As many of you know, or perhaps not (due to geographic reasons) parts of the world witnessed a solar eclipse – a rare phenomenon in which the sun is completely obscured by the moon. Important to notice that in this region of the world (Scotland) we witnessed approximately 95%-98% coverage.

As seen from the Earth, a solar eclipse is a type of eclipse that occurs when the Moon passes between the Sun and Earth, and the Moon fully or partially blocks (“occults”) the Sun. This can happen only at new moon, when the Sun and the Moon are in conjunction as seen from Earth in an alignment referred to as syzygy. In a total eclipse, the disk of the Sun is fully obscured by the Moon. In partial and annular eclipses, only part of the Sun is obscured.

 

So, I read a couple of blogs on how to take photos to this great astronomical  probability, and spoke with some friends (Murray and Gleb) that have great photography knowledge.

Then I bought 4 filters, 3 ND (neutral density) and a UV one. For those wondering about ND: a neutral density filter orND filter is a filter that reduces or modifies the intensity of all wavelengths or colors of light equally, giving no changes in hue of color rendition. It can be a colorless (clear) or grey filter.

Equipment:

• Canon EOS Rebel (stock lens)
• 2, 4, 8 ND filters
• UV filter
• GoPro Hero 3 (for the timelapse)

So, at 8:30am I started walking towards Salisbury Crags in Holyrood Park, Edinburgh, to try to get some nice shots… And the result is next, please enjoy. (Don’t forget to watch the video at the end…)

[exif id=”597″]

Be sure to watch the video:

This is about some experiments I’m doing using python and openCV and of course one of my drones… In this case the drone used for taking the videos, was my hexacopter (Alduxhexa).

The point is to explore different techniques and algorithms to track colours, objects and the follow them using a multicopter.

In the next video you will see my hexacopter flying with a GoPro pointing always down (to the ground). I want to be able to identify colours on the ground.

The code is available here.

openCV is a library of programming functions mainly aimed at real-time computer vision.

I’m using a HSV (hue-saturation-lightness) range of “whites” and then I use the function “inRange” to then get an region of possible color, if this region is large enough, then I marked and I can say the color has being found. The explanation could be more complex from what I just described, but its better to keep things simple.

In the code on my github, you can see other different examples, like face tracking, motion detection and even object detection, be sure to check them out!

Thanks to Murray for the above awesome photo of my hexacopter.

Tania ask me this Sunday morning if I was able to make a “better” sound out of a .wav file for a project in a course… So, I started googling and found different softwares to do this kind of stuff, but you need to pay for them and they are more like the “professional” kind of software. Not really what we wanted here.

So, I carry on googling but adding the magic word “python” 😉 until I found a great music synthesizer made in python by a guy called Martin C. Doege, the sauce is here.

Its important to notice that this was file comes for a 3D model… so, .stl file to .wav (via importing raw data in Audacity).

This is the original sound file (beware: it sounds horrible!!)

 

When I tested the examples, I was able to hear the classic synthesizer sound, which I really love. I remembered my padrisinimo Juan who introduced me into the music of Wendy Carlos, which is awesome both in sound and in complexity. For example, the album Switch-on-Bach was Carlos’ break-through album, one of the first to draw attention to the synthesizer as a genuine musical instrument, and it took 4 years to complete!!!! Listen to this mix.

Soooo… the basic idea was to read the wav file, get the data, which is an array of numbers with lots of precision. That particular wav file (the one Tania gave me), it ranges from -1 to 1, and it was 1519616 on length. So, the idea was to map those values, and the changed them to notes, and then create a synthesizer sound file from it.

Of course there is more music science behind it, but me, being not a music scientist I fixed the octaves, and with that the time changed… the final version sounds like this:

 

And thats how a 3D part sounds!!!!

Making sounds with objects.

