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#!/usr/bin/env python3 | |
#---------------------------------------------------------------------------- | |
# Copyright (c) 2018 FIRST. All Rights Reserved. | |
# Open Source Software - may be modified and shared by FRC teams. The code | |
# must be accompanied by the FIRST BSD license file in the root directory of | |
# the project. | |
# My 2019 license: use it as much as you want. Crediting is recommended because it lets me know that I am being useful. | |
# Credit to Screaming Chickens 3997 | |
# This is meant to be used in conjuction with WPILib Raspberry Pi image: https://github.com/wpilibsuite/FRCVision-pi-gen | |
#---------------------------------------------------------------------------- | |
import json | |
import time | |
import sys | |
from threading import Thread | |
from cscore import CameraServer, VideoSource | |
from networktables import NetworkTablesInstance | |
import cv2 | |
import numpy as np | |
from networktables import NetworkTables | |
import math | |
########### SET RESOLUTION TO 256x144 !!!! ############ | |
# import the necessary packages | |
import datetime | |
#Class to examine Frames per second of camera stream. Currently not used. | |
class FPS: | |
def __init__(self): | |
# store the start time, end time, and total number of frames | |
# that were examined between the start and end intervals | |
self._start = None | |
self._end = None | |
self._numFrames = 0 | |
def start(self): | |
# start the timer | |
self._start = datetime.datetime.now() | |
return self | |
def stop(self): | |
# stop the timer | |
self._end = datetime.datetime.now() | |
def update(self): | |
# increment the total number of frames examined during the | |
# start and end intervals | |
self._numFrames += 1 | |
def elapsed(self): | |
# return the total number of seconds between the start and | |
# end interval | |
return (self._end - self._start).total_seconds() | |
def fps(self): | |
# compute the (approximate) frames per second | |
return self._numFrames / self.elapsed() | |
# class that runs separate thread for showing video, | |
class VideoShow: | |
""" | |
Class that continuously shows a frame using a dedicated thread. | |
""" | |
def __init__(self, imgWidth, imgHeight, cameraServer, frame=None, name='stream'): | |
self.outputStream = cameraServer.putVideo(name, imgWidth, imgHeight) | |
self.frame = frame | |
self.stopped = False | |
def start(self): | |
Thread(target=self.show, args=()).start() | |
return self | |
def show(self): | |
while not self.stopped: | |
self.outputStream.putFrame(self.frame) | |
def stop(self): | |
self.stopped = True | |
def notifyError(self, error): | |
self.outputStream.notifyError(error) | |
class WebcamVideoStream: | |
def __init__(self, camera, cameraServer, frameWidth, frameHeight, name="WebcamVideoStream"): | |
# initialize the video camera stream and read the first frame | |
# from the stream | |
#Automatically sets exposure to 0 to track tape | |
self.webcam = camera | |
self.webcam.setExposureManual(0) | |
#Some booleans so that we don't keep setting exposure over and over to the same value | |
self.autoExpose = False | |
self.prevValue = self.autoExpose | |
#Make a blank image to write on | |
self.img = np.zeros(shape=(frameWidth, frameHeight, 3), dtype=np.uint8) | |
#Gets the video | |
self.stream = cameraServer.getVideo(camera = camera) | |
(self.timestamp, self.img) = self.stream.grabFrame(self.img) | |
# initialize the thread name | |
self.name = name | |
# initialize the variable used to indicate if the thread should | |
# be stopped | |
self.stopped = False | |
def start(self): | |
# start the thread to read frames from the video stream | |
t = Thread(target=self.update, name=self.name, args=()) | |
