOv8

YOLOv8 object detection on COCO — training, evaluation, and real-time predictions.

Fine tuning a deep learning model Yolov8 for object detection using coco dataset

Cross-domain object detection/tracking evaluation tool for robotics datasets (YOLOv8, Grounding DINO, ByteTrack, COCO mAP)

Comparative analysis of YOLOv8 architectural enhancements (CBAM vs. CoordConv) using the COCO 2017 dataset for object detection.

Object Detection with tensorflow js and roboflow, which is tensorflow using coco ssd model, and roboflow using yolov8 model.

Real time AI camera combining YOLOv8 (COCO + OpenImages) with Weighted Box Fusion for broad spectrum, duplicate-free object detection.

A Traffic Management Solution For Indian Roads - YOLOv8 and COCO Object Detection, as well as Use of a Novel Priority Algorithm.