example Namespace Reference

Variables
str	cfg_file = "../cfg/yolov4-tiny.cfg"
	class_names = open(names_file).read().splitlines()
	colours = darknet.class_colors(class_names)
	darknet_image = darknet.make_image(width, height, 3)
	detections = darknet.detect_image(network, class_names, darknet_image, thresh=prediction_threshold)
	height = darknet.network_height(network)
	image_bgr = cv2.imread(filename)
	image_resized = cv2.resize(image_rgb, (width, height), interpolation=cv2.INTER_LINEAR)
	image_rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)
	image_with_boxes = darknet.draw_boxes(detections, image_resized, colours)
str	log_file = "output.log"
str	names_file = "../cfg/coco.names"
	network = darknet.load_net_custom(cfg_file.encode("ascii"), weights_file.encode("ascii"), 0, 1)
float	prediction_threshold = 0.5
str	weights_file = "../yolov4-tiny.weights"
	width = darknet.network_width(network)

Detailed Description

This is EXAMPLE python code showing how to use the Python darknet module.
It is NOT a final application!  You must modify this example to make it do what you need.

Variable Documentation

cfg_file

str example.cfg_file = "../cfg/yolov4-tiny.cfg"

class_names

example.class_names = open(names_file).read().splitlines()

colours

example.colours = darknet.class_colors(class_names)

darknet_image

example.darknet_image = darknet.make_image(width, height, 3)

detections

example.detections = darknet.detect_image(network, class_names, darknet_image, thresh=prediction_threshold)

height

example.height = darknet.network_height(network)

image_bgr

example.image_bgr = cv2.imread(filename)

image_resized

example.image_resized = cv2.resize(image_rgb, (width, height), interpolation=cv2.INTER_LINEAR)

image_rgb

example.image_rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)

image_with_boxes

example.image_with_boxes = darknet.draw_boxes(detections, image_resized, colours)

log_file

str example.log_file = "output.log"

names_file

str example.names_file = "../cfg/coco.names"

network

example.network = darknet.load_net_custom(cfg_file.encode("ascii"), weights_file.encode("ascii"), 0, 1)

prediction_threshold

float example.prediction_threshold = 0.5

weights_file

str example.weights_file = "../yolov4-tiny.weights"

width

example.width = darknet.network_width(network)