kopia lustrzana https://github.com/pimoroni/pimoroni-pico
103 wiersze
3.4 KiB
Python
103 wiersze
3.4 KiB
Python
import pimoroni_i2c
|
|
import breakout_vl53l5cx
|
|
import time
|
|
from ulab import numpy
|
|
|
|
# The VL53L5CX requires a firmware blob to start up.
|
|
# Make sure you upload "vl53l5cx_firmware.bin" via Thonny to the root of your filesystem
|
|
# You can find it here: https://github.com/ST-mirror/VL53L5CX_ULD_driver/blob/no-fw/lite/en/vl53l5cx_firmware.bin
|
|
|
|
# This example attempts to track a "bright" object (such as a white business card)
|
|
# It uses reflectance to identify the target and compute the X/Y coordinates
|
|
# of its "center of mass" in the sensors view.
|
|
|
|
# Motion indication only works at distances > 400mm so it's not
|
|
# really useful as a method to reject data.
|
|
|
|
# Configure your distance and brightness thresholds to suit your object
|
|
DISTANCE_THRESHOLD = 400 # Distance in mm
|
|
REFLECTANCE_THRESHOLD = 60 # Estimated reflectance in %
|
|
|
|
|
|
PINS_BREAKOUT_GARDEN = {"sda": 4, "scl": 5}
|
|
PINS_PICO_EXPLORER = {"sda": 20, "scl": 21}
|
|
|
|
# Sensor startup time is proportional to i2c baudrate
|
|
# HOWEVER many sensors may not run at > 400KHz (400000)
|
|
i2c = pimoroni_i2c.PimoroniI2C(**PINS_BREAKOUT_GARDEN, baudrate=2_000_000)
|
|
|
|
print("Starting up sensor...")
|
|
t_sta = time.ticks_ms()
|
|
sensor = breakout_vl53l5cx.VL53L5CX(i2c)
|
|
t_end = time.ticks_ms()
|
|
print("Done in {}ms...".format(t_end - t_sta))
|
|
|
|
# Make sure to set resolution and other settings *before* you start ranging
|
|
sensor.set_resolution(breakout_vl53l5cx.RESOLUTION_8X8)
|
|
sensor.set_ranging_frequency_hz(15)
|
|
sensor.start_ranging()
|
|
|
|
|
|
while True:
|
|
time.sleep(1.0 / 60)
|
|
if sensor.data_ready():
|
|
# "data" is a namedtuple (attrtuple technically)
|
|
# it includes average readings as "distance_avg" and "reflectance_avg"
|
|
# plus a full 4x4 or 8x8 set of readings (as a 1d tuple) for both values.
|
|
data = sensor.get_data()
|
|
|
|
reflectance = numpy.array(data.reflectance).reshape((8, 8))
|
|
distance = numpy.array(data.distance).reshape((8, 8))
|
|
|
|
scalar = 0
|
|
target_distance = 0
|
|
n_distances = 0
|
|
# Filter out unwanted reflectance values
|
|
for ox in range(8):
|
|
for oy in range(8):
|
|
d = distance[ox][oy]
|
|
r = reflectance[ox][oy]
|
|
if d > DISTANCE_THRESHOLD or r < REFLECTANCE_THRESHOLD:
|
|
reflectance[ox][oy] = 0
|
|
else:
|
|
scalar += r
|
|
|
|
# Get a total from all the distances within our accepted target
|
|
for ox in range(8):
|
|
for oy in range(8):
|
|
d = distance[ox][oy]
|
|
r = reflectance[ox][oy]
|
|
if r > 0:
|
|
target_distance += d
|
|
n_distances += 1
|
|
|
|
# Average the target distance
|
|
if n_distances > 0:
|
|
target_distance /= n_distances
|
|
else:
|
|
target_distance = 0
|
|
|
|
# Flip reflectance now we've applied distance
|
|
# both fields are upside-down!
|
|
reflectance = numpy.flip(reflectance, axis=0)
|
|
|
|
# Calculate the center of mass along X and Y
|
|
x = 0
|
|
y = 0
|
|
if scalar > 0:
|
|
for ox in range(8):
|
|
for oy in range(8):
|
|
y += reflectance[ox][oy] * ox
|
|
y /= scalar
|
|
y /= 3.5
|
|
y -= 1.0
|
|
|
|
for oy in range(8):
|
|
for ox in range(8):
|
|
x += reflectance[ox][oy] * oy
|
|
x /= scalar
|
|
x /= 3.5
|
|
x -= 1.0
|
|
|
|
print(round(x, 2), round(y, 2), round(target_distance, 2))
|