natowi

Introduction

The Openscan project https://openscan.eu is a really cool 3D printing and scanning project. It systematically takes a series of photos that can be stitched together into a 3D model using photogrammetry. Thomas Megel the creator of OpenScan has a really cool cloud-based service that can take the raw photos and turn them an STL model for you. You can read more about it here: https://github.com/OpenScanEu/OpenScan/blob/master/temp/README.md

Another way to take advantage of photogrammetry is using AliceVision's Meshroom. Prusa Research did a nice explainer/tutorial in this blog post: https://blog.prusaprinters.org/photogrammetry-2-3d-scanning-simpler-better-than-ever_29393/

The main "catch" with Meshroom is that it requires CUDA and hence an NVIDIA graphics card. It didn't have an NVIDIA card (and didn't want to figure out how to run in the cloud) but I did have a Jetson Nano 2GB https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-nano/education-projects/

The documentati

Setting up Travis deploy

Create an OAuth token from your profile settings

under Developer select Personal access token
generate a new one and copy it to the clipboard

On the travis page of the repository, go to settings --> More Options->Settings
Set a new Environment Variable called eg GITHUB_RELEASE_API_KEY or whatever u like, and copy the key
In the .travis.yaml file, under add something like that

before_deploy:
 - ARCHIVE_BASE_PATH=${INSTALL_DIR}

	#!/usr/bin/env python3

	# Import the Qarnot SDK
	import qarnot

	# Create a connection, from which all other objects will be derived
	# Enter client token here
	conn = qarnot.connection.Connection(client_token="<<<MY_SECRET_TOKEN>>>")

	# Create the task

	# py kapture-cropper.py -i dataset-kapture\ --border_px 0 --scale_factor 1 -v

	import kapture
	import kapture.io.csv as csv
	from PIL import Image
	from kapture.io.csv import kapture_to_dir
	import os, logging, argparse
	import kapture.utils.logging

	logger = logging.getLogger("kapture-cropper")

	import json, os, shutil
	from os.path import join, basename
	from tqdm import tqdm
	import numpy as np

	MESHROOM = r"E:\workspace\dataset\01_DTU\cache\20\meshroom\MeshroomCache\ConvertSfMFormat\4b9ced4a64f3f996f7650f3d5ed9e27c4774a7c9\sfm.json"
	COLMAP = r"E:\workspace\dataset\01_DTU\cache\20\colmap"


	def make_dir(folder):

	% required dimensions
	standoff = 500; % distance from camera, in [mm]
	fovWidth = 320; % width of field of view, in [mm]
	fovHeight = 10; % height of FOV, in [mm]

	% sensor resolution
	sensorXRes = 4096; % widht
	sensorYRes = 3072; % height

	% pixel physical size

	#!/usr/bin/env python3
	# -- coding: utf-8 --


	import os, sys
	from tempfile import gettempdir
	from subprocess import call


	def beep(waveform=(79, 45, 32, 50, 99, 113, 126, 127)):

	docopt==0.6.2
	trimesh==2.10.18