def updateRobotPos():
global cte, x, y, theta, env
cap = WebcamVideoStream(src=int(sys.argv[1]))
cap.start()
print("Setting up...")
setupImgs = []
for i in range(15):
frame = cap.read()
setupImgs.append(frame)
time.sleep(0.1)
transformMatrix = setup(setupImgs)
while True:
frame = cap.read()
#print(frame[50:60, 50:60, 1])
x, y, theta, outImage = getRobotPosition(frame, transformMatrix)
print(x, y, theta)
print("")
cte = y
updateImage(outImage)
env.setRobotPose(x, y, theta)
m = env.visualizeMap()
updateImage2(m)
time.sleep(0.01)
def _detect(self):
"""Class function to detect faces and eyes within faces"""
video_stream = WebcamVideoStream()
video_stream.start()
# Cascade Classifiers
face_cascade = cv2.CascadeClassifier(
'haarcascades/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_eye.xml')
while True:
frame = video_stream.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Detecting faces and eyes
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
roi_gray = gray[y:y + h, x:x + h]
roi_color = frame[y:y + h, x:x + h]
eyes = eye_cascade.detectMultiScale(roi_gray)
if len(eyes) / len(faces) == 2:
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh),
(0, 255, 0), 1)
if cv2.waitKey(1) & 0xFF == ord('q'):
video_stream.stop()
break
# Display image
cv2.imshow('Image', frame)
def updateRobotPos():
global cte, x, y, theta, env
cap = WebcamVideoStream(src=int(sys.argv[1]))
cap.start()
print("Setting up...")
setupImgs = []
for i in range(15):
frame = cap.read()
setupImgs.append(frame)
time.sleep(0.1)
transformMatrix, reprojMatrix = setup(setupImgs)
while True:
frame = cap.read()
#print(frame[50:60, 50:60, 1])
x, y, theta, outImage = getRobotPosition(frame, transformMatrix)
print(x, y, theta)
print("")
cte = y
#updateImage(outImage)
env.setRobotPose(x, y, theta)
m = env.visualizeMap()
#out = cv2.warpPerspective(m, reprojMatrix, (outImage.shape[1], outImage.shape[0]))
#out = cv2.addWeighted(out, 0.5, outImage, 1 - 0.5, 0)
updateImage(outImage)
updateImage2(m)
time.sleep(0.01)
def updateRobotPos():
global x, y, theta, env, outImage, started, reprojMatrix, pp, frame, transformMatrix, initFinished
cap = WebcamVideoStream(src=int(sys.argv[1]))
cap.start()
print("Setting up...")
setupImgs = []
for i in range(15):
frame = cap.read()
setupImgs.append(frame)
time.sleep(0.1)
transformMatrix, reprojMatrix = setup(setupImgs)
initFinished = True
while True:
frame = cap.read()
x, y, theta, outImage = getRobotPosition(frame, transformMatrix)
env.setRobotPose(x, y, theta)
time.sleep(0.01)
class VideoStream:
def __init__(self,
src=1,
usePiCamera=False,
resolution=(320, 240),
framerate=32):
# check to see if the picamera module should be used
if usePiCamera:
# only import the picamera packages unless we are
# explicity told to do so -- this helps remove the
# requirement of `picamera[array]` from desktops or
# laptops that still want to use the `imutils` package
from pivideostream import PiVideoStream
# initialize the picamera stream and allow the camera
# sensor to warmup
self.stream = PiVideoStream(resolution=resolution,
framerate=framerate)
# otherwise, we are using OpenCV so initialize the webcam
# stream
else:
self.stream = WebcamVideoStream(src=src)
def start(self):
# start the threaded video stream
return self.stream.start()
def update(self):
# grab the next frame from the stream
self.stream.update()
def read(self):
# return the current frame
return self.stream.read()
def stop(self):
# stop the thread and release any resources
self.stream.stop()
def main():
#Select Webcam to Stream from
vs = WebcamVideoStream(0)
vs.start()
#Initialize Config for tesseract
#tesconfigargs = ('-l digits --psm 10')
tesconfigargs = '--oem 0 -c tessedit_char_whitelist=0123456789-. --psm 10'
#Set pytesseract CMD (Windows only)
pytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files (x86)\\Tesseract-OCR\\tesseract.exe'
#Instanciate Logger
setup_logger('log', r'C:\Temp\ImageAnalysis.csv')
log = logging.getLogger('log')
log.info("-------------------------------------Capture started----------------------------------------------")
while True:
frame = vs.read()
cv2.imshow('frame', frame)
#Color to GrayScale Filter
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#small Gaussian Blur Filter to filter out grainy Stuff
gauss = cv2.GaussianBlur(gray, (5,5),0)
#canny detector
canny = cv2.Canny(gauss,100,200)
cv2.imshow('canny', canny)
_, cnts, _= cv2.findContours(canny, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = sorted(cnts, key = cv2.contourArea, reverse = True)[:10]
## loop over our contours
screenCnt = None
for c in cnts:
if cv2.contourArea(c) > 1000:
#approximate the contour
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.02 * peri, True)
#if our approximated contour has four points, then
#we can assume that we have found our screen
if len(approx) == 4:
screenCnt = approx
cv2.drawContours(frame, [screenCnt], -1, (0, 255, 0), 3)
x,y,width,height = cv2.boundingRect(screenCnt)
croppedframe = frame[y: y + height , x: x + width] # both opencv and numpy are "row-major", so y goes first
digit = pytesseract.image_to_string(croppedframe, config=tesconfigargs)
# Print and Log recognized text
log.info(digit)
break
cv2.imshow('frame', frame)
key = cv2.waitKey(5) & 0xFF
if key == 27:
break
#Do Cleanup
vs.stop()
cv2.destroyAllWindows()
from WebcamVideoStream import WebcamVideoStream
import pytesseract
import cv2
import numpy as np
print("[INFO] Starting Video Stream")
vs = WebcamVideoStream()
vs.start()
#time.sleep(2)
#Initialize Config for tesseract
#'-l eng Define the english wordfile
#config = ('-l eng')
config = ('-l digits --psm 10')
while True:
frame = vs.read()
#Color to GrayScale Filter
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
## # cv2.imshow("Region Captured", frame)
## # cv2.imshow("Region Captured", frame)
#cv2.imshow('gray', gray)
#small Gaussian Blur Filter to filter out grainy Stuff
gauss = cv2.GaussianBlur(gray, (5, 5), 0)
#cv2.imshow('gauss', gauss)
#canny detector
#option, threshold1, threshold2
canny = cv2.Canny(gauss, 100, 200)
#canny = cv2.Canny(gauss,lower,upper)