The code is here:

[python title=”Code to ransform a wav file to synthesizer sound”]
#!/usr/bin/env python

"""wav-to-synth.py: Transform a wav file to synthesizer sound"""
"""
– Using the PySynth library from Martin C. Doege
– http://mdoege.github.io/PySynth/
– The sound is similar to a: DX7 e-piano
* Using Audiolab to read the wav file (maybe there us an easier way of doing this…)
* https://pypi.python.org/pypi/scikits.audiolab/
"""
__author__ = "Aldo Vargas"
__copyright__ = "Copyright 2015 Aldux.net"

__license__ = "GPL"
__version__ = "1"
__maintainer__ = "Aldo Vargas"
__email__ = "alduxvm@gmail.com"
__status__ = "Development"

import pysynth
import numpy as np
from scikits.audiolab import wavread

# 88 notes or piano key frequencies (for equal temperament)
notes = [‘a0’, ‘a#0’, ‘b0’, ‘c1’, ‘c#1’, ‘d1’, ‘d#1’, ‘e1’, ‘f1’, ‘f#1’, ‘g1’, ‘g#1’, ‘a1’, ‘a#1’, ‘b1’, ‘c2’, ‘c#2’, ‘d2’, ‘d#2’, ‘e2’, ‘f2’, ‘f#2’, ‘g2’, ‘g#2’, ‘a2’, ‘a#2’, ‘b2’, ‘c3’, ‘c#3’, ‘d3’, ‘d#3’, ‘e3’, ‘f3’, ‘f#3’, ‘g3’, ‘g#3’, ‘a3’, ‘a#3’, ‘b3’, ‘c4’, ‘c#4’, ‘d4’, ‘d#4’, ‘e4’, ‘f4’, ‘f#4’, ‘g4’, ‘g#4’, ‘a4’, ‘a#4’, ‘b4’, ‘c5’, ‘c#5’, ‘d5’, ‘d#5’, ‘e5’, ‘f5’, ‘f#5’, ‘g5’, ‘g#5’, ‘a5’, ‘a#5’, ‘b5’, ‘c6’, ‘c#6’, ‘d6’, ‘d#6’, ‘e6’, ‘f6’, ‘f#6’, ‘g6’, ‘g#6’, ‘a6’, ‘a#6’, ‘b6’, ‘c7’, ‘c#7’, ‘d7’, ‘d#7’, ‘e7’, ‘f7’, ‘f#7’, ‘g7’, ‘g#7’, ‘a7’, ‘a#7’, ‘b7’, ‘c8’]

# Re-maps a number from one range to another.
def map(x, in_min, in_max, out_min, out_max):
return (x – in_min) * (out_max – out_min) // (in_max – in_min) + out_min

# Round and convert to integer a array.
def roundandint(a, decimals=1):
b=np.around(a-10**(-(decimals+5)), decimals=decimals)
return b.astype(int)

# Change the numbers to piano key notes of 2 channels
def toNotes(data):
c1 = ();
c2 = ();
for k in range(100):
c1=((notes[data[k][0]],2),)+c1
c2=((notes[data[k][1]],4),)+c2
return (c1,c2)

if __name__=="__main__":
# Read the wav file
filename = "test2.wav"
data, sample_frequency,encoding = wavread(filename)

# Transform it to notes
c1,c2 = toNotes(roundandint(map(data,-1,1,1,88),0))

# Save channel 1 and 2 and the mix them
pysynth.make_wav(c1, fn = "c1.wav")
pysynth.make_wav(c2, fn = "c2.wav")
pysynth.mix_files("c1.wav", "c2.wav", "final.wav")
[/python]

AlduxHexa, my hexacopter build was created (at the beginning) with the sole purpose of carrying this 2.8 kilogram infrared camera.

My business partner Ifeanyi manage to get this B series in order for us to do some tests and some shots inside the West Quadrangle at the University of Glasgow.

In order to be able to fly carrying this massive payload, this hexacopter build was built with 740kv – 500watts BLDC and 13in carbon fibre propellers, carbon frame and lots of extra fancy stuff. The real deal.

The camera specifications are as follows:

• Sensitivity 40 mK @ + 30 °C
• IFOV 0.65 mrad
• FOV 24° × 18° / 0.3 m
• Temperature range –40°C to +120°C
• Accuracy ±2°C or ±2% of reading

FLIR B620 is a high performance infrared inspection system specially developed for building applications including automatic humidity and insulation defects alarm. With its state of the art technology including a 640×480 detector it produces sharp detailed images. Its unique ergonomic design makes it convenient to work with during inspections. The camera is equipped with the standard 24° lens.

The results:

Research and partnership is still and ongoing process. Ask us for any doubt you got.