def main(): print('Initializing post-processor') post.init() print('Creating video capture') # From robot stream stream = socket.socket(socket.AF_INET, socket.SOCK_STREAM) while True: # Loop until we successfully connected try: stream.settimeout(4.5) stream.connect(("roborio-3647-frc.local", 1180)) print('Connected to video source') break # Get out of retry loop, as we were successful except (socket.timeout, OSError): print('Failed to connect to video source, retrying') stream = socket.socket(socket.AF_INET, socket.SOCK_STREAM) # Recreate new socket time.sleep(1.5) stream.send(struct.pack('!i', 30)) # FPS stream.send(struct.pack('!i', -1)) # HW_COMPRESSION stream.send(struct.pack('!i', 1)) # framesize # From webcam """ cap = cv2.VideoCapture(0) print('Connected to video source') """ print('Creating pipeline') pipeline = GripPipeline() print('Running pipeline') # From robot stream sbytes = bytearray() while True: # TODO: Insert Try Except, and restart on error newb = stream.recv(1024) sbytes += newb a = sbytes.find(b'\xff\xd8') b = sbytes.find(b'\xff\xd9') if a != -1 and b != -1: jpg = sbytes[a:b + 2] sbytes = sbytes[b + 2:] if len(jpg) == 0: continue frame = cv2.imdecode(np.fromstring(bytes(jpg), dtype=np.uint8), cv2.IMREAD_COLOR) pipeline.process(frame) post.process(frame, pipeline) # From webcam """ while cap.isOpened(): have_frame, frame = cap.read() if have_frame: pipeline.process(frame) extra_processing(frame, pipeline) """ print('Capture closed')
def main(): NetworkTable.setTeam(5587) # TODO set your team number NetworkTable.setClientMode() # TODO switch to RIO IP, or IP of laptop running OutlineViewer for setup NetworkTable.setIPAddress('10.55.87.2') NetworkTable.initialize() # TODO find what v4l2-ctl settings you need. Pass each commandline option # through this array. REQUIRES v4l2-utils to be installed. call([ "v4l2-ctl", "--set-ctrl=exposure_auto=1", "--set-ctrl=exposure_absolute=9", "--set-ctrl=white_balance_temperature_auto=0" ], shell=False) cap = cv2.VideoCapture(0) pipeline = GripPipeline() while True: ret, frame = cap.read() if ret: # TODO add extra parameters if the pipeline takes more than just a # single image pipeline.process(frame) extra_processing(pipeline)
def getXY(): """ Code that determines the x any y values of the cubes in pixels No Parameters Returns the X coordinate and the Y coordinate """ cap = cv2.VideoCapture(0) # Connects to the Camera pipeline = GripPipeline() have_frame, frame = cap.read( ) # Sets the frame variable equal to the image the video puts off. if have_frame: pipeline.process(frame) # Isolates the Contours 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 ) # Gets the center of the Box by finding the adding half of the width widths.append(w) heights.append(h) print(center_x_positions[0]) print(center_y_positions[0]) return center_x_positions[0], center_y_positions[ 0] # Returns the X and Y Values
def main(system_arguments): # initialize the camera and grab a reference to the raw camera capture with PiCamera() as camera: camera_setup(camera) raw_capture = PiRGBArray(camera, size=(WINDOW_WIDTH, WINDOW_HEIGHT)) gripped = GripPipeline() # allow the camera to warm up time.sleep(0.1) # capture frames from the camera for frame in camera.capture_continuous(raw_capture, format="bgr", use_video_port=True): # grab the raw NumPy array representing the image, then initialize the timestamp # and occupied/unoccupied text image = frame.array gripped.process(image) c = gripped.filter_contours_output draw(c, image) # show the frame cv2.imshow("Frame", image) # clear the stream in preparation for the next frame raw_capture.truncate(0) # if the `q` key was pressed, break from the loop if cv2.waitKey(1) & 0xFF == ord("q"): break cv2.destroyAllWindows() return 0
