def extra_processing(pipeline):
"""
Performs extra processing on the pipeline's outputs and publishes data to NetworkTables.
:param pipeline: the pipeline that just processed an image
:return: None
"""
center_x_positions = []
center_y_positions = []
widths = []
heights = []
# Find the bounding boxes of the contours to get x, y, width, and height
for contour in pipeline.filter_contours_output:
x, y, w, h = cv2.boundingRect(contour)
center_x_positions.append(
x + w / 2
) # X and Y are coordinates of the top-left corner of the bounding box
center_y_positions.append(y + h / 2)
widths.append(w)
heights.append(y)
print(center_x_positions)
# Publish to the '/vision' network table
table = NetworkTable.getTable("/vision")
table.putValue("centerX", NumberArray.from_list(center_x_positions))
table.putValue("centerY", NumberArray.from_list(center_y_positions))
table.putValue("width", NumberArray.from_list(widths))
table.putValue("height", NumberArray.from_list(heights))
def main():
ip = "10.24.81.2"
NetworkTable.setIPAddress(ip)
NetworkTable.setClientMode()
#print "Initializing Network Tables"
NetworkTable.initialize()
goalFinder = GoalFinder()
stream = urllib.urlopen('http://10.24.81.11/mjpg/video.mjpg')
bytes = ''
#print "Start Target Search Loop..."
#turn true for single picture debuging
first = False
beagle = NetworkTable.getTable("GRIP")
goals_table = beagle.getSubTable("aGoalContours")
while True:
#TODO: Fetch image from camera.
# img = cv2.imread("0.jpg")
bytes += stream.read(16384)
b = bytes.rfind('\xff\xd9')
a = bytes.rfind('\xff\xd8', 0, b - 1)
if a != -1 and b != -1:
jpg = bytes[a:b + 2]
bytes = bytes[b + 2:]
img = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8),
cv2.CV_LOAD_IMAGE_COLOR)
goalFinder.process_image(img)
goals_table.putValue("centerX",
NumberArray.from_list(goalFinder.targetXs))
goals_table.putValue("centerY",
NumberArray.from_list(goalFinder.targetYs))
goals_table.putValue(
"width", NumberArray.from_list(goalFinder.targetWidths))
goals_table.putValue(
"height", NumberArray.from_list(goalFinder.targetHeights))
goals_table.putValue("area",
NumberArray.from_list(goalFinder.targetAreas))
#if len(goalFinder.targetAreas) > 0:
# print goalFinder.targetAreas
#Use if you want to the save the image and retrieve it later.
if first:
first = False
cv2.imwrite("test.jpg", img)
goals_table.putNumber("OwlCounter",
goals_table.getNumber("OwlCounter", 0) + 1)
sleep(.01)
def main():
ip = "10.24.81.2"
NetworkTable.setIPAddress(ip)
NetworkTable.setClientMode()
# print "Initializing Network Tables"
NetworkTable.initialize()
goalFinder = GoalFinder()
stream = urllib.urlopen("http://10.24.81.11/mjpg/video.mjpg")
bytes = ""
# print "Start Target Search Loop..."
# turn true for single picture debuging
first = False
beagle = NetworkTable.getTable("GRIP")
goals_table = beagle.getSubTable("aGoalContours")
while True:
# TODO: Fetch image from camera.
# img = cv2.imread("0.jpg")
bytes += stream.read(16384)
b = bytes.rfind("\xff\xd9")
a = bytes.rfind("\xff\xd8", 0, b - 1)
if a != -1 and b != -1:
jpg = bytes[a : b + 2]
bytes = bytes[b + 2 :]
img = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8), cv2.CV_LOAD_IMAGE_COLOR)
goalFinder.process_image(img)
goals_table.putValue("centerX", NumberArray.from_list(goalFinder.targetXs))
goals_table.putValue("centerY", NumberArray.from_list(goalFinder.targetYs))
goals_table.putValue("width", NumberArray.from_list(goalFinder.targetWidths))
goals_table.putValue("height", NumberArray.from_list(goalFinder.targetHeights))
goals_table.putValue("area", NumberArray.from_list(goalFinder.targetAreas))
# if len(goalFinder.targetAreas) > 0:
# print goalFinder.targetAreas
# Use if you want to the save the image and retrieve it later.
if first:
first = False
cv2.imwrite("test.jpg", img)
goals_table.putNumber("OwlCounter", goals_table.getNumber("OwlCounter", 0) + 1)
sleep(0.01)