t.daemon = True | |
t.start() | |
return self | |
def update(self): | |
# keep looping infinitely until the thread is stopped | |
while True: | |
# if the thread indicator variable is set, stop the thread | |
if self.stopped: | |
return | |
#Boolean logic we don't keep setting exposure over and over to the same value | |
if self.autoExpose: | |
self.webcam.setExposureAuto() | |
else: | |
self.webcam.setExposureManual(0) | |
#gets the image and timestamp from cameraserver | |
(self.timestamp, self.img) = self.stream.grabFrame(self.img) | |
def read(self): | |
# return the frame most recently read | |
return self.timestamp, self.img | |
def stop(self): | |
# indicate that the thread should be stopped | |
self.stopped = True | |
def getError(self): | |
return self.stream.getError() | |
###################### PROCESSING OPENCV ################################ | |
#Angles in radians | |
#image size ratioed to 16:9 | |
image_width = 256 | |
image_height = 144 | |
#Lifecam 3000 from datasheet | |
#Datasheet: https://dl2jx7zfbtwvr.cloudfront.net/specsheets/WEBC1010.pdf | |
diagonalView = math.radians(68.5) | |
#16:9 aspect ratio | |
horizontalAspect = 16 | |
verticalAspect = 9 | |
#Reasons for using diagonal aspect is to calculate horizontal field of view. | |
diagonalAspect = math.hypot(horizontalAspect, verticalAspect) | |
#Calculations: http://vrguy.blogspot.com/2013/04/converting-diagonal-field-of-view-and.html | |
horizontalView = math.atan(math.tan(diagonalView/2) * (horizontalAspect / diagonalAspect)) * 2 | |
verticalView = math.atan(math.tan(diagonalView/2) * (verticalAspect / diagonalAspect)) * 2 | |
#Focal Length calculations: https://docs.google.com/presentation/d/1ediRsI-oR3-kwawFJZ34_ZTlQS2SDBLjZasjzZ-eXbQ/pub?start=false&loop=false&slide=id.g12c083cffa_0_165 | |
H_FOCAL_LENGTH = image_width / (2*math.tan((horizontalView/2))) | |
V_FOCAL_LENGTH = image_height / (2*math.tan((verticalView/2))) | |
#blurs have to be odd | |
green_blur = 7 | |
orange_blur = 27 | |
# define range of green of retroreflective tape in HSV | |
lower_green = np.array([0,220,25]) | |
upper_green = np.array([101, 255, 255]) | |
#define range of orange from cargo ball in HSV | |
lower_orange = np.array([0,193,92]) | |
upper_orange = np.array([23, 255, 255]) | |
#Flip image if camera mounted upside down | |
def flipImage(frame): | |
return cv2.flip( frame, -1 ) | |
#Blurs frame | |
def blurImg(frame, blur_radius): | |
img = frame.copy() | |
blur = cv2.blur(img,(blur_radius,blur_radius)) | |
return blur | |
# Masks the video based on a range of hsv colors | |
# Takes in a frame, range of color, and a blurred frame, returns a masked frame | |
def threshold_video(lower_color, upper_color, blur): | |
# Convert BGR to HSV | |
hsv = cv2.cvtColor(blur, cv2.COLOR_BGR2HSV) | |
# hold the HSV image to get only red colors | |
mask = cv2.inRange(hsv, lower_color, upper_color) | |
# Returns the masked imageBlurs video to smooth out image | |
return mask | |
# Finds the tape targets from the masked image and displays them on original stream + network tales | |
def findTargets(frame, mask): | |
# Finds contours | |
_, contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_TC89_KCOS) | |
# Take each frame | |
# Gets the shape of video | |
screenHeight, screenWidth, _ = frame.shape | |
# Gets center of height and width | |
centerX = (screenWidth / 2) - .5 | |
centerY = (screenHeight / 2) - .5 | |
# Copies frame and stores it in image | |
image = frame.copy() | |
# Processes the contours, takes in (contours, output_image, (centerOfImage) | |
if len(contours) != 0: | |
image = findTape(contours, image, centerX, centerY) | |
# Shows the contours overlayed on the original video | |
return image | |
