def __init__(self, camera_offset):
self.detect_shape = DetectShape()
self.last_x = 0
self.last_y = 0
# Change if camera is not in line with shooter
self.camera_offset = camera_offset
# Feedback of PID
self.x_offset = 0
self.wanted_x = 0
# Used for distance
self.y_offset = 0
self.target_locked = False
def __init__(self):
self.detect_shape = DetectShape()
self.last_x = 0
self.last_y = 0
# Change if camera is not in line with shooter
self.camera_offset = 0
# Feedback of PID
self.x_offset = 0
self.wanted_x = 0
# Used for distance
self.y_offset = 0
self.distance = 0
# Change to change dynamicly
self.x_threshold = 100
self.y_threshold = 100
self.target_locked = False
class ContourDetect:
def __init__(self, camera_offset):
self.detect_shape = DetectShape()
self.last_x = 0
self.last_y = 0
# Change if camera is not in line with shooter
self.camera_offset = camera_offset
# Feedback of PID
self.x_offset = 0
self.wanted_x = 0
# Used for distance
self.y_offset = 0
self.target_locked = False
def contour_detect(self, mask, is_tracking):
""" Filters the contours to a single contour and gets data from it """
height, width = mask.shape
# Setpoint of PID
self.wanted_x = width / 2 + self.camera_offset
if (is_tracking):
# Detects edges to make easier for contours
edges = cv2.Canny(mask, 100, 150, apertureSize=3)
# List of all raw contours includes noise
_, contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
# Where we eliminate some of the contours by shape
contour_shape = []
# Filters if there is a contour detected
if (len(contours) >= 1):
# Filters by shape
for contour in contours:
perimeter = cv2.arcLength(contour, True)
# Filters based on shape
if (self.detect_shape.detect(contour, perimeter)):
contour_shape.append(contour)
# Filter by biggest contour
if (len(contour_shape) >= 1):
selected_contour = contour_shape[0]
for contour in contour_shape:
# Gets the dimensions
(x, y, w, h) = cv2.boundingRect(contour)
(big_x, big_y, big_w,
big_h) = cv2.boundingRect(selected_contour)
# Gets area of each contour
area = self.get_area(w, h)
biggest_area = self.get_area(big_w, big_h)
# Checks which one is bigger and makes it the selected contour
if (area > biggest_area):
selected_contour = contour
else:
selected_contour = None
# Use filtered contour to get data
if (selected_contour != None):
self.target_locked = True
# Gets the position and dimensions of the contour
(x, y, w, h) = cv2.boundingRect(selected_contour)
# Draws rectangle around contour
cv2.rectangle(mask, (x, y - h), (x + w, y + h),
(255, 0, 0), 2)
# Draws circle around center of contour
cv2.circle(mask, (self.get_center(
x, y + h, w, h).x, self.get_center(x, y - h, w, h).y),
10, (255, 0, 0))
# Updates feedback for pids
self.x_offset = self.get_x_offset(
self.get_center(x, y - h, w, h).x)
self.y_offset = self.get_y_offset(
self.get_center(x, y - h, w, h).y, height)
self.last_x = x
self.last_y = y
else:
self.target_locked = False
else:
self.target_locked = False
else:
self.target_locked = False
def get_center(self, x, y, w, h):
""" This returns a Point which is the center of the contour """
return Point(x + (w / 2), y + h)
def get_x_offset(self, x):
""" Returns the x_offset used as feedback to the pid """
return x - (self.wanted_x)
def get_y_offset(self, y, height):
""" Returns the y_offset from the bottom of the frame used in a regression """
return y - (height / 2)
def get_rotation_pid(self):
""" Returns the x_offset used as feedback in a pid """
return self.x_offset
def get_area(self, w, h):
""" Returns the area """
return (w * h) * 2
def is_target_locked(self):
""" Checks if the filter it tracking a target """
return self.target_locked
class ContourDetect:
def __init__(self):
self.detect_shape = DetectShape()
self.last_x = 0
self.last_y = 0
# Change if camera is not in line with shooter
self.camera_offset = 0
# Feedback of PID
self.x_offset = 0
self.wanted_x = 0
# Used for distance
self.y_offset = 0
self.distance = 0
# Change to change dynamicly
self.x_threshold = 100
self.y_threshold = 100
self.target_locked = False
def contour_detect(self, mask, is_tracking):
height, width = mask.shape
# Setpoint of PID
self.wanted_x = width/2 + self.camera_offset
if (is_tracking):
# Detects edges to make easier for contours
edges = cv2.Canny(mask, 100, 150, apertureSize=3)
# List of all raw contours includes noise
_, contours, _= cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Where we eliminate some of the shape noise
contour_shape = []
# Filters
if (len(contours) >= 1):
# Filters by shape
for contour in contours:
perimeter = cv2.arcLength(contour,True)
if (self.detect_shape.detect(contour, perimeter)):
contour_shape.append(contour)
contour_biggest = [contour_shape[0]]
# Filter by biggest contour
if (len(contour_shape) >= 1):
for contour in contour_shape:
(x, y, w, h) = cv2.boundingRect(contour)
(big_x, big_y, big_w, big_h) = cv2.boundingRect(contour_biggest[0])
area = self.get_area(w,h)
biggest_area = self.get_area(big_w, big_h)
if (area > biggest_area):
contour_biggest = []
contour_biggest.append(contour)
if (len(contour_biggest) >= 1):
self.target_locked = True
(x,y,w,h) = cv2.boundingRect(contour_biggest[0])
cv2.rectangle(mask, (x ,y - h), (x + w, y + h), (255, 0, 0), 2)
cv2.circle(mask, (self.get_center(x, y+h,w, h).x, self.get_center(x, y-h, w, h).y), 10, (255, 0, 0))
self.x_offset = self.get_x_offset(self.get_center(x, y-h, w, h).x, width)
self.y_offset = self.get_y_offset(self.get_center(x, y-h, w, h).y, height)
self.distance = self.get_distance(self.y_offset)
#print(self.distance)
self.last_x = x
self.last_y = y
else:
self.target_locked = False
else:
self.target_locked = False
else:
self.target_locked = False
# Need to comment out for not testing
#cv2.imshow('Contour image',mask)
def get_center(self, x, y, w, h):
return Point(x + (w/2), y + h)
def get_x_offset(self, x, width):
return x - (self.wanted_x)
def get_y_offset(self, y, height):
return y - (height/2)
def get_rotation_pid(self):
return RotationPID(self.x_offset, self.wanted_x)
def get_distance(self, y_offset):
print(y_offset)
return ((263.95) / (1.0 + ( 46.8851 * math.pow(math.e, -0.008061 * y_offset) )) ) + 4.88508
def get_area(self, w, h):
return (w * h) * 2
def is_target_locked(self):
return self.target_locked