Real time Human Detection Counting

Overview

Real-time-Human-Detection-Counting.

In this Project, I am going to build the Human Detection and Counting System through Webcam [or video or images].

Project Prerequisites

  1. OpenCV: A strong library used for machine learning
  2. Imutils: To Image Processing
  3. Numpy: Used for Scientific Computing. Image is stored in a numpy array.
  4. Argparse: Used to give input in command line.

To run the project, please run below-mentioned commands as per requirements

  1. To give video file as input: python main.py -v ‘Path_to_video’

  2. To give image file as input: python main.py -i ‘Path_to-image’

  3. To use the camera: python main.py -c True

  4. To save the output: Python main.py -c True -o ‘file_name’

Owner
Mir Nawaz Ahmad
Enthusiastic Data scientist eager to contribute to team success through hard work, attention to detail and excellent organizational skills.
Mir Nawaz Ahmad
Source code for the plant extraction workflow introduced in the paper “Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision”

Plant extraction workflow Source code for the plant extraction workflow introduced in the paper "Agricultural Plant Cataloging and Establishment of a

Maurice Günder 0 Apr 22, 2022
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat

Hanzhe Hu 99 Dec 12, 2022
PlaidML is a framework for making deep learning work everywhere.

A platform for making deep learning work everywhere. Documentation | Installation Instructions | Building PlaidML | Contributing | Troubleshooting | R

PlaidML 4.5k Jan 02, 2023
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

Erick Cobos 73 Dec 04, 2022
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution

Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a

Oliver Hahn 16 Dec 23, 2022
TorchX is a library containing standard DSLs for authoring and running PyTorch related components for an E2E production ML pipeline.

TorchX is a library containing standard DSLs for authoring and running PyTorch related components for an E2E production ML pipeline

193 Dec 22, 2022
Datasets and pretrained Models for StyleGAN3 ...

Datasets and pretrained Models for StyleGAN3 ... Dear arfiticial friend, this is a collection of artistic datasets and models that we have put togethe

lucid layers 34 Oct 06, 2022
STMTrack: Template-free Visual Tracking with Space-time Memory Networks

STMTrack This is the official implementation of the paper: STMTrack: Template-free Visual Tracking with Space-time Memory Networks. Setup Prepare Anac

Zhihong Fu 62 Dec 21, 2022
Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps

Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s

Thomas Frerix 40 Dec 17, 2022
Addition of pseudotorsion caclulation eta, theta, eta', and theta' to barnaba package

Addition to Original Barnaba Code: This is modified version of Barnaba package to calculate RNA pseudotorsion angles eta, theta, eta', and theta'. Ple

Mandar Kulkarni 1 Jan 11, 2022
Centroid-UNet is deep neural network model to detect centroids from satellite images.

Centroid UNet - Locating Object Centroids in Aerial/Serial Images Introduction Centroid-UNet is deep neural network model to detect centroids from Aer

GIC-AIT 19 Dec 08, 2022
Python implementation of O-OFDMNet, a deep learning-based optical OFDM system,

O-OFDMNet This includes Python implementation of O-OFDMNet, a deep learning-based optical OFDM system, which uses neural networks for signal processin

Thien Luong 4 Sep 09, 2022
2 Jul 19, 2022
TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular potentials

TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular

TorchMD 104 Jan 03, 2023
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

HUAWEI Noah's Ark Lab 2.6k Jan 01, 2023
an implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation using PyTorch

revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f

Simon Niklaus 59 Dec 22, 2022
VoxHRNet - Whole Brain Segmentation with Full Volume Neural Network

VoxHRNet This is the official implementation of the following paper: Whole Brain Segmentation with Full Volume Neural Network Yeshu Li, Jonathan Cui,

Microsoft 12 Nov 24, 2022
DIRL: Domain-Invariant Representation Learning

DIRL: Domain-Invariant Representation Learning Domain-Invariant Representation Learning (DIRL) is a novel algorithm that semantically aligns both the

Ajay Tanwani 30 Nov 07, 2022
SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning

SPCL SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning Update on 2021/11/25: ArXiv Ver

Binhui Xie (谢斌辉) 11 Oct 29, 2022
Programming with Neural Surrogates of Programs

Programming with Neural Surrogates of Programs

0 Dec 12, 2021