Camview - A CLI-tool used to stream CCTV online footage based on URL params

Related tags

Deep Learningcamview
Overview

CamView

A CLI-tool used to stream CCTV online footage based on URL params


Get Started

To get started with CamView, simply download the camview.py file and download the required libs, and then run.

  1. pip install ast requests selenium climage cv2 multiprocessing argparse
  2. python camview.py

CamView has some optional flags for different modes. To use as normal, you do not need to include any of these. However, for devices with certain constraints, there is an optional CLI mode where images are converted and then printed to the terminal. To use this feature, type:

python camview.py --cli

Screenshot(s)

Imgur


About CamView

CamView works on part magic, part Python, and part Google! It wouldn't be fair for me to take all the credit, when in fact CamView builds on top of each of these tools.

The process CamView uses is detailed a bit more here for those who are interested.

  1. First, we take the string (either specified by the user or the selected preset) and use it as a Google query like inurl:query. This is a well-known process for finding things on the internet, and used more widely outside of misconfigured/public webcam discovery to find exploitable servers or logins with default credentials. More on this process (called Google Hacking), can be found here
  2. Next, we take all the google search results, and send them to a verify function, where we request the page and check the response. If the page loads as expected, we send the url on, if not, we don't use that url later.
  3. Using the urls we've uncovered, we load each of them and inject a custom JS script into each page. This JS script (since there is no set way to find the stream, as it is an element) will iterate through every image on the site, and then return the one with the largest dimensions. (We go off the assumption that the largest image must be the stream, but ocassionally we are wrong.
  4. Once we have this image in our python script, we open a new thread and display the image using the OpenCV tools, either in the default video player, or we convert the frame with climage and print it as is.

Licence

Copyright 2022 Finn Lancaster

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Owner
Finn Lancaster
Student, hacker, game dev, pianist.
Finn Lancaster
Official pytorch code for SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal

SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal This is the official pytorch code for SSAT: A Symmetric Semantic-

ForeverPupil 57 Dec 13, 2022
Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-Pixel Part Segmentation [3DV 2021 Oral]

Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-Pixel Part Segmentation [3DV 2021 Oral] Learning to Disambiguate Strongly In

Zicong Fan 40 Dec 22, 2022
Codebase for BMVC 2021 paper "Text Based Person Search with Limited Data"

Text Based Person Search with Limited Data This is the codebase for our BMVC 2021 paper. Please bear with me refactoring this codebase after CVPR dead

Xiao Han 33 Nov 24, 2022
Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling

VAE with Volume-Preserving Flows This is a PyTorch implementation of two volume-preserving flows as described in the following papers: Tomczak, J. M.,

Jakub Tomczak 87 Dec 26, 2022
Trajectory Extraction of road users via Traffic Camera

Traffic Monitoring Citation The associated paper for this project will be published here as soon as possible. When using this software, please cite th

Julian Strosahl 14 Dec 17, 2022
Efficiently Disentangle Causal Representations

Efficiently Disentangle Causal Representations Install dependency pip install -r requirements.txt Main experiments Causality direction prediction cd

4 Apr 01, 2022
Codebase for the solution that won first place and was awarded the most human-like agent in the 2021 NeurIPS Competition MineRL BASALT Challenge.

KAIROS MineRL BASALT Codebase for the solution that won first place and was awarded the most human-like agent in the 2021 NeurIPS Competition MineRL B

Vinicius G. Goecks 37 Oct 30, 2022
The PyTorch implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision.

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision The PyTorch implementation of DiscoBox: Weakly Supe

Shiyi Lan 1 Oct 23, 2021
Pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks."

alpha-GAN Unofficial pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks." arXi

Victor Shepardson 78 Dec 08, 2022
Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021.

NL-CSNet-Pytorch Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021. Note: this repo only shows the strategy of

WenxueCui 7 Nov 07, 2022
Anonymous implementation of KSL

k-Step Latent (KSL) Implementation of k-Step Latent (KSL) in PyTorch. Representation Learning for Data-Efficient Reinforcement Learning [Paper] Code i

1 Nov 10, 2021
Multi-tool reverse engineering collaboration solution.

CollaRE v0.3 Intorduction CollareRE is a tool for collaborative reverse engineering that aims to allow teams that do need to use more then one tool du

105 Nov 27, 2022
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)

scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A

郭飞 3.7k Jan 03, 2023
Code for the paper "Relation of the Relations: A New Formalization of the Relation Extraction Problem"

This repo contains the code for the EMNLP 2020 paper "Relation of the Relations: A New Paradigm of the Relation Extraction Problem" (Jin et al., 2020)

YYY 27 Oct 26, 2022
Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative adversarial networks (GAN)

Flickr-Faces-HQ Dataset (FFHQ) Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative

NVIDIA Research Projects 2.9k Dec 28, 2022
RefineGNN - Iterative refinement graph neural network for antibody sequence-structure co-design (RefineGNN)

Iterative refinement graph neural network for antibody sequence-structure co-des

Wengong Jin 83 Dec 31, 2022
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models Code accompanying CVPR'20 paper of the same title. Paper lin

Alex Damian 7k Dec 30, 2022
Towards Boosting the Accuracy of Non-Latin Scene Text Recognition

Convolutional Recurrent Neural Network + CTCLoss | STAR-Net Code for paper "Towards Boosting the Accuracy of Non-Latin Scene Text Recognition" Depende

Sanjana Gunna 7 Aug 07, 2022
DeconvNet : Learning Deconvolution Network for Semantic Segmentation

DeconvNet: Learning Deconvolution Network for Semantic Segmentation Created by Hyeonwoo Noh, Seunghoon Hong and Bohyung Han at POSTECH Acknowledgement

Hyeonwoo Noh 325 Oct 20, 2022
To build a regression model to predict the concrete compressive strength based on the different features in the training data.

Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features

Ashish Kumar 4 Jun 11, 2022