def __init__(self, webcam_device, webcam_name, local_ip="127.0.0.1", local_port=8087, calc="peg"): self.__calc = calc # start web cam and set dimensions self.__camera = cv2.VideoCapture(webcam_device) self.__camera.set(cv2.CAP_PROP_FRAME_WIDTH, 640) self.__camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 480) # setup cv source to write frames to for mjpeg server self.__cvsource = cs.CvSource(webcam_name, cs.VideoMode.PixelFormat.kMJPEG, 320, 240, 30) # setup mjpeg server self.__mjpeg_server = cs.MjpegServer("httpserver", local_port) self.__mjpeg_server.setSource(self.__cvsource); # setup grip pipeline from grip.py self.__grip_pipeline = GripPipeline() # write camera info table = NetworkTable.getTable("CameraPublisher") cam = table.getSubTable(webcam_name) cam.putString("source", "usb:IMAQdx/") cam.putStringArray("streams", ["mjpg:http://" + local_ip + ":" + str(local_port) + "/stream.mjpg?name="+webcam_name]) if self.__debug: self.__webcam_name = webcam_name cv2.namedWindow(self.__webcam_name)
def main(): cs = CameraServer.getInstance() cs.enableLogging() camera = cs.startAutomaticCapture() camera.setResolution(HORIZONTAL_RES, VERTICAL_RES) NetworkTables.initialize(server='10.56.54.2') pipeline = GripPipeline() cvSink = cs.getVideo() outputStream = cs.putVideo('Shooter', HORIZONTAL_RES, VERTICAL_RES) img = np.zeros(shape=(VERTICAL_RES, HORIZONTAL_RES, 3), dtype=np.uint8) while True: time, img = cvSink.grabFrame(img) if time == 0: outputStream.notifyError(cvSink.getError()) continue pipeline.process(img) if len(pipeline.find_contours_output) > 0: extra_process( max(pipeline.find_contours_output, key=cv2.contourArea)) outputStream.putFrame(pipeline.find_contours_image)
def main(): if len(sys.argv) != 2: print("Error: specify an IP to connect to!") exit(0) ip = sys.argv[1] print(ip) print('Initializing NetworkTables') NetworkTables.setClientMode() #NetworkTables.setIPAddress('roboRIO-6355-FRC') NetworkTables.setTeam(6355) # NetworkTables.initialize() NetworkTables.initialize(server=ip) print('Creating video capture') cap = cv2.VideoCapture(0) print('Creating pipeline') pipeline = GripPipeline() print('Running pipeline') while cap.isOpened(): have_frame, frame = cap.read() if have_frame: print('have frame') cv2.imshow('Unprocessed', cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)) cv2.waitKey() pipeline.process(frame) extra_processing(pipeline) print('Capture closed')
def main(): ''' print('Initializing NetworkTables') NetworkTable.setIPAddress("10.52.55.98") NetworkTable.setClientMode() NetworkTable.initialize() print('Creating video capture') ''' cap = cv2.VideoCapture(0) print("here") bytes = '' first = False print('Creating pipeline') pipeline = GripPipeline() print('Running pipeline') while cap.isOpened(): have_frame, frame = cap.read() if have_frame: pipeline.process(frame) extra_processing(pipeline) print(x) ''' plt.grid(True) plt.legend(loc='best') plt.show() ''' print('Capture closed')
def __init__(self): self.grip = GripPipeline() self.ocv_vision = cv.VideoCapture() self.ocv_vision_on = False self.mjpg_process = None self.mjpg_on = False
def main(): print('Initializing NetworkTables...') NetworkTables.initialize(server=server) print('Creating Video Capture...') cap = cv2.VideoCapture(videoDevice) # Change Exposure (***change video device as needed***): os.system( 'v4l2-ctl -d /dev/video0 -c exposure_auto=1 -c exposure_absolute=0') print('Creating Pipeline...') pipeline = GripPipeline() print('Running Pipeline.') while cap.isOpened(): have_frame, frame = cap.read() if have_frame: pipeline.process(frame) publishData(pipeline) if enableGUI: # Set thickness of lines thickness = 2 # Draw the normal contours (Green): cv2.drawContours(frame, pipeline.filter_contours_output, -1, (0, 255, 0), thickness) # Draw the proper rectangles: for contour in pipeline.filter_contours_output: # Minimum Bounding Rectangle: minAreaRect_FULL = cv2.minAreaRect(contour) boxCorners = cv2.boxPoints(minAreaRect_FULL) # Numpy Conversion: box = numpy.array(boxCorners).reshape( (-1, 1, 2)).astype(numpy.int32) # Draw rotated rectangle (Red): cv2.drawContours(frame, [box], -1, (0, 0, 255), thickness) # Normal Bounding Rectangle: x, y, w, h = cv2.boundingRect(contour) cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), thickness) # Show all data in a window: cv2.imshow('FRC Vision', frame) # Kill if 'q' is pressed: if cv2.waitKey(1) & 0xFF == ord('q'): break print('Capture closed.')