# Finds the balls from the masked image and displays them on original stream + network tables | |
def findCargo(frame, mask): | |
# Finds contours | |
_, contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_TC89_KCOS) | |
# Take each frame | |
# Gets the shape of video | |
screenHeight, screenWidth, _ = frame.shape | |
# Gets center of height and width | |
centerX = (screenWidth / 2) - .5 | |
centerY = (screenHeight / 2) - .5 | |
# Copies frame and stores it in image | |
image = frame.copy() | |
# Processes the contours, takes in (contours, output_image, (centerOfImage) | |
if len(contours) != 0: | |
image = findBall(contours, image, centerX, centerY) | |
# Shows the contours overlayed on the original video | |
return image | |
# Draws Contours and finds center and yaw of orange ball | |
# centerX is center x coordinate of image | |
# centerY is center y coordinate of image | |
def findBall(contours, image, centerX, centerY): | |
screenHeight, screenWidth, channels = image.shape; | |
#Seen vision targets (correct angle, adjacent to each other) | |
cargo = [] | |
if len(contours) > 0: | |
#Sort contours by area size (biggest to smallest) | |
cntsSorted = sorted(contours, key=lambda x: cv2.contourArea(x), reverse=True) | |
biggestCargo = [] | |
for cnt in cntsSorted: | |
x, y, w, h = cv2.boundingRect(cnt) | |
aspect_ratio = float(w) / h | |
# Get moments of contour; mainly for centroid | |
M = cv2.moments(cnt) | |
# Get convex hull (bounding polygon on contour) | |
hull = cv2.convexHull(cnt) | |
# Calculate Contour area | |
cntArea = cv2.contourArea(cnt) | |
# Filters contours based off of size | |
if (checkBall(cntArea, aspect_ratio)): | |
### MOSTLY DRAWING CODE, BUT CALCULATES IMPORTANT INFO ### | |
# Gets the centeroids of contour | |
if M["m00"] != 0: | |
cx = int(M["m10"] / M["m00"]) | |
cy = int(M["m01"] / M["m00"]) | |
else: | |
cx, cy = 0, 0 | |
if(len(biggestCargo) < 3): | |
##### DRAWS CONTOUR###### | |
# Gets rotated bounding rectangle of contour | |
rect = cv2.minAreaRect(cnt) | |
# Creates box around that rectangle | |
box = cv2.boxPoints(rect) | |
# Not exactly sure | |
box = np.int0(box) | |
# Draws rotated rectangle | |
cv2.drawContours(image, [box], 0, (23, 184, 80), 3) | |
# Draws a vertical white line passing through center of contour | |
cv2.line(image, (cx, screenHeight), (cx, 0), (255, 255, 255)) | |
# Draws a white circle at center of contour | |
cv2.circle(image, (cx, cy), 6, (255, 255, 255)) | |
# Draws the contours | |
cv2.drawContours(image, [cnt], 0, (23, 184, 80), 1) | |
# Gets the (x, y) and radius of the enclosing circle of contour | |
(x, y), radius = cv2.minEnclosingCircle(cnt) | |
# Rounds center of enclosing circle | |
center = (int(x), int(y)) | |
# Rounds radius of enclosning circle | |
radius = int(radius) | |
# Makes bounding rectangle of contour | |
rx, ry, rw, rh = cv2.boundingRect(cnt) | |
# Draws countour of bounding rectangle and enclosing circle in green | |
cv2.rectangle(image, (rx, ry), (rx + rw, ry + rh), (23, 184, 80), 1) | |
cv2.circle(image, center, radius, (23, 184, 80), 1) | |
# Appends important info to array | |
if not biggestCargo: | |
biggestCargo.append([cx, cy, cnt]) | |
elif [cx, cy, cnt] not in biggestCargo: | |
biggestCargo.append([cx, cy, cnt]) | |
# Check if there are cargo seen | |
if (len(biggestCargo) > 0): | |
#pushes that it sees cargo to network tables | |
networkTable.putBoolean("cargoDetected", True) | |
# Sorts targets based on x coords to break any angle tie | |
biggestCargo.sort(key=lambda x: math.fabs(x[0])) | |
closestCargo = min(biggestCargo, key=lambda x: (math.fabs(x[0] - centerX))) | |
xCoord = closestCargo[0] | |
finalTarget = calculateYaw(xCoord, centerX, H_FOCAL_LENGTH) | |
print("Yaw: " + str(finalTarget)) | |
