def getContours(img):
#retrieves extreme outer contours
contours, hierarchy = cv2.findContours(img, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_NONE)[-2:]
for cnt in contours:
area = cv2.contourArea(cnt)
print(area)
if area > 10:
cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
peri = cv2.arcLength(cnt, True)
print(peri)
approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
print(len(approx))
objCor = len(approx)
x, y, w, h = cv2.boundingRect(approx)
if objCor == 3: objectType = "Tri"
elif objCor == 4:
aspRatio = w / float(h)
if aspRatio > 0.95 and aspRatio < 1.05: objectType = "Square"
else: objectType = "Rectangle"
elif objCor > 4: objectType = "Circle"
else: objectType = "None"
#draw rectangles on objects
cv2.rectangle(imgContour, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(imgContour, objectType,
(x + (w // 2) - 10, y + (h // 2) - 10),
cv2.FONT_HERSHEY_COMPLEX, 0.8, (0, 0, 0), 2)
imgCanny = cv2.Canny(img, 50, 50)
imgStack = stck.stackImages(0.6, ([img, imgCanny], [thresh, thresh]))
cv2.imshow("Stacked", imgStack)
g_min = cv2.getTrackbarPos("Gray min", "Trackbars")
g_max = cv2.getTrackbarPos("Gray max", "Trackbars")
a_len = cv2.getTrackbarPos("Arc len", "Trackbars")
a_len = a_len / 10000
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
ret, thresh = cv2.threshold(blurred, g_min, g_max, cv2.THRESH_BINARY_INV)
ret, thresh1 = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
ret, thresh2 = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
ret, thresh3 = cv2.threshold(gray, 127, 255, cv2.THRESH_TRUNC)
ret, thresh4 = cv2.threshold(gray, 127, 255, cv2.THRESH_TOZERO)
ret, thresh5 = cv2.threshold(gray, 127, 255, cv2.THRESH_TOZERO_INV)
test = cv2.bitwise_or(thresh, thresh1)
#res1 = cv2.bitwise_and(frame,frame,mask=thresh)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
for contour in contours:
approx = cv2.approxPolyDP(contour,
a_len * cv2.arcLength(contour, True), True)
cv2.drawContours(frame, [approx], -1, (0, 0, 255), 3)
imgStack = stack.stackImages(0.2, ([
test,
thresh,
], [thresh2, thresh3], [thresh4, thresh5]))
cv2.imshow("Stacked", imgStack)
key = cv2.waitKey(1)
if key == 27: #esc
cv2.destroyAllWindows()
break
#TODO: Look up explanation approx.ravel, get coordinates contour
x = approx.ravel()[0]
y = approx.ravel()[1]
#print(len(approx))
# Write X and Y coordinates to detected object
if len(approx) >= 150:
XandY = str(x) + ", " + str(y)
cv2.putText(frame, XandY, (x, y), font, 2, (0, 0, 255))
#Video
#cv2.imshow("Frame", frame)
#cv2.imshow("Mask",mask)
#if pic
#imgResult = cv2.bitwise_and(cap,cap,mask=mask)
#Stack images, just for convenience
imgStack = stck.stackImages(0.6, ([frame, gray, thresh]))
cv2.imshow("Stacked", imgStack)
process = psutil.Process(os.getpid())
memory = process.memory_info().rss * pow(10, -6)
print("%0.2f" % memory) # in bytes
key = cv2.waitKey(1)
if key == 27: #esc
break
cap.release()
cv2.destroyAllWindows()
frame = cv2.imread("txt.png")
cv2.namedWindow("Stacked", cv2.WINDOW_NORMAL)
while True:
g_min = cv2.getTrackbarPos("Gray min", "Trackbars")
g_max = cv2.getTrackbarPos("Gray max", "Trackbars")
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
ret, thresh = cv2.threshold(blurred, g_min, g_max, cv2.THRESH_BINARY)
hFrame, wFrame, _ = frame.shape
