Python library for YOLOv8 and YOLOv9 small object detection and instance segmentation
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Updated
May 22, 2024 - Python
Python library for YOLOv8 and YOLOv9 small object detection and instance segmentation
Using YOLOv8 and Detectron2 models, this project automates the detection of plant diseases from image data to facilitate early diagnosis and treatment.
Converting COCO annotation (CVAT) to annotation for YOLOv8-seg (instance segmentation) and YOLOv8-obb (oriented bounding box detection)
YoloV8 segmentation NPU for the RK 3566/68/88
A real-time application to monitor leopard in urban or rural areas.
Segmentation of coral reefs in benthic imagery to quantify the long-term growth or decline of coral cover within marine protected areas.
Traffic light recognition
Autonomous drone system utilizing image analysis and dynamic movement adjustments for smoke plume tracking and particle sampling : GAIA-drone-control Project
Infer yolov8-seg models from Ultralytics with ONNXRuntime (no torch required)
Road instance segmentation using YOLOv8 object detection for annotation and the YOLOv8 object detection for segmentation
Google Gemini Demo: "Guess the Country" Game
Road instance segmentation using YOLOv8 object detection for annotation and the YOLOv8 object detection for segmentation
This repository contains a re-implementation of YOLOv8 specifically designed for person detection using PyTorch. It provides a streamlined approach to implement and utilize YOLOv8 for detecting individuals within images.
ROS2 Package for instance segmentation using the YoloV8 segmentation model and a Intel Realsense D435 camera
StepSight Pro uses Roboflow to manage datasets from 'outdoordetection' versions 1 and 2. With YOLOv8n's pretrained model, it utilizes Ultralytics' YOLO for training on 'outdoorDetection-2' data. Explore the implementation at StepSightPro."
YOLOx8 model segmentation for face features
🚀 YOLO to COCO Conversion: Easily convert YOLO annotation format to COCO JSON using a Streamlit app. Customize categories, visualize annotations, and download JSON output. Perfect for computer vision projects!
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