acetinkaya/Faster-R-CNN-ile-Derin-Ogrenme-Tabanli-Nesne-Tespiti-ve-Dogruluk-Analizi
Faster R-CNN Evrişimsel sinir ağı üzerinde geliştirilen modelin derin öğrenme yöntemleri ile doğruluk tahmini ve analizi: Nesne Tespiti Uygulaması
This project helps anyone who needs to automatically identify and locate specific objects within images, video streams, or real-time webcam feeds. You input visual data (photos, videos, or live camera input) and get back the same visual data with detected objects highlighted by a bounding box and an accuracy percentage. This would be useful for quality control inspectors, surveillance operators, or researchers in computer vision.
No commits in the last 6 months.
Use this if you need to precisely detect and verify the presence of a known object in various visual inputs with a high degree of accuracy.
Not ideal if you need to identify objects that are not yet trained into the system or require real-time detection on extremely resource-constrained devices.
Stars
7
Forks
—
Language
—
License
MIT
Category
Last pushed
Nov 09, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/acetinkaya/Faster-R-CNN-ile-Derin-Ogrenme-Tabanli-Nesne-Tespiti-ve-Dogruluk-Analizi"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
broadinstitute/keras-rcnn
Keras package for region-based convolutional neural networks (RCNNs)
alankbi/detecto
Build fully-functioning computer vision models with PyTorch
sovit-123/fasterrcnn-pytorch-training-pipeline
PyTorch Faster R-CNN Object Detection on Custom Dataset
kenshohara/video-classification-3d-cnn-pytorch
Video classification tools using 3D ResNet
lufficc/SSD
High quality, fast, modular reference implementation of SSD in PyTorch