Miquel Massot miquelmassot

## remote_awareness.proto
syntax="proto2";
import "dccl/option_extensions.proto";

message SingleImageSummary {
  option (dccl.msg) = { codec_version: 4
                        id: 124
                        max_bytes: 100 };
  required int32 image_id = 1 [(dccl.field) = { min: 0 max: 65535 }];
  required double latitude = 2 [(dccl.field) = { units { system: "angle::degree" derived_dimensions: "plane_angle" }
                                                min: -90

## image_exif_folder_to_csv.py
import exifread
from pathlib import Path
import argparse

def _get_if_exist(data, key):
    if key in data:
        return data[key]
    return None

def get_exif(filename):

## rosbag2csv.py
import rosbag, csv
import string
import argparse
from pathlib import Path

"""
Extract messages from bagfiles into CSV files

Usage:
    python rosbag2csv.py  bagfiles [bagfiles ...] [--topics TOPICS [TOPICS ...]]

## compare_directories.py
import filecmp

directory_cmp = filecmp.dircmp(
    a="/media/oplab-source/configuration",
    b="/media/remote/biocammap/Data/configuration",
    hide=[".@__thumb"])


def print_subdir(directory_cmp, level=0, full_tree=False):
    left_only = directory_cmp.left_only

## numpy_indexing_fail_example.py
import torch
import numpy as np

powers_of_two = list(2**p for p in range(1, 9))
print(powers_of_two)

print('-------- Using torch')
for M in powers_of_two:
  for N in powers_of_two:
    a = torch.rand(M, N)

## compile_MeshLab-2020.05.sh
# install dependencies
sudo apt-get install qt5-default qtcreator libqt5xmlpatterns5-dev qtscript5-dev  libeigen3-dev

git clone --recursive --branch MeshLab-2020.05 https://github.com/cnr-isti-vclab/meshlab.git

cd meshlab

# set build flags
QMAKE_FLAGS=('-spec' 'linux-g++' 'CONFIG+=release' 'CONFIG+=qml_release' 'CONFIG+=c++11' 'QMAKE_CXXFLAGS+=-fPIC' 'QMAKE_CXXFLAGS+=-fopenmp' 'QMAKE_CXXFLAGS+=-std=c++11' 'QMAKE_CXXFLAGS+=-fpermissive' 'INCLUDEPATH+=/usr/include/eigen3' "LIBS+=-L`pwd`/lib/linux-g++")
MAKE_FLAGS=('-j12')

## laser_calibration.yaml
mean_xyz_m: [1.5000313520431519, -0.08760256320238113, 8.258567810058594]
mean_plane: [1.0, -5.104500695516541e-06, -2.2570870615480905e-05, -1.499910442280434]
plane_angle_std_deg: 0.027107068317437855
plane_angle_mean_deg: 0.012027655943119862
plane_angle_median_deg: 0.004789200110805726
pitch_angle_std_deg: 0.024811587400379545
pitch_angle_mean_deg: -0.0019246573604165722
yaw_angle_std_deg: 0.016095586665442262
yaw_angle_mean_deg: 0.0010355123576031083
num_iterations: 100

## .screenrc
# Save this in ~/.screenrc

# Use bash
shell /bin/bash

autodetach on

# Big scrollback
defscrollback 5000

## move_repo.sh
#!/bin/bash

if [ $# -ne 2 ];
  then echo "USAGE: move_repo.sh OLD_REMOTE_URL NEW_REMOTE_URL"
  exit
fi

CURR_DIR=`pwd`
OLD_REMOTE="$1"
NEW_REMOTE="$2"

## float_to_binary_string.cpp
#include <iostream>
#include <string>
#include <cstring>
#include <vector>
#include <iomanip> // setw

std::string f2s(float p) {
  unsigned char* pc = reinterpret_cast<unsigned char*>(&p);
  return std::string(pc, pc + sizeof(float));
}
	syntax="proto2";
	import "dccl/option_extensions.proto";

	message SingleImageSummary {
	option (dccl.msg) = { codec_version: 4
	id: 124
	max_bytes: 100 };
	required int32 image_id = 1 [(dccl.field) = { min: 0 max: 65535 }];
	required double latitude = 2 [(dccl.field) = { units { system: "angle::degree" derived_dimensions: "plane_angle" }
	min: -90
	import exifread
	from pathlib import Path
	import argparse

	def _get_if_exist(data, key):
	if key in data:
	return data[key]
	return None

	def get_exif(filename):
	import rosbag, csv
	import string
	import argparse
	from pathlib import Path

	"""
	Extract messages from bagfiles into CSV files

	Usage:
	python rosbag2csv.py bagfiles [bagfiles ...] [--topics TOPICS [TOPICS ...]]
	import filecmp

	directory_cmp = filecmp.dircmp(
	a="/media/oplab-source/configuration",
	b="/media/remote/biocammap/Data/configuration",
	hide=[".@__thumb"])


	def print_subdir(directory_cmp, level=0, full_tree=False):
	left_only = directory_cmp.left_only
	import torch
	import numpy as np

	powers_of_two = list(2**p for p in range(1, 9))
	print(powers_of_two)

	print('-------- Using torch')
	for M in powers_of_two:
	for N in powers_of_two:
	a = torch.rand(M, N)
	# install dependencies
	sudo apt-get install qt5-default qtcreator libqt5xmlpatterns5-dev qtscript5-dev libeigen3-dev

	git clone --recursive --branch MeshLab-2020.05 https://github.com/cnr-isti-vclab/meshlab.git

	cd meshlab

	# set build flags
	QMAKE_FLAGS=('-spec' 'linux-g++' 'CONFIG+=release' 'CONFIG+=qml_release' 'CONFIG+=c++11' 'QMAKE_CXXFLAGS+=-fPIC' 'QMAKE_CXXFLAGS+=-fopenmp' 'QMAKE_CXXFLAGS+=-std=c++11' 'QMAKE_CXXFLAGS+=-fpermissive' 'INCLUDEPATH+=/usr/include/eigen3' "LIBS+=-L`pwd`/lib/linux-g++")
	MAKE_FLAGS=('-j12')
	mean_xyz_m: [1.5000313520431519, -0.08760256320238113, 8.258567810058594]
	mean_plane: [1.0, -5.104500695516541e-06, -2.2570870615480905e-05, -1.499910442280434]
	plane_angle_std_deg: 0.027107068317437855
	plane_angle_mean_deg: 0.012027655943119862
	plane_angle_median_deg: 0.004789200110805726
	pitch_angle_std_deg: 0.024811587400379545
	pitch_angle_mean_deg: -0.0019246573604165722
	yaw_angle_std_deg: 0.016095586665442262
	yaw_angle_mean_deg: 0.0010355123576031083
	num_iterations: 100
	# Save this in ~/.screenrc

	# Use bash
	shell /bin/bash

	autodetach on

	# Big scrollback
	defscrollback 5000
	#!/bin/bash

	if [ $# -ne 2 ];
	then echo "USAGE: move_repo.sh OLD_REMOTE_URL NEW_REMOTE_URL"
	exit
	fi

	CURR_DIR=`pwd`
	OLD_REMOTE="$1"
	NEW_REMOTE="$2"
	#include <iostream>
	#include <string>
	#include <cstring>
	#include <vector>
	#include <iomanip> // setw

	std::string f2s(float p) {
	unsigned char* pc = reinterpret_cast<unsigned char*>(&p);
	return std::string(pc, pc + sizeof(float));
	}