我正在尝试从实时图像馈送(网络摄像头)生成灰度运动历史图像,以供我构建的CNN模型处理,从UpdateEmotionHistory函数我得到以下输出:
[width x height] array of type np.float32
我想把这个数组转换成灰度图像,运动中的变化越亮like this
编辑:下面添加了代码示例
import cv2
import numpy as np
import time
import genMHI_util
cap = cv2.VideoCapture(0)
fgbg = cv2.createBackgroundSubtractorMOG2(history=1000,detectShadows=False)
colourThreshold = 0.975
frame_reduction_counter = 0
mhi = np.zeros((genMHI_util.MHI_WIDTH, genMHI_util.MHI_HEIGHT), np.float32)
while True:
ret, frame = cap.read()
# kernel = np.ones((5, 5), np.float32) / 25
# frame = cv2.medianBlur(frame, 5)
# frame = cv2.filter2D(frame, -1, kernel) # Blur image
if frame_reduction_counter >= 0:
# Disregarding frames that do not contain enough movement, below the set threshold
frame_reduction_counter = 0
timestamp = cv2.getTickCount() / cv2.getTickFrequency()
# Do background subtraction on frame to get silhouette
silhouette = fgbg.apply(frame)
silhouette = cv2.resize(silhouette, (genMHI_util.MHI_WIDTH, genMHI_util.MHI_HEIGHT))
# Update MHI
cv2.motempl.updateMotionHistory(silhouette, mhi, timestamp, 0.5)
# Do something with 'mhi' object (300x300 float array) ?
# Convert float array to int
mask = cv2.convertScaleAbs(mhi,
alpha=(255 / genMHI_util.MHI_DURATION),
beta=((genMHI_util.MHI_DURATION - timestamp) * 255 / genMHI_util.MHI_DURATION))
# Preview images
cv2.imshow('original', frame)
cv2.imshow('silhouette', silhouette)
cv2.imshow('mhi', mask)
cv2.waitKey(1)
frame_reduction_counter += 1
cap.release()
cv2.destroyAllWindows()
常数:
MHI_DURATION = 5
MHI_WIDTH = 300
MHI_HEIGHT = 300
目前没有回答
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