def main():
""" Main entry point of the app """
usr_input = input(
'Select the Video\n\t1. Tag0 \n\t2. Tag1 \n\t3. Tag2 \n\t4. multipleTags\n\nYour Choice: '
)
print(getVideoFile(int(usr_input)))
cap = cv2.VideoCapture(getVideoFile(int(usr_input)))
font = cv2.FONT_HERSHEY_SIMPLEX
Xc = np.array([[0, 0], [511, 0], [511, 511], [0, 511]])
while (cap.isOpened()):
ret, frame = cap.read()
if frame is not None:
cv2.imshow('Normal', frame)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
corner_points_temp, dst_total, frame = getCornerPoints(frame)
for tag_no in range(0, (len(corner_points_temp))):
corner_points = corner_points_temp[0]
H = homographicTransform(corner_points, Xc)
h_inv = np.linalg.inv(H)
transformed_image = getTransfomredImage(h_inv, gray, 512)
ID_val, rotations = decode(transformed_image)
temp = frame
frame = superImpose(h_inv, temp, rotations + 1)
cv2.imshow('Superimposed', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
cap.release()
cv2.destroyAllWindows()
def main():
""" Main entry point of the app """
usr_input = input(
'Select the Video\n\t1. Tag0 \n\t2. Tag1 \n\t3. Tag2 \n\t4. multipleTags\n\nYour Choice: ')
print(getVideoFile(int(usr_input)))
cap = cv2.VideoCapture(getVideoFile(int(usr_input)))
font = cv2.FONT_HERSHEY_SIMPLEX
Xc = np.array([[0, 0], [0, 199], [199, 199], [199, 0]])
while(cap.isOpened()):
ret, frame = cap.read()
if frame is not None:
frame = np.array(frame, dtype=np.uint8)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
corner_points_temp, dst_total, frame = getCornerPoints(frame)
for tag_no in range(0, (len(corner_points_temp))):
corner_points = corner_points_temp[0]
H = homographicTransform(corner_points, Xc)
h_inv = np.linalg.inv(H)
transformed_image = getTransfomredImage(h_inv, gray,200)
ID_val,rotation = decode(transformed_image)
cv2.imshow('transformed_image',transformed_image)
cv2.putText(frame,'Tag ' + str(tag_no + 1) + ' value: ' + str(ID_val),(10,100 + 50*tag_no), font, 2, (200,255,155), 2, cv2.LINE_AA)
frame[dst_total>0.01*dst_total.max()]=[0,0,255]
cv2.imshow('Harris corner detector', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
cap.release()
cv2.destroyAllWindows()
def main():
""" Main entry point of the app """
cap = cv2.VideoCapture('Tag1.mp4')
while (cap.isOpened()):
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
ret, thresh = cv2.threshold(gray, 240, 255, 0, cv2.THRESH_BINARY)
contours, heirarchy = cv2.findContours(thresh, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
contour_sizes = [(cv2.contourArea(contour), contour)
for contour in contours]
biggest_contour = max(contour_sizes, key=lambda x: x[0])[1]
dst_total = np.zeros(gray.shape, dtype='uint8')
heirarchy = heirarchy[0]
corner_idx_temp = np.zeros((4, 1))
corner_idx = np.zeros((1, 1))
corner_points = np.zeros((1, 2))
for component in zip(contours, heirarchy):
currentHierarchy = component[1]
currentContour = component[0]
size = cv2.minAreaRect(component[0])
isSecond = 0
idx = currentHierarchy[3]
while True:
if idx == -1:
break
isSecond = isSecond + 1
idx = heirarchy[idx][3]
if isSecond == 1:
gray_fl = np.float32(gray)
mask = np.zeros(gray_fl.shape, dtype='uint8')
mask = cv2.GaussianBlur(mask, (3, 3), 0)
cv2.fillPoly(mask, [currentContour], (255, 255, 255))
dst = cv2.cornerHarris(mask, 5, 3, 0.04)
dst = cv2.dilate(dst, None)
ret, dst = cv2.threshold(dst, 0.1 * dst.max(), 255, 0)
dst = np.uint8(dst)
cv2.drawContours(frame, [currentContour], -1, (0, 255, 0), 3)
ret, labels, stats, centroids = cv2.connectedComponentsWithStats(
dst)
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,
100, 0.001)
corners = cv2.cornerSubPix(gray_fl, np.float32(centroids),
(5, 5), (-1, -1), criteria)
dst_total = dst + dst_total
corners = np.delete(corners, (0), axis=0)
print(corners)
if (len(corners) < 4):
break
#corner_idx_temp = sortCorners(corners)
#corners = np.delete(corners, np.setdiff1d(np.arange(len(corners)), corner_idx_temp), axis = 0)
corners = sortCorners(corners)
corner_points = np.concatenate((corner_points, corners),
axis=0)
#corner_idx = np.concatenate((corner_idx, corner_idx_temp), axis = 0)
#corner_idx = np.delete(corner_idx, (0), axis=0)
corner_points = np.delete(corner_points, (0), axis=0)
#corner_idx = np.rint(corner_idx)
#corner_idx = corner_idx.astype(int)
corner_points = (np.rint(corner_points)).astype(int)
#print('corner')
#print(corner_idx)
print('corner_points')
print(corner_points)
total_tags = np.int(len(corner_points) / 4)
print('total_tags')
print(total_tags)
for tag_no in range(0, total_tags):
#print('inside each tag')
#print((corner_points[4*tag_no:4*tag_no+4][:]) )
#print((corner_idx[4*tag_no:4*tag_no+4]))
H = homographicTransform(
corner_points[4 * tag_no:4 * tag_no +
4][:]) #,(corner_idx[4*tag_no:4*tag_no+4]))
transformed_image = np.zeros((200, 200), dtype='uint8')
h_inv = np.linalg.inv(H)
for row in range(0, 200):
for col in range(0, 200):
X_dash = np.array([col, row, 1]).T
X = np.matmul(h_inv, X_dash)
X = (X / X[2])
X = X.astype(int)
transformed_image[col][row] = gray[X[1]][X[0]]
#cv2.imshow('QR_image',transformed_image)
ID_val = decode(transformed_image)
print(ID_val)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
frame_modi = frame
frame_modi[dst_total > 0.01 * dst_total.max()] = [0, 0, 255]
cv2.imshow('Harris corner detector', frame_modi)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()