YoloV3 in Pytorch and Jupyter Notebook
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Updated
Aug 3, 2019 - Jupyter Notebook
YoloV3 in Pytorch and Jupyter Notebook
This notebook implements an object detection based on a pre-trained model - YOLOv3. The model architecture is called a “DarkNet” and was originally loosely based on the VGG-16 model.
Detect objects in a video and displays them using Mpimg in the notebook
This contains array of python notebooks which describes how we can create Annotation file for Yolo Object Detection without any Tool
Repository with python notebooks for training and testing YOLOV3 and YOLOV4 models for multiclass object detection
Repo to store code for #66DaysOfData challenge by Ken Jee. Includes notebooks and code for different concepts and technologies in data science for learning purposes.
Object Detection and depth EStimation. A deep learning course project.
Welcome to this repository for object detection using the Indoor Object Detection Dataset by Adhikari and Bishwo. This repository contains a Colab notebook that demonstrates how to train an object detector using the dataset.
This project implements object detection using YOLOv3 with pre-trained weights. It supports live detection from a webcam, image detection, and video detection. The application is built using Python with libraries such as OpenCV, PIL, and Tkinter for the GUI, and runs primarily through a Jupyter Notebook interface.
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