def find_line_and_confidence(self):
top_line = self.find_line()
rect = self.calculate_bottom_bounding_box(top_line)
if usb_is_connected:
self.snapshot.draw_rectangle(rect, color=(255, 255, 255))
self.logger.debug("rect=", rect)
if (rect[1] < self.snapshot.height() >> 1):
sensor.flush()
bottom_line = self.find_line(roi=rect)
if (bottom_line):
if usb_is_connected:
self.snapshot.draw_line(bottom_line.line(), color=(0, 0, 255))
if (top_line):
confidence = 1 - abs(bottom_line.x1() - top_line.x2()) / (
self.snapshot.width() << 1)
else:
confidence = 1 - bottom_line.x1() / (
self.snapshot.width() << 1)
self.logger.debug("confidence=", confidence)
else:
confidence = 0
self.logger.trace("returing line=", top_line, ", confidence=",
confidence)
return (top_line, confidence)
def find_line(self, **keyword_parameters):
global top_area_theshold, bottom_area_theshold
self.logger.trace("entering find_line...")
if (self.threshold == None):
raise RuntimeError("Set threshold before trying to find a line")
self.logger.debug("calling get_regression... threshold=",
self.threshold)
if ('roi' in keyword_parameters):
roi = keyword_parameters['roi']
#roi_stats = self.snapshot.get_statistics(roi = roi)
#self.logger.debug("roi_stats=", roi_stats)
area_theshold = bottom_area_theshold
else:
roi = self.line_roi
area_theshold = top_area_theshold
self.line = self.snapshot.get_regression(self.threshold, \
area_threshold = area_theshold, pixels_threshold = _PIXELS_THRESHOLD, \
robust = True, roi = roi)
if ('roi' in keyword_parameters):
pass
elif usb_is_connected and self.line:
self.logger.trace("line found")
self.snapshot.draw_line(self.line.line(), color=self.line_color)
sensor.flush()
self.logger.trace("returing line=", self.line)
return self.line
def take(self):
self.logger.trace("entering take...")
try:
self.watchdog.feed()
except AttributeError:
pass # no watchdog to feed
# after taking a picture: img.binary(COLOR_THRESHOLDS if COLOR_LINE_FOLLOWING else GRAYSCALE_THRESHOLDS)
self.logger.trace("taking snapshot...")
self.snapshot = sensor.snapshot()
#if (pyb.elapsed_millis(self.glare_check_millis) > MILLIS_BETWEEN_GLARE_CHECK):
#self._check_glare()
#self.glare_check_millis = pyb.millis()
if usb_is_connected:
self.snapshot.draw_rectangle(self.line_roi, color=(150, 150, 150))
if self.SHOW_BINARY_VIEW:
if (self.threshold == None):
raise RuntimeError(
"Set threshold before trying to use binary view")
self.logger.trace("calling binary...")
self.snapshot.binary(self.threshold)
elif self.use_hist:
self.logger.trace("calling histeq...")
self.snapshot.histeq()
#elif self.CHROMINVAR:
#trace("calling chrominvar...")
#self.snapshot.chrominvar()
sensor.flush()
self.logger.trace("returing snapshot...")
return self.snapshot
def wait_for_april_tag():
global state
state = READY_FOR_INPUT
while (state == READY_FOR_INPUT):
set_pw_colors(time.ticks())
# if not taking snapshots, delay
#pyb.udelay(led_timer.period())
clock.tick() # for fps()
img = sensor.snapshot()
for tag in img.find_apriltags():
state = GOT_INPUT
sensor.flush()
#print(clock.fps())
return tag.id();
def unittest(data_path, temp_path):
import sensor
sensor.reset()
sensor.set_framesize(sensor.QVGA)
sensor.set_pixformat(sensor.GRAYSCALE)
img = sensor.snapshot().clear()
img.set_pixel(img.width()//2+50, 120, 255)
img.set_pixel(img.width()//2-50, 120, 255)
img.draw_line([img.width()//2-50, 50, img.width()//2+50, 50])
img.draw_rectangle([img.width()//2-25, img.height()//2-25, 50, 50])
img.draw_circle(img.width()//2, img.height()//2, 40)
img.draw_string(11, 10, "HelloWorld!")
img.draw_cross(img.width()//2, img.height()//2)
sensor.flush()
img.difference(data_path+"/drawing.pgm")
stats = img.get_statistics()
return (stats.max() == 0) and (stats.min() == 0)
def unittest(data_path, temp_path):
import sensor
sensor.reset()
sensor.set_framesize(sensor.QVGA)
sensor.set_pixformat(sensor.GRAYSCALE)
img = sensor.snapshot().clear()
img.set_pixel(img.width() // 2 + 50, 120, 255)
img.set_pixel(img.width() // 2 - 50, 120, 255)
img.draw_line([img.width() // 2 - 50, 50, img.width() // 2 + 50, 50])
img.draw_rectangle([img.width() // 2 - 25, img.height() // 2 - 25, 50, 50])
img.draw_circle(img.width() // 2, img.height() // 2, 40)
img.draw_string(11, 10, "HelloWorld!")
img.draw_cross(img.width() // 2, img.height() // 2)
sensor.flush()
img.difference(data_path + "/drawing.pgm")
stats = img.get_statistics()
return (stats.max() == 0) and (stats.min() == 0)
# Higher threshold results in a higher detection rate, with more false positives.
objects = img.find_features(face_cascade, threshold=0.5, scale_factor=1.4)
# Draw faces
for face in objects:
print(face)
#img.draw_rectangle(face)
(x, y, r) = circle_from_rect(face)
img.draw_circle(x, y, r)
# Now find eyes within each face.
# Note: Use a higher threshold here (more detections) and lower scale (to find small objects)
eyes = img.find_features(eyes_cascade,
threshold=0.5,
scale_factor=1.2,
roi=face)
for e in eyes:
print("found eyes")
print(e)
#(x, y, r) = circle_from_rect(e)
#img.draw_circle(x, y, r)
img.draw_rectangle(e)
red_led.on()
notFound = False
sensor.flush()
time.sleep(5000)
# Print FPS.
# Note: Actual FPS is higher, streaming the FB makes it slower.
#print(clock.fps())