Comments (7)
Spending entirely too much effort making fancy comparisons
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import numpy as np
import time
import matplotlib.pyplot as plt
from statistics import mean
def time_func(func,trials,data):
times = []
for i in range(0,trials):
start = time.perf_counter()
func(data)
end = time.perf_counter() - start
times.append(end*1000000)
print('Average Time: ' + str(mean(times)) + ' us')
return times
def numpy_func(data):
nparr = np.array(data)
nparr = nparr.reshape(24,32)
nparr = np.fliplr(nparr)
nparr = np.ndarray.flatten(nparr)
data = np.ndarray.tolist(nparr)
def vanilla_func(data):
mirror = []
matrix = [data[i:i + 32] for i in range(0, len(data), 32)]
for row in matrix:
row.reverse()
mirror.extend(row)
numpy_func_times = time_func(numpy_func,100000,data)
vanilla_func_times = time_func(vanilla_func,100000,data)
Average Time: 48.310819000375886 us
Average Time: 9.757216000250537 us
plt.plot(numpy_func_times,'-')
plt.plot(vanilla_func_times,'-')
plt.legend(['numpy','vanilla'],loc='best')
plt.xlabel('Trial Number')
plt.ylabel('Time (μs)')
plt.title('Comparison of implementations of reflection')
plt.show()
from sights.
The first task is to confirm what values are being output by each wrapper.
The MLX90460 wrapper which was just written today outputs in degrees celsius.
I do have an AMG8833 sensor, so I'll hook that up as well when I get some time.
from sights.
The AMG8833 is up and running. It reports the same units as the MLX90640, which is a good place to start. The only modifications we need to make to fix colours are to the graph.
Current colours: Red is cold, yellow is hot.
Observations: The MLX90640 is mirrored. Considering the data is a one-dimensional array of 32*24=768 elements, what would be the best way to reflect this?
from sights.
6fbd871 uses the range of the thermal camera to determine colours. The minimum temperature (-40°C for the MLX90640 and 0°C for the AMG8833) is 180° on the hue circle (sharp, ice-blue aqua) and the maximum temperature (300°C for the MLX90640 and 80°C for the AMG8833) is 0° on the hue circle (pure red).
However, this means that there is very little contrast for objects that are close in temperature. This image illustrates this effect well. The MLX90640, with its range of 340°C, shows the mug of hot water and the ice pack in nearly the same colours.
Mug of hot water on the left, ice pack on the right of each thermal image.
Instead, I'm thinking of using the maximum and minimum temperatures in the frame to define the range.
I'm also going to rotate around the hue wheel another 60 degrees, which will give us colours closer to the popular FLIR brand of handheld thermal cameras.
from sights.
Added a wrapper for the MLX90641 sensor as well, using the standard MLX90641x library.
All MLX90641x sensors could use the same wrapper in Sights 2.0.
from sights.
I think this is ready to close.
from sights.
This is looking excellent Jack! I'm happy to close this issue 😄
from sights.
Related Issues (20)
- Accent Colour Theming
- I2C multiplexer support
- Toggle graph HOT 1
- Implement "vanilla-picker" for colour picking in the visual config editor
- Add emergency stop button to interface HOT 1
- Add ability to see limit of circle graphs via a tooltip
- There are unsaved changes when interface is loaded while service is stopped
- Create a new config file location
- Reduce Bandwidth Usage HOT 2
- Replace Motion with an integrated camera streaming solution
- Replace Server-to-Client WebSocket Connection HOT 1
- Thermal Camera Graph Improvements HOT 5
- Replace config files with profiles, introduce a Sights config file HOT 3
- The Sights Interface Design Wizard 2.0 HOT 3
- Replace ShellInABox with integrated SSH console
- Advanced gamepad controls and mappings
- First-class Android support
- Revamp Sights installation process
- Support for Actions
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from sights.