class PipelineWrapper: def __init__(self, image): self.pw_image = image self.gp = GripPipeline() self.gp.process(self.pw_image) #Use the GripPipeline class to get contours def getContours(self): cnts = self.gp.filter_contours_output return cnts
def main(): NetworkTable.setTeam('0000') # TODO set your team number NetworkTable.initialize() cap = cv2.VideoCapture(0) pipeline = GripPipeline() while True: ret, frame = cap.read() if ret: pipeline.process( frame ) # TODO add extra parameters if the pipeline takes more than just a single image extra_processing(pipeline)
def main(): # For usb/built-in camera camera = cv2.VideoCapture(1) # For ip camera (MJPEG Stream) # camera = cv2.VideoCapture("/url-to-your-stream/video.mjpg") mypipeline = GripPipeline() while camera.isOpened(): have_frame, frame = camera.read() if have_frame is not None: mypipeline.process(frame) extra_process(mypipeline) sleep(0.5) print("Capture closed")
def __init__(self): self.grip = GripPipeline() self.cap = cv2.VideoCapture(0) self.blank_image = np.zeros((480, 640, 3), np.uint8) self.contoursImg = None self.newVar = None logging.basicConfig(level=logging.DEBUG) NetworkTables.initialize(server='10.62.39.2') self.rp = NetworkTables.getTable("RaspberryPi")
def main(cameraPort, CAMERA_INSTANCE): print('Waiting on network tables') wait_for_port_open(networktableHostname, networktablePort) print('Network tables available') print('Waiting on camera') wait_for_port_open(cameraHostname, cameraPort) print('Camera available') print('Initializing NetworkTables') NetworkTables.setClientMode() NetworkTables.setIPAddress(networktableHostname) NetworkTables.initialize() table = NetworkTables.getTable('/vision/diagnostic_%s' % CAMERA_INSTANCE) print('Creating video capture') stream = urllib.request.urlopen('http://%s:%d/?action=stream' % (cameraHostname, cameraPort)) print('Creating pipeline') pipeline = GripPipeline() if not stream.isclosed(): print('opened capture') print('Running pipeline') i = 0 previous_frame_time = time.time() extraBytes = bytes() while True: frame, extraBytes = getFrame(stream, extraBytes) frame_start = time.time() pipeline.process(frame) extra_processing(pipeline, CAMERA_INSTANCE) frame_end = time.time() frame_interval = frame_start - previous_frame_time frame_rate = 1 / (frame_interval) frame_time = frame_end - frame_start previous_frame_time = frame_start i += 1 table.putNumber('count', i) table.putNumber('frameRate', frame_rate) table.putNumber('frameTime', frame_time) table.putNumber('frameInterval', frame_interval) print('Capture closed')
class VisionCalls: def __init__(self): self.grip = GripPipeline() self.ocv_vision = cv.VideoCapture() self.ocv_vision_on = False self.mjpg_process = None self.mjpg_on = False def stream(self): """ Turns on streamer and closes opencv vision """ if self.ocv_vision_on: self.ocv_vision.release() self.ocv_vision_on = False if !self.mjpg_on: self.mjpg_process = subprocess.Popen( [ "mjpg_streamer", "-i", "input_uvc.so -d /dev/video0 -f 30 -r 640x480 -y -n", "-o", "output_http.so -w ./www -p 1180", "&" ]) self.mjpg_on = True def vision(self): """ Enables opencv and runs the process """ if self.mjpg_on: self.mjpg_process.kill() time.sleep(2.5) self.mjpg_on = False self.ocv_vision_on = False if !self.ocv_vision_on: self.ocv_vision.open(0) self.ocv_vision_on = True self.grip.process(self.ocv_vision.read()[1])
def main(): #Establishes a connection to NetworkTable print("Establishing a connection to the NetworkTable") NetworkTables.setClientMode() NetworkTables.setIPAddress("roboRIO-540-frc.local") NetworkTables.initialize() print("Connected to NetworkTable") #Captures frames and runs them through the GRIP Pipeline print("Starting vision tracking and GRIP Pipeline") cp = cv2.VideoCapture(0) pipeline = GripPipeline() while cp.isOpened(): have_frame, frame = cp.read() if have_frame: pipeline.process(frame) extra_processing(pipeline)