# Puts the yaw on screen | |
# Draws yaw of target + line where center of target is | |
cv2.putText(image, "Yaw: " + str(finalTarget), (40, 40), cv2.FONT_HERSHEY_COMPLEX, .6, | |
(255, 255, 255)) | |
cv2.line(image, (xCoord, screenHeight), (xCoord, 0), (255, 0, 0), 2) | |
currentAngleError = finalTarget | |
#pushes cargo angle to network tables | |
networkTable.putNumber("cargoYaw", currentAngleError) | |
else: | |
#pushes that it doesn't see cargo to network tables | |
networkTable.putBoolean("cargoDetected", False) | |
cv2.line(image, (round(centerX), screenHeight), (round(centerX), 0), (255, 255, 255), 2) | |
return image | |
# Draws Contours and finds center and yaw of vision targets | |
# centerX is center x coordinate of image | |
# centerY is center y coordinate of image | |
def findTape(contours, image, centerX, centerY): | |
screenHeight, screenWidth, channels = image.shape; | |
#Seen vision targets (correct angle, adjacent to each other) | |
targets = [] | |
if len(contours) >= 2: | |
#Sort contours by area size (biggest to smallest) | |
cntsSorted = sorted(contours, key=lambda x: cv2.contourArea(x), reverse=True) | |
biggestCnts = [] | |
for cnt in cntsSorted: | |
# Get moments of contour; mainly for centroid | |
M = cv2.moments(cnt) | |
# Get convex hull (bounding polygon on contour) | |
hull = cv2.convexHull(cnt) | |
# Calculate Contour area | |
cntArea = cv2.contourArea(cnt) | |
# calculate area of convex hull | |
hullArea = cv2.contourArea(hull) | |
# Filters contours based off of size | |
if (checkContours(cntArea, hullArea)): | |
### MOSTLY DRAWING CODE, BUT CALCULATES IMPORTANT INFO ### | |
# Gets the centeroids of contour | |
if M["m00"] != 0: | |
cx = int(M["m10"] / M["m00"]) | |
cy = int(M["m01"] / M["m00"]) | |
else: | |
cx, cy = 0, 0 | |
if(len(biggestCnts) < 13): | |
#### CALCULATES ROTATION OF CONTOUR BY FITTING ELLIPSE ########## | |
rotation = getEllipseRotation(image, cnt) | |
# Calculates yaw of contour (horizontal position in degrees) | |
yaw = calculateYaw(cx, centerX, H_FOCAL_LENGTH) | |
# Calculates yaw of contour (horizontal position in degrees) | |
pitch = calculatePitch(cy, centerY, V_FOCAL_LENGTH) | |
##### DRAWS CONTOUR###### | |
# Gets rotated bounding rectangle of contour | |
rect = cv2.minAreaRect(cnt) | |
# Creates box around that rectangle | |
box = cv2.boxPoints(rect) | |
# Not exactly sure | |
box = np.int0(box) | |
# Draws rotated rectangle | |
cv2.drawContours(image, [box], 0, (23, 184, 80), 3) | |
# Calculates yaw of contour (horizontal position in degrees) | |
yaw = calculateYaw(cx, centerX, H_FOCAL_LENGTH) | |
# Calculates yaw of contour (horizontal position in degrees) | |
pitch = calculatePitch(cy, centerY, V_FOCAL_LENGTH) | |
# Draws a vertical white line passing through center of contour | |
cv2.line(image, (cx, screenHeight), (cx, 0), (255, 255, 255)) | |
# Draws a white circle at center of contour | |
cv2.circle(image, (cx, cy), 6, (255, 255, 255)) | |
# Draws the contours | |
cv2.drawContours(image, [cnt], 0, (23, 184, 80), 1) | |
# Gets the (x, y) and radius of the enclosing circle of contour | |
(x, y), radius = cv2.minEnclosingCircle(cnt) | |
# Rounds center of enclosing circle | |
center = (int(x), int(y)) | |
# Rounds radius of enclosning circle | |
radius = int(radius) | |
# Makes bounding rectangle of contour | |
rx, ry, rw, rh = cv2.boundingRect(cnt) | |
boundingRect = cv2.boundingRect(cnt) | |
# Draws countour of bounding rectangle and enclosing circle in green | |
cv2.rectangle(image, (rx, ry), (rx + rw, ry + rh), (23, 184, 80), 1) | |
cv2.circle(image, center, radius, (23, 184, 80), 1) | |
# Appends important info to array | |
if not biggestCnts: | |
biggestCnts.append([cx, cy, rotation]) | |
elif [cx, cy, rotation] not in biggestCnts: | |
