darknet_video.py File Reference

Namespaces
namespace	darknet_video

Functions
	darknet_video.check_arguments_errors (args)
	darknet_video.convert2original (image, bbox)
	darknet_video.convert2relative (bbox)
	darknet_video.convert4cropping (image, bbox)
	darknet_video.drawing (frame_queue, detections_queue, fps_queue)
	darknet_video.inference (darknet_image_queue, detections_queue, fps_queue)
	darknet_video.parse_args ()
	darknet_video.set_saved_video (input_video, output_video, size)
	darknet_video.signal_handler (sig, frame)
	darknet_video.str2int (video_path)
	darknet_video.video_capture (frame_queue, darknet_image_queue)

Variables
	darknet_video.args = parse_args()
	darknet_video.cap = cv2.VideoCapture(input_path)
	darknet_video.capture_thread = None
	darknet_video.class_colors = darknet.class_colors(class_names)
	darknet_video.class_names = open(args.data_file).read().splitlines()
	darknet_video.darknet_height = darknet.network_height(network)
	darknet_video.darknet_image_queue = Queue(maxsize=1)
	darknet_video.darknet_width = darknet.network_width(network)
	darknet_video.detections_queue = Queue(maxsize=1)
	darknet_video.drawing_thread = None
	darknet_video.fps_queue = Queue(maxsize=1)
int	darknet_video.frame_delay = 30
	darknet_video.frame_queue = Queue()
	darknet_video.inference_thread = None
	darknet_video.input_path = str2int(args.input)
bool	darknet_video.is_running = True
	darknet_video.network = darknet.load_net_custom(args.config_file.encode("ascii"), args.weights.encode("ascii"), 0, 1)
	darknet_video.video_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
	darknet_video.video_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))