def main(): global idNum plDone = False didStreamSucceed = False while didStreamSucceed is False: if plDone is False: try: print "Creating pipeline" pipeline = GripPipeline.GripPipeline() print "Pipeline created" plDone = True except Exception as err: print "Error creating pipeline: " + str(err) if plDone is True: try: print "Opening Stream" stream = urllib.urlopen('http://10.42.37.2:1181/?action=stream') print "Stream Opened" didStreamSucceed = True except Exception as err: print "Error creating stream: " + str(err) print "Initialization Complete" bytes = '' isRunning = True while isRunning is True: try: 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.IMREAD_COLOR) #print "Writing /mnt/usb/pre" + str(idNum) + ".jpg" #cv2.imwrite("/mnt/usb/pre" + str(idNum) + ".jpg", img) #print "Running" pipeline.process(img, idNum) extra_processing(pipeline) except KeyboardInterrupt: print "Ending" isRunning = False except Exception as err: print "Error in main loop, continuing: " + str(err)
def main(): print('Initializing NetworkTables') NetworkTables.setClientMode() NetworkTables.setIPAddress('localhost') NetworkTables.initialize() print('Creating video capture') cap = cv2.VideoCapture(0) print('Creating pipeline') pipeline = GripPipeline() print('Running pipeline') while cap.isOpened(): have_frame, frame = cap.read() if have_frame: pipeline.process(frame) extra_processing(pipeline) print('Capture closed')
def start_process(cv_sink, nt_instance): data_entry = nt_instance.getTable("Vision").getEntry("data") data_entry.setDefaultString("-1 -1") pipeline = GripPipeline() while True: _, frame = cv_sink.grabFrame(np.zeros((480, 640, 3), dtype=np.uint8)) pipeline.process(frame) contours = pipeline.find_contours_output if len(contours) > 0: contour = get_largest_contour(contours) moments = cv2.moments(contour) if moments["m00"] != 0: center_x = int(moments["m10"] / moments["m00"]) x, y, width, height = cv2.boundingRect(contour) data_entry.setString("{} {}".format(center_x, width)) print("Contour:", center_x, width) else: data_entry.setString("-1 -1") else: data_entry.setString("-1 -1")
def main(): parser = argparse.ArgumentParser() parser.add_argument("--img", required=True) args = parser.parse_args() image_name = args.img image2 = image.copy() gp = GripPipeline() gp.process(image2) contours = gp.find_contours_output print(len(contours)) #Number of contours found #Left Target e = 0.05 * cv2.arcLength(contours[0], True) #6 approx = cv2.approxPolyDP(contours[0], e, True) #Finds 4 corners of a target bottomLeft = findBottomLeft(approx) print(bottomLeft) upperLeft = findUpperLeft(approx) print(upperLeft) print(approx ) #coordinates of all corners for checking if bottomLeft is correct #Right Target e2 = 0.1 * cv2.arcLength(contours[1], True) #4 approx2 = cv2.approxPolyDP(contours[1], e2, True) #Finds 4 corners of other target bottomRight = findBottomRight(approx2) print(bottomRight) upperRight = findUpperRight(approx2) print(upperRight) print(approx2) cv2.drawContours(image2, approx, -1, (0, 255, 0), 2) cv2.drawContours(image2, approx2, -1, (0, 255, 0), 2) cv2.imshow("contours", image2) cv2.waitKey(0)
def main(): """Run this file to process vision code. Please go to README.md to learn how to use this properly By Grant Perkins, 2018 """ # Initialize pipeline, image, camera server pipe = GripPipeline() img = np.zeros(shape=(480, 640, 3), dtype=np.uint8) cs = CameraServer.getInstance() camera = cs.startAutomaticCapture() camera.setResolution(640, 480) camera.setFPS(20) camera.setExposureManual(40) # Get a CvSink. This will capture images from the camera cvsink = cs.getVideo() # Wait on vision processing until connected to Network Tables cond = threading.Condition() notified = [False] def listener(connected, info): print(info, '; Connected=%s' % connected) with cond: notified[0] = True cond.notify() NetworkTables.initialize(server='roborio-1100-frc.local') NetworkTables.addConnectionListener(listener, immediateNotify=True) with cond: print("Waiting") if not notified[0]: # Wait until connected. cond.wait() is exited once listener is called by ConnectionListener cond.wait() print("Connected!") table = NetworkTablesInstance.getDefault().getTable("Pi") imagetaken = False last = -1 while True: time.sleep(.4) # Tell the CvSink to grab a frame from the camera and put it # in the source image. If there is an error notify the output. t, img = cvsink.grabFrame(img) if t == 0: continue pipe.process(img) cx, cy = pipe.get_centeroid() area = pipe.get_area() print(cx) if cx != last and cx != -1: print(cx) last = cx table.getEntry("centerx").setDouble(cx) table.getEntry("centery").setDouble(cy) table.getEntry("area").setDouble(area)
