99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
import pimoroni_i2c
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import breakout_vl53l5cx
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import time
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from ulab import numpy
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# This example attempts to track a "bright" object (such as a white business card)
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# It uses reflectance to identify the target and compute the X/Y coordinates
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# of its "center of mass" in the sensors view.
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# Motion indication only works at distances > 400mm so it's not
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# really useful as a method to reject data.
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# Configure your distance and brightness thresholds to suit your object
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DISTANCE_THRESHOLD = 400 # Distance in mm
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REFLECTANCE_THRESHOLD = 60 # Estimated reflectance in %
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PINS_BREAKOUT_GARDEN = {"sda": 4, "scl": 5}
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PINS_PICO_EXPLORER = {"sda": 20, "scl": 21}
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# Sensor startup time is proportional to i2c baudrate
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# HOWEVER many sensors may not run at > 400KHz (400000)
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i2c = pimoroni_i2c.PimoroniI2C(**PINS_BREAKOUT_GARDEN, baudrate=2_000_000)
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print("Starting up sensor...")
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t_sta = time.ticks_ms()
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sensor = breakout_vl53l5cx.VL53L5CX(i2c, firmware=open("vl53l5cx_firmware.bin").read())
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t_end = time.ticks_ms()
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print("Done in {}ms...".format(t_end - t_sta))
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# Make sure to set resolution and other settings *before* you start ranging
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sensor.set_resolution(breakout_vl53l5cx.RESOLUTION_8X8)
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sensor.set_ranging_frequency_hz(15)
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sensor.start_ranging()
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while True:
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time.sleep(1.0 / 60)
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if sensor.data_ready():
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# "data" is a namedtuple (attrtuple technically)
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# it includes average readings as "distance_avg" and "reflectance_avg"
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# plus a full 4x4 or 8x8 set of readings (as a 1d tuple) for both values.
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data = sensor.get_data()
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reflectance = numpy.array(data.reflectance).reshape((8, 8))
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distance = numpy.array(data.distance).reshape((8, 8))
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scalar = 0
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target_distance = 0
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n_distances = 0
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# Filter out unwanted reflectance values
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for ox in range(8):
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for oy in range(8):
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d = distance[ox][oy]
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r = reflectance[ox][oy]
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if d > DISTANCE_THRESHOLD or r < REFLECTANCE_THRESHOLD:
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reflectance[ox][oy] = 0
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else:
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scalar += r
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# Get a total from all the distances within our accepted target
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for ox in range(8):
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for oy in range(8):
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d = distance[ox][oy]
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r = reflectance[ox][oy]
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if r > 0:
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target_distance += d
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n_distances += 1
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# Average the target distance
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if n_distances > 0:
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target_distance /= n_distances
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else:
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target_distance = 0
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# Flip reflectance now we've applied distance
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# both fields are upside-down!
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reflectance = numpy.flip(reflectance, axis=0)
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# Calculate the center of mass along X and Y
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x = 0
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y = 0
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if scalar > 0:
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for ox in range(8):
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for oy in range(8):
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y += reflectance[ox][oy] * ox
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y /= scalar
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y /= 3.5
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y -= 1.0
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for oy in range(8):
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for ox in range(8):
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x += reflectance[ox][oy] * oy
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x /= scalar
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x /= 3.5
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x -= 1.0
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print(round(x, 2), round(y, 2), round(target_distance, 2))
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