biggestCnts.append([cx, cy, rotation]) | |
# Sorts array based on coordinates (leftmost to rightmost) to make sure contours are adjacent | |
biggestCnts = sorted(biggestCnts, key=lambda x: x[0]) | |
# Target Checking | |
for i in range(len(biggestCnts) - 1): | |
#Rotation of two adjacent contours | |
tilt1 = biggestCnts[i][2] | |
tilt2 = biggestCnts[i + 1][2] | |
#x coords of contours | |
cx1 = biggestCnts[i][0] | |
cx2 = biggestCnts[i + 1][0] | |
cy1 = biggestCnts[i][1] | |
cy2 = biggestCnts[i + 1][1] | |
# If contour angles are opposite | |
if (np.sign(tilt1) != np.sign(tilt2)): | |
centerOfTarget = math.floor((cx1 + cx2) / 2) | |
#ellipse negative tilt means rotated to right | |
#Note: if using rotated rect (min area rectangle) | |
# negative tilt means rotated to left | |
# If left contour rotation is tilted to the left then skip iteration | |
if (tilt1 > 0): | |
if (cx1 < cx2): | |
continue | |
# If left contour rotation is tilted to the left then skip iteration | |
if (tilt2 > 0): | |
if (cx2 < cx1): | |
continue | |
#Angle from center of camera to target (what you should pass into gyro) | |
yawToTarget = calculateYaw(centerOfTarget, centerX, H_FOCAL_LENGTH) | |
#Make sure no duplicates, then append | |
if not targets: | |
targets.append([centerOfTarget, yawToTarget]) | |
elif [centerOfTarget, yawToTarget] not in targets: | |
targets.append([centerOfTarget, yawToTarget]) | |
#Check if there are targets seen | |
if (len(targets) > 0): | |
# pushes that it sees vision target to network tables | |
networkTable.putBoolean("tapeDetected", True) | |
#Sorts targets based on x coords to break any angle tie | |
targets.sort(key=lambda x: math.fabs(x[0])) | |
finalTarget = min(targets, key=lambda x: math.fabs(x[1])) | |
# Puts the yaw on screen | |
#Draws yaw of target + line where center of target is | |
cv2.putText(image, "Yaw: " + str(finalTarget[1]), (40, 40), cv2.FONT_HERSHEY_COMPLEX, .6, | |
(255, 255, 255)) | |
cv2.line(image, (finalTarget[0], screenHeight), (finalTarget[0], 0), (255, 0, 0), 2) | |
currentAngleError = finalTarget[1] | |
# pushes vision target angle to network tables | |
networkTable.putNumber("tapeYaw", currentAngleError) | |
else: | |
# pushes that it deosn't see vision target to network tables | |
networkTable.putBoolean("tapeDetected", False) | |
cv2.line(image, (round(centerX), screenHeight), (round(centerX), 0), (255, 255, 255), 2) | |
return image | |
# Checks if tape contours are worthy based off of contour area and (not currently) hull area | |
def checkContours(cntSize, hullSize): | |
return cntSize > (image_width / 6) | |
# Checks if ball contours are worthy based off of contour area and (not currently) hull area | |
def checkBall(cntSize, cntAspectRatio): | |
return (cntSize > (image_width / 2)) and (round(cntAspectRatio) == 1) | |
#Forgot how exactly it works, but it works! | |
def translateRotation(rotation, width, height): | |
if (width < height): | |
rotation = -1 * (rotation - 90) | |
if (rotation > 90): | |
rotation = -1 * (rotation - 180) | |
rotation *= -1 | |
return round(rotation) | |
def calculateDistance(heightOfCamera, heightOfTarget, pitch): | |
heightOfTargetFromCamera = heightOfTarget - heightOfCamera | |
# Uses trig and pitch to find distance to target | |
''' | |
d = distance | |
h = height between camera and target | |
a = angle = pitch | |
tan a = h/d (opposite over adjacent) | |
d = h / tan a | |
. | |
/| | |
/ | | |
/ |h | |
/a | | |
camera ----- | |
d | |
''' | |
distance = math.fabs(heightOfTargetFromCamera / math.tan(math.radians(pitch))) | |
return distance | |
# Uses trig and focal length of camera to find yaw. | |
# Link to further explanation: https://docs.google.com/presentation/d/1ediRsI-oR3-kwawFJZ34_ZTlQS2SDBLjZasjzZ-eXbQ/pub?start=false&loop=false&slide=id.g12c083cffa_0_298 | |
def calculateYaw(pixelX, centerX, hFocalLength): | |