def getXY(): cap = cv2.VideoCapture(0) pipeline = GripPipeline() have_frame, frame = cap.read() print(frame.shape) if have_frame: pipeline.process(frame) 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(h) print(center_x_positions[0]) print(center_y_positions[0]) return center_x_positions[0], center_y_positions[0]
def main(): global idNum while True: plDone = False didStreamSucceed = False while didStreamSucceed is False: if plDone is False: try: print "Creating pipeline" pipeline = GripPipeline.GripPipeline() print "Pipeline created" plDone = True except Exception as err: print "Error creating pipeline: " + str(err) if plDone is True: try: print "Opening Stream" camTable = NetworkTables.getTable( 'CameraPublisher/USB Camera 0') cameras = camTable.getStringArray('streams') print cameras return # for item in cameras: # print item stream = cv2.VideoCapture( 'http://10.42.37.2:1181/stream.mjpg') print "Stream Opened" didStreamSucceed = True except Exception as err: print "Error creating stream: " + str(err) print "Initialization Complete" while stream.isOpened(): ret, img = stream.read() if ret is True: pipeline.process(img) if len(pipeline.filter_contours_output) >= 1 and (idNum % 10) is 0: print "Writing image to usb" cv2.imwrite("/mnt/usb/" + str(idNum) + "raw.jpg", img) cv2.imwrite("/mnt/usb/" + str(idNum) + "filtered.jpg", pipeline.hsl_threshold_output) extra_processing(pipeline) else: print "Error reading from camera" break
def main(): global idNum while True: plDone = False didStreamSucceed = False while didStreamSucceed is False: if plDone is False: try: print "Creating pipeline" pipeline = GripPipeline.GripPipeline() print "Pipeline created" plDone = True except Exception as err: print "Error creating pipeline: " + str(err) if plDone is True: try: print "Opening Stream" stream = cv2.VideoCapture('http://roborio-4237-frc.local:1181/stream.mjpg') #stream = cv2.VideoCapture(1) print "Stream Opened" didStreamSucceed = True except Exception as err: print "Error creating stream: " + str(err) print "Initialization Complete" while stream.isOpened(): ret, img = stream.read() if ret is True: pipeline.process(img) if len(pipeline.filter_contours_output) >= 1 and (idNum % 10) is 0: pass #print "Writing image to usb" #cv2.imwrite("/mnt/usb/" + str(idNum) + "raw.jpg", img) #cv2.imwrite("/mnt/usb/" + str(idNum) + "filtered.jpg", pipeline.hsl_threshold_output) extra_processing(pipeline) else: print "Error reading from camera" break
class Vision: gp = GripPipeline() #initialize network tables comms sd = NetworkTables.getTable("SmartDashboard") angle = 0 dist = 0 def pImg(self): img = self.grab() # img = cv2.imread("C:\Users\KnightVision\Pictures\RPI vision testing\ledPicx\img1487521546_0.jpg", cv2.IMREAD_COLOR) # temporary test code if type(img) is numpy.ndarray: # checks if image is not empty print("Processing . . . ") cx, self.dist = self.gp.process(img) self.calc_angle(cx) else: print("ERROR: cv2 img is empty! || " + "testImg.jpg") return 2 def calc_angle(self, u): print("Calculating Angle . . . \n") raw_angle = math.degrees(math.atan((u-176)/298.7)) init_angle = math.degrees(math.atan(1.25/self.dist)) self.angle = init_angle + raw_angle print(init_angle, raw_angle, self.angle) print("DONE!") def grab(self): result, im = cap.read() return im def reset_exposure(self): os.system("v4l2-ctl -d /dev/video0 -c exposure_auto=1 -c exposure_absolute=0") print("Setting exposure setting to 5 . . . ") time.sleep(1) print("Done!") def push_data(self): if self.angle > 0.1 or self.angle < -0.1: self.sd.putNumber("pegAngle", self.angle) if self.dist > 0: self.sd.putNumber("distance", self.dist)
