def sense_and_act(self):
if self.bbcon.can_take_photo:
print("Taking photo!")
image_obj = self.c_sensob.update()
img = Imager(image=image_obj)
img.dump_image('/')
self.match_degree = 0.9
triple2 = [0] * 3
for x in range(img.xmax):
for y in range(img.ymax):
t = img.get_pixel(x, y)
for i in range(len(triple2)):
triple2[i] += t[i]
print("RGB", triple2)
print(triple2[0] > triple2[1] and triple2[0] > triple2[2])
if triple2[0] > triple2[1] and triple2[0] > triple2[2]:
self.motor_recommendations = ['t']
else:
self.motor_recommendations = ['f']
self.bbcon.photo_taken()
self.priority = 0.9
class FindRedSensob(Sensob):
def __init__(self):
self.bilde = None
self.value = [0,0,0,0,0] #Makes the list with red pixels
Sensob.__init__(self,[Camera()]) #Super-constructor with the camera-sensor.
def update(self):
if super(FindRedSensob,self).update(): #Run the super-update, to update the sensor values.
self.take_picture() #Takes the picture and stores it on the rpi.
self.bilde = Imager('red_image.jpeg') #Accesses the picture.
self.value = [0, 0, 0, 0, 0] #Resets the list.
self.delta = self.bilde.xmax // 5 #Divides the picture into 5 equal columns.
self.make_image_wta() #Performs a winner-take-all-function to make every pixel only red, green or blue.
self.make_red_image() #Makes all green and blue pixels black, and maximizes the red in the red pixels.
self.calculate_where_most_red() #Calculates wich fith has the most red, and returns the list as the self.value.
return self.value
def take_picture(self):
im = Imager(image=self.sensors[0].update()).scale(1,1) #Takes the picture.
im.dump_image('red_image.jpeg') #Stores the picture.
def reset(self):
Sensob.reset(self)
self.value = [0,0,0,0,0]
def get_value(self):
return self.value
def is_red_pixel(self,x,y):
pixel = self.bilde.get_pixel(x,y)
if pixel[0] > pixel[1] and pixel[0] > pixel[2] and pixel[0] > 50:
return True
def make_image_wta(self): #Performs a winner-take-all-function to make every pixel only red, green or blue.
self.bilde = self.bilde.map_color_wta()
def make_red_image(self): #Makes all green and blue pixels black, and maximizes the red in the red pixels.
for i in range(self.bilde.xmax):
for j in range(self.bilde.ymax):
if self.is_red_pixel(i,j):
self.bilde.set_pixel(i,j,(255,0,0))
else:
self.bilde.set_pixel(i,j,(0,0,0))
def calculate_where_most_red(self): #Calculates wich fith has the most red, and returns the list as the self.value
for i in range(self.bilde.xmax):
for j in range(self.bilde.ymax):
if self.is_red_pixel(i,j):
which_fifth = i//self.delta
#print("which fifth: ", which_fifth)
self.value[which_fifth - 1] += 1
def process_data(self, data):
print("Datatype: ", data)
red_count = 0
image = Imager(image=data[0])
pixel_list = []
for x in range(image.xmax):
for y in range(image.ymax):
pixel_list.append(image.get_pixel(x, y))
for pixel in pixel_list:
temp_count = 0
for i in range(3):
if self.lower[i] < pixel[i] < self.upper[i]:
temp_count += 1
if temp_count == 3:
red_count += 1
self.value = red_count / self.camob.get_size()
def detect_red(image, percentage):
"""Checks if more than a percentage of the pixels are red"""
imager = Imager(image=image)
count = 0
for x in range(imager.xmax):
for y in range(imager.ymax):
pixel = imager.get_pixel(x, y)
if pixel[0] - pixel[1] >= 150 and pixel[0] - pixel[2] >= 150:
count += 1
elif pixel[1] < 25 and pixel[2] < 25 and pixel[0] - pixel[
1] >= 80 and pixel[0] - pixel[2] >= 80:
count += 1
elif pixel[1] > 150 and pixel[2] > 150 and pixel[0] - pixel[
1] >= 80 and pixel[0] - pixel[2] >= 80:
count += 1
return count / (imager.xmax * imager.ymax) > percentage
def update(self):
"""Check if you see red
Takes a picture, runs wta(winner takes all) on it, then counts the number of red pixels
If there's enough red, motor"""
self.sensor.update()
taken_image = self.sensor.get_value()
wta_image = Imager(image=taken_image).map_color_wta(thresh=0.5) # colors each pixel the dominant color
red_count = 0
for i in range(20, 100):
for j in range(20, 80):
if wta_image.get_pixel(i, j)[0] > 100:
red_count += 1
print('Red count is:', red_count)
if red_count > self.color_treshold:
self.value = 1.0
else:
self.value = 0.0
