# or:
# 'videos\\traffic-cars.mp4'
video = cv2.VideoCapture('IMG_5567.mp4')
# Preparing variable for writer
# that we will use to write processed frames
writer = None
# Preparing variables for spatial dimensions of the frames
h, w = None, None
"""
End of:
Reading input video
"""
img_org = cv2.imread("IMG_5567.png")
markers = tools.find_markers(img_org)
corners, img_org = tools.sort_markers(markers, img_org)
"""
Start of:
Loading YOLO v3 network
"""
# Loading COCO class labels from file
# Opening file
# Pay attention! If you're using Windows, yours path might looks like:
# r'yolo-coco-data\coco.names'
# or:
# 'yolo-coco-data\\coco.names'
with open('coco.names') as f:
# Getting labels reading every line
# and putting them into the list
# Import .csv of location coordinates in EPSG 3857
corners_geo = pd.read_csv('./data/corners_3857.csv')
# Preparing variable for writer
# that we will use to write processed frames
writer = None
# Preparing variables for spatial dimensions of the frames
h, w = None, None
"""
End of:
Reading input video
"""
img_org = cv2.imread('./playground/media/video_corners.jpg')
markers = transf.find_markers(img_org)
corners, img_org = transf.sort_markers(markers, img_org)
"""
Start of:
Loading YOLO v3 network
"""
# Loading COCO class labels from file
# Opening file
# Pay attention! If you're using Windows, yours path might looks like:
# r'yolo-coco-data\coco.names'
# or:
# 'yolo-coco-data\\coco.names'
with open('./cfg/coco.names') as f:
# Getting labels reading every line
# and putting them into the list