yaw = math.degrees(math.atan((pixelX - centerX) / hFocalLength)) | |
return round(yaw) | |
# Link to further explanation: https://docs.google.com/presentation/d/1ediRsI-oR3-kwawFJZ34_ZTlQS2SDBLjZasjzZ-eXbQ/pub?start=false&loop=false&slide=id.g12c083cffa_0_298 | |
def calculatePitch(pixelY, centerY, vFocalLength): | |
pitch = math.degrees(math.atan((pixelY - centerY) / vFocalLength)) | |
# Just stopped working have to do this: | |
pitch *= -1 | |
return round(pitch) | |
def getEllipseRotation(image, cnt): | |
try: | |
# Gets rotated bounding ellipse of contour | |
ellipse = cv2.fitEllipse(cnt) | |
centerE = ellipse[0] | |
# Gets rotation of ellipse; same as rotation of contour | |
rotation = ellipse[2] | |
# Gets width and height of rotated ellipse | |
widthE = ellipse[1][0] | |
heightE = ellipse[1][1] | |
# Maps rotation to (-90 to 90). Makes it easier to tell direction of slant | |
rotation = translateRotation(rotation, widthE, heightE) | |
cv2.ellipse(image, ellipse, (23, 184, 80), 3) | |
return rotation | |
except: | |
# Gets rotated bounding rectangle of contour | |
rect = cv2.minAreaRect(cnt) | |
# Creates box around that rectangle | |
box = cv2.boxPoints(rect) | |
# Not exactly sure | |
box = np.int0(box) | |
# Gets center of rotated rectangle | |
center = rect[0] | |
# Gets rotation of rectangle; same as rotation of contour | |
rotation = rect[2] | |
# Gets width and height of rotated rectangle | |
width = rect[1][0] | |
height = rect[1][1] | |
# Maps rotation to (-90 to 90). Makes it easier to tell direction of slant | |
rotation = translateRotation(rotation, width, height) | |
return rotation | |
#################### FRC VISION PI Image Specific ############# | |
configFile = "/boot/frc.json" | |
class CameraConfig: pass | |
team = None | |
server = False | |
cameraConfigs = [] | |
"""Report parse error.""" | |
def parseError(str): | |
print("config error in '" + configFile + "': " + str, file=sys.stderr) | |
"""Read single camera configuration.""" | |
def readCameraConfig(config): | |
cam = CameraConfig() | |
# name | |
try: | |
cam.name = config["name"] | |
except KeyError: | |
parseError("could not read camera name") | |
return False | |
# path | |
try: | |
cam.path = config["path"] | |
except KeyError: | |
parseError("camera '{}': could not read path".format(cam.name)) | |
return False | |
cam.config = config | |
cameraConfigs.append(cam) | |
return True | |
"""Read configuration file.""" | |
def readConfig(): | |
global team | |
global server | |
# parse file | |
try: | |
with open(configFile, "rt") as f: | |
j = json.load(f) | |
except OSError as err: | |
print("could not open '{}': {}".format(configFile, err), file=sys.stderr) | |
return False | |
# top level must be an object | |
if not isinstance(j, dict): | |
parseError("must be JSON object") | |
return False | |
# team number | |
try: | |
team = j["team"] | |
except KeyError: | |
parseError("could not read team number") | |
return False | |
# ntmode (optional) | |
if "ntmode" in j: | |
str = j["ntmode"] | |
if str.lower() == "client": | |
server = False | |
elif str.lower() == "server": | |
server = True | |
else: | |
parseError("could not understand ntmode value '{}'".format(str)) | |
# cameras | |
try: | |
cameras = j["cameras"] | |
except KeyError: | |
parseError("could not read cameras") | |
return False | |
for camera in cameras: | |
if not readCameraConfig(camera): | |
return False | |
return True | |
"""Start running the camera.""" | |
def startCamera(config): | |
print("Starting camera '{}' on {}".format(config.name, config.path)) | |
cs = CameraServer.getInstance() | |
camera = cs.startAutomaticCapture(name=config.name, path=config.path) | |