#['m', '221', '282', '237', '293', '0'], ['text','x','y','width','height']
#boxes = pytesseract.image_to_boxes(frame)
boxes = pytesseract.image_to_data(frame)
#print(boxes)
#print(boxes)
for b in boxes.splitlines():
b = b.split(' ')
x, y, w, h = int(b[1]), int(b[2]), int(b[3]), int(b[4])
cv2.rectangle(frame, (x, hFrame - y), (w, hFrame - h), (0, 0, 255), 1)
cv2.putText(frame, b[0], (x, hFrame - y + 125),
cv2.FONT_HERSHEY_COMPLEX, 0.5, (50, 50, 255), 1)
imgStack = stack.stackImages(1, ([frame, frame], [thresh, thresh]))
while True:
cv2.imshow("Stacked", imgStack)
key = cv2.waitKey(1)
if key == 27: #esc
exit()
#while True:
if command == 'y':
cap = opencamera()
_, frame = cap.read()
#frame = cap.read()
g_min = cv2.getTrackbarPos("Gray min", "Trackbars")
g_max = cv2.getTrackbarPos("Gray max", "Trackbars")
MaskedFrame = FrameMasking(frame, g_min, g_max)
hFrame, wFrame, _ = frame.shape
frame = MaskedFrame
boxes = pytesseract.image_to_boxes(frame)
for b in boxes.splitlines():
b = b.split(' ')
print(b[0][0])
#print(b)
#all strings -> int
x,y,w,h = int(b[1]), int(b[2]), int(b[3]), int(b[4])
cv2.rectangle(frame,(x,hFrame-y),(w,hFrame-h),(0,0,255),1)
cv2.putText(frame, b[0], (x, hFrame-y+125), cv2.FONT_HERSHEY_COMPLEX, 0.5, (50,50,255),1)
while True:
imgStack = stack.stackImages(0.5,([frame,frame],[MaskedFrame,MaskedFrame]))
cv2.imshow("Stacked", imgStack)
key = cv2.waitKey(1)
if key == 27:
print("break")
cap.release()
break
##calculate difference between center and predefined dot
#print(centers[0])
temp = centers[0]
xCenter = temp[0]
yCenter = temp[1]
#distance = math.sqrt((math.pow(xCenter,2)-math.pow(320,2))+(math.pow(yCenter,2)-0))
distance = math.sqrt(
math.pow(xCenter - 480, 2) + math.pow(yCenter - 0, 2))
cv2.putText(frame, str(distance), (25, 25),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0))
#D = np.linalg.norm(cx-cy)
#print(D)
"""
x,y,w,h = cv2.boundingRect(img)
cv2.rectangle(mask,(x,y),(x+w,y+h),(0,255,0),2)
plt.imshow(frame)
print("Distances: vertical: %d, horizontal: %d" % (h,w))
"""
#a = cv2.magnitude(centers[0],centers[1], 2)
#print(a)
imgStack = stck.stackImages(0.5, ([frame, thresh, maskerode, maskerode], [
maskrange, frame, frame, frame
], [maskerode, maskdilation, maskopen, maskclose]))
#imgStack = stck.stackImages(0.9,([frame,maskerode,maskdilation],[maskopen,maskclose,frame]))
cv2.imshow("Stacked", imgStack)
key = cv2.waitKey(1)
if key == 27: #esc
break
aspRatio = w / float(h)
if aspRatio > 0.95 and aspRatio < 1.05: objectType = "Square"
else: objectType = "Rectangle"
elif objCor > 4: objectType = "Circle"
else: objectType = "None"
#draw rectangles on objects
cv2.rectangle(imgContour, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(imgContour, objectType,
(x + (w // 2) - 10, y + (h // 2) - 10),
cv2.FONT_HERSHEY_COMPLEX, 0.8, (0, 0, 0), 2)
cap = cv2.VideoCapture(0)
while True:
_, img = cap.read()
imgContour = img.copy()
imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
imgblur = cv2.GaussianBlur(imgGray, (7, 7), 1)
#canny corners
imgCanny = cv2.Canny(imgblur, 50, 50)
getContours(imgCanny)
k = cv2.waitKey(1) & 0xFF
imgBlank = np.zeros_like(img)
imgStack = stck.stackImages(
0.6, ([img, imgGray, imgblur], [imgCanny, imgContour, imgBlank]))
cv2.imshow("Stacked", imgStack)
if k == ord('q'):
break