# (left + round(1.5 * labelSize[0]), top + baseLine),(0, 255, 255), cv.FILLED)
cv.putText(img, label, (left, top),
cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1)
cv.imshow('camera', img)
t = time.time() - prev_time
print("FPS = %.2f , time=%.2fs" % (1 / t, t))
k = cv.waitKey(1)
if k == 27: # esc
ok = False
elif k == 32: # ' '
bPause = not bPause
cv.destroyAllWindows()
cap.release()
if __name__ == "__main__":
fClasses = "./mod/dark/tiny/tiny.names"
modelCfg = "./mod/dark/tiny/tiny.cfg"
modelWeights = "./mod/dark/tiny/tiny.weights"
# 初始化对象
yolo = yolo3.CV_Yolo3(fClasses, confThreshold=0.5, nmsThreshold=0.5)
print("Classes =", len(yolo3.Yolo3_Classes))
# 设置配置文件
yolo.cv_dnn_init(modelCfg, modelWeights)
openvideo(yolo, './img/v1.mp4')
# coding: utf-8
#
# 程序功能 ：调用 Yolo3 库，识别图片中的 object
import cv2 as cv
import numpy as np
import opencv_yolo3 as yolo3
import time
fClasses = "./mod/dark/coco/coco.names"
modelCfg = "./mod/dark/coco/coco.cfg"
modelWeights = "./mod/dark/coco/coco.weights"
# 初始化对象
bt = time.time()
yolo = yolo3.CV_Yolo3(fClasses)
print("Classes =", len(yolo3.Yolo3_Classes))
# 设置配置文件
yolo.cv_dnn_init(modelCfg, modelWeights)
t1 = time.time()
print("Time of Init Yolo :", t1 - bt)
image_path = "./img/jj001.jpg"
img = cv.imread(image_path)
dects, runtime = yolo.yolov3_predict(img) # 识别图片, 返回 对象集 和 运行时间
t2 = time.time()
print("Time of Detect Img :", t2 - t1)
#print(dects)
yolo3.Yolo3_ShowInfos(img, dects, runtime)