Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes
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Updated
Jul 19, 2024 - Python
Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes
Firescrew - Spotting moving objects on your RTSP network cameras faster than a caffeinated cat!
Open Toolkit for Painless Object Detection
mmdetection3d 代码重点注解笔记
YOLO Algorithm (Yolov2 model) trained on COCO Dataset for Object Detection
Tensorflow Advanced Technique Specialization - Solution
YOLO is a state-of-the-art, real-time object detection algorithm. In this notebook, I had applied the YOLO algorithm to detect objects in images ,videos and webcam
Using YOLOv8 to build a Object Classifier/Tracker for RBG/Thermal Cameras
Repository contains RetinaNet,Yolov3 and Faster RCNN for multi object detection on SIMD Dataset http://vision.seecs.edu.pk/simd/
Explore the Computer Vision Interview Prep repository! This GitHub collection offers interview questions and answers for Data Scientists. Elevate your knowledge of computer vision, confidently tackle technical interviews, and succeed in the dynamic field of data science with a focus on computer vision applications.
YOLO version 3 implementation in TensorFlow 2
This a simple comparison and benefits of the pre-trained weights model vs the random weights model
Custom Dataset Training pipeline using Pytorch and Meta's object detection model DETR.
Python library for Object Detection metrics.
This is an Object Detection Web App built using Flask. It is developed using OpenCV4.4.0 by re-using a pre-trained TensorFlow Object Detection Model API trained on the COCO dataset.
Object Detection and Tracking using yolov3 and deepsort
Sini Dek Dekat Yanda is software dangerous object detection.
Object Detection With YOLO
Custom object detection model for low clearance signs
This project demonstrates object detection using YOLOv5. The model is trained on a custom dataset and can detect objects in new images. YOLOv5 is a state-of-the-art object detection model known for its speed and accuracy, making it suitable for real-time applications.
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