This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape

Overview

Metashape-Utils

This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape, given a set of 2D coordinates (in a local coordinate reference system - CRS) of N markers collimated onto one (or M) plane(s).

The number of markers N and planes M is arbitrary.

The coordinates must be stored into a .yaml file like the example pars.yaml.

Starting from the provided set of markers, the script scalebars.py generates all the possible scale bars per plane, and subdivides them into two equally numerous subsets of control and check bars.

Because of this, in the same .yaml parameter file, the user must also provide the accuracy of the scale bars, and the chunk id of the 3D model/mesh/point cloud to scale.

After the 3D model/mesh/point is scaled, the RMSE of the control and check bars is saved into a Statistics_scalebars.txt file.

To run the script scalebars.py, the user must launch Metashape, press CTRL + R, and write the path of the script scalebars.py as Script and the path of the .yaml file as Argument.

The script test.py, instead, allows the user to assess the relationship between RMSE and number of scale bars; to investigate this relationship from a statistically relevant point of view, the test is repeated I times, where I is the number of iterations (which is a parameter to set in the .yaml file).

The values of RMSE are then saved to a .csv file, whose path must be defined in the .yaml file.

Finally, a plot of the relationship is produced.

To launch the script test.py, the same instructions as scalebars.py can be followed.

Owner
INSCRIBE
INSCRIBE - INvention of SCRIpts and their BEginnings
INSCRIBE
The object detection pipeline is based on Ultralytics YOLOv5

AYOLOv2 The main goal of this repository is to rewrite the object detection pipeline with a better code structure for better portability and adaptabil

153 Dec 22, 2022
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation This project attempted to implement the paper Putting NeRF on a

254 Dec 27, 2022
Code for "Retrieving Black-box Optimal Images from External Databases" (WSDM 2022)

Retrieving Black-box Optimal Images from External Databases (WSDM 2022) We propose how a user retreives an optimal image from external databases of we

joisino 5 Apr 13, 2022
Detecting drunk people through thermal images using Deep Learning (CNN)

Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab

Giacomo Ferretti 3 Oct 27, 2022
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement

SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement This repository implements the approach described in SporeAgent: Reinforced

Dominik Bauer 5 Jan 02, 2023
Code for the paper "JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design"

JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design This repository contains code for the paper: JA

Aspuru-Guzik group repo 55 Nov 29, 2022
Build upon neural radiance fields to create a scene-specific implicit 3D semantic representation, Semantic-NeRF

Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr

Shuaifeng Zhi 243 Jan 07, 2023
🕵 Artificial Intelligence for social control of public administration

Non-tech crash course into Operação Serenata de Amor Tech crash course into Operação Serenata de Amor Contributing with code and tech skills Supportin

Open Knowledge Brasil - Rede pelo Conhecimento Livre 4.4k Dec 31, 2022
Diagnostic tests for linguistic capacities in language models

LM diagnostics This repository contains the diagnostic datasets and experimental code for What BERT is not: Lessons from a new suite of psycholinguist

61 Jan 02, 2023
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

xmu-xiaoma66 7.7k Jan 05, 2023
Convolutional Neural Network for 3D meshes in PyTorch

MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f

Rana Hanocka 1.4k Jan 04, 2023
A deep learning object detector framework written in Python for supporting Land Search and Rescue Missions.

AIR: Aerial Inspection RetinaNet for supporting Land Search and Rescue Missions AIR is a deep learning based object detection solution to automate the

Accenture 13 Dec 22, 2022
This project aims to be a handler for input creation and running of multiple RICEWQ simulations.

What is autoRICEWQ? This project aims to be a handler for input creation and running of multiple RICEWQ simulations. What is RICEWQ? From the descript

Yass Fuentes 1 Feb 01, 2022
Iranian Cars Detection using Yolov5s, PyTorch

Iranian Cars Detection using Yolov5 Train 1- git clone https://github.com/ultralytics/yolov5 cd yolov5 pip install -r requirements.txt 2- Dataset ../

Nahid Ebrahimian 22 Dec 05, 2022
Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties

Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties 8.11.2021 Andrij Vasylenko I

Leverhulme Research Centre for Functional Materials Design 4 Dec 20, 2022
FFTNet vocoder implementation

Unofficial Implementation of FFTNet vocode paper. implement the model. implement tests. overfit on a single batch (sanity check). linearize weights fo

Eren Gölge 81 Dec 08, 2022
An easy-to-use app to visualise attentions of various VQA models.

Ask Me Anything: A tool for visualising Visual Question Answering (AMA) An easy-to-use app to visualise attentions of various VQA models. Please click

Apoorve 37 Nov 13, 2022
A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

Adversarial Video Generation This project implements a generative adversarial network to predict future frames of video, as detailed in "Deep Multi-Sc

Matt Cooper 704 Nov 26, 2022
Joint Discriminative and Generative Learning for Person Re-identification. CVPR'19 (Oral)

Joint Discriminative and Generative Learning for Person Re-identification [Project] [Paper] [YouTube] [Bilibili] [Poster] [Supp] Joint Discriminative

NVIDIA Research Projects 1.2k Dec 30, 2022
CenterNet:Objects as Points目标检测模型在Pytorch当中的实现

CenterNet:Objects as Points目标检测模型在Pytorch当中的实现

Bubbliiiing 267 Dec 29, 2022