import cv2 from grip import GripPipeline from networktables import NetworkTables cap = cv2.VideoCapture(0) NetworkTables.initialize(server='roboRIO-1437-FRC.local') table = NetworkTables.getTable('Vision') #Clear the table for key in table.getKeys(): table.delete(key) grip = GripPipeline() while(True): # Capture frame-by-frame ret, frame = cap.read() if not ret: raise Exception("could not load image !") # Our operations on the frame come here #height, width, channels = frame.shape #print(width) gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) sift = cv2.xfeatures2d.SIFT_create() kp = sift.detect(gray, None) cv2.drawKeypoints(gray, kp, frame, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) # Display the resulting frame cv2.imshow('frame', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break
class Main(): def __init__(self): self.grip = GripPipeline() self.cap = cv2.VideoCapture(0) self.blank_image = np.zeros((480, 640, 3), np.uint8) self.contoursImg = None self.newVar = None logging.basicConfig(level=logging.DEBUG) NetworkTables.initialize(server='10.62.39.2') self.rp = NetworkTables.getTable("RaspberryPi") def drawRectangle(self, contour_output, contour_hierarchy, source0): height, width, _ = source0.shape min_x, min_y = width, height max_x = max_y = 0 # computes the bounding box for the contour, and draws it on the frame, for contour, hier in zip(contour_output, contour_hierarchy): (x,y,w,h) = cv2.boundingRect(contour) min_x, max_x = min(x, min_x), max(x+w, max_x) min_y, max_y = min(y, min_y), max(y+h, max_y) center = x+(w/2) if w > 80 and h > 80: cv2.rectangle(source0, (x,y), (x+w,y+h), (255, 0, 0), 2) cv2.circle(source0, (int(x+(w/2)), int(y+(h/2))), 10, (0, 255, 0)) if max_x - min_x > 0 and max_y - min_y > 0: cv2.rectangle(source0, (min_x, min_y), (max_x, max_y), (255, 0, 0), 2) cv2.circle(source0, (int(x+(w/2)), int(y+(h/2))), 10, (0, 255, 0)) return center def drawRectangleBetter(self, cnt, img): rect = cv2.minAreaRect(img) box = cv2.boxPoints(rect) # cv2.boxPoints(rect) for OpenCV 3.x box = np.int0(box) cv2.drawContours(img, [box], 0, (0,0,255), 2) def run(self): while True: ret, frame = self.cap.read() contoursImg = frame.copy() self.grip.process(frame) cv2.drawContours(self.blank_image, self.grip.find_contours_output, cv2.FILLED, [0, 0, 255], 2) circleXCenter = self.drawRectangle(self.grip.filter_contours_output, self.grip.contour_hierarchy, contoursImg) #cv2.imshow("source", frame) #cv2.imshow("rectangle", contoursImg) #cv2.imshow("frame", blank_image) circleXCenter = (circleXCenter - 320) / 10 self.rp.putNumber("distance", circleXCenter)
import os from networktables import NetworkTable from grip import GripPipeline now = datetime.datetime.now() print("Vision Log for " + str(now.day) + "/" + str(now.month) + "/" + str(now.year) + " ~ " + str(now.hour) + ":" + str(now.minute) + ":" + str(now.second)) print("OpenCV version: " + str(cv2.__version__)) print("Starting Vision...") bytes = '' version = int(cv2.__version__[:1]) streamRunning = True pipeline = GripPipeline() try: NetworkTable.setTeam(2551) NetworkTable.setIPAddress("roborio-2551-frc.local") NetworkTable.setClientMode() NetworkTable.initialize() print("Initializing Network Tables...") except: print("Network Tables already initialized") pass #NetworkTable.setTeam(2551) #NetworkTable.setIPAddress("roborio-2551-frc.local") #NetworkTable.setClientMode() #NetworkTable.initialize()
and float(cnt1.w) / float(cnt2.w) <= 1.2): rc = SUCCESS if rc == ERROR: cnt1.reset() cnt2.reset() return rc #Configuring the camera to look the way we want config_microsoft_cam() #init_UDP_client() #init_network_tables() M_HFOV = find_fov(M_HA, M_VA, M_DFOV) #print(M_HFOV) pipeline = GripPipeline() vision_math = Math() #Video Capture stuff cam = cv2.VideoCapture(0) #Set Camera resoultion cam.set(3, HRES) cam.set(4, VRES) cnt1 = Contour() cnt2 = Contour() count = 0 t_end = time.time() + 10 while time.time() <= t_end: count = count + 1 captureStartTime = cv2.getTickCount() s, im = cam.read() # captures image