camera.setConfigJson(json.dumps(config.config)) | |
return cs, camera | |
if __name__ == "__main__": | |
if len(sys.argv) >= 2: | |
configFile = sys.argv[1] | |
# read configuration | |
if not readConfig(): | |
sys.exit(1) | |
# start NetworkTables | |
ntinst = NetworkTablesInstance.getDefault() | |
#Name of network table - this is how it communicates with robot. IMPORTANT | |
networkTable = NetworkTables.getTable('ChickenVision') | |
if server: | |
print("Setting up NetworkTables server") | |
ntinst.startServer() | |
else: | |
print("Setting up NetworkTables client for team {}".format(team)) | |
ntinst.startClientTeam(team) | |
# start cameras | |
cameras = [] | |
streams = [] | |
for cameraConfig in cameraConfigs: | |
cs, cameraCapture = startCamera(cameraConfig) | |
streams.append(cs) | |
cameras.append(cameraCapture) | |
#Get the first camera | |
webcam = cameras[0] | |
cameraServer = streams[0] | |
#Start thread reading camera | |
cap = WebcamVideoStream(webcam, cameraServer, image_width, image_height).start() | |
# (optional) Setup a CvSource. This will send images back to the Dashboard | |
# Allocating new images is very expensive, always try to preallocate | |
img = np.zeros(shape=(image_height, image_width, 3), dtype=np.uint8) | |
#Start thread outputing stream | |
streamViewer = VideoShow(image_width,image_height, cameraServer, frame=img).start() | |
#cap.autoExpose=True; | |
tape = False | |
fps = FPS().start() | |
#TOTAL_FRAMES = 200; | |
# loop forever | |
while True: | |
# So whatever camera you want you just change 0 to 1 or 1 to 0 | |
# It default to the first (0th) camera | |
webcam = cameras[int(networkTable.getNumber("WhichCamera", 0))] | |
cameraServer = streams[int(networkTable.getNumber("WhichCamera", 0))] | |
# Sets video reader to read from new webcam and cameraServer | |
cap.webcam = webcam | |
cap.stream = cameraServer.getVideo(camera = webcam) | |
# 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. | |
timestamp, img = cap.read() | |
#Uncomment if camera is mounted upside down | |
#frame = flipImage(img) | |
#Comment out if camera is mounted upside down | |
frame = img | |
if timestamp == 0: | |
# Send the output the error. | |
streamViewer.notifyError(cap.getError()); | |
# skip the rest of the current iteration | |
continue | |
#Checks if you just want camera for driver (No processing), False by default | |
if(networkTable.getBoolean("Driver", False)): | |
cap.autoExpose = True | |
processed = frame | |
else: | |
# Checks if you just want camera for Tape processing , False by default | |
if(networkTable.getBoolean("Tape", True)): | |
#Lowers exposure to 0 | |
cap.autoExpose = False | |
boxBlur = blurImg(frame, green_blur) | |
threshold = threshold_video(lower_green, upper_green, boxBlur) | |
processed = findTargets(frame, threshold) | |
else: | |
# Checks if you just want camera for Cargo processing, by dent of everything else being false, true by default | |
cap.autoExpose = True | |
boxBlur = blurImg(frame, orange_blur) | |
threshold = threshold_video(lower_orange, upper_orange, boxBlur) | |
processed = findCargo(frame, threshold) | |
#Puts timestamp of camera on netowrk tables | |
networkTable.putNumber("VideoTimestamp", timestamp) | |
streamViewer.frame = processed | |
# update the FPS counter | |
fps.update() | |
#Flushes camera values to reduce latency | |
ntinst.flush() | |
#Doesn't do anything at the moment. You can easily get this working by indenting these three lines | |
# and setting while loop to: while fps._numFrames < TOTAL_FRAMES | |
fps.stop() | |
print("[INFO] elasped time: {:.2f}".format(fps.elapsed())) | |
print("[INFO] approx. FPS: {:.2f}".format(fps.fps())) | |
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