前言
模式识别视觉基础(视频处理知识) OpenCV应用
python 3.6+
安装组件
pip install matplotlib numpy opencv-python pillow
要求:
从网上下载或自己手机录制一段视频(>30秒),第0-5秒显示一句话的字幕,第6-15秒显示另一句话的字幕。
第20秒开始从屏幕中心出现一个光点,发出眩光,逐渐扩大覆盖的整个屏幕(类似太阳),最后光点缩小复原,整个过程10秒。
一、代码实现
import cv2
import math
import numpy as np
org_video = "Screen-univers.mp4"
sub_video = "Screenrecorder_U.mp4"
# Define the codec and create VideoWriter object
cap = cv2.VideoCapture(org_video) # 读取视频
fps_video = cap.get(cv2.CAP_PROP_FPS)# 获取视频帧率
fourcc = cv2.VideoWriter_fourcc(*"mp4v")# 设置写入视频的编码格式
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))# 获取视频宽度
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))# 获取视频高度
videoWriter = cv2.VideoWriter(sub_video, fourcc, fps_video, (width, height))#保存视频
text1='The scenery is infinitely good'
text2='And things need to be done early !'
def show_text(img,text,word_x):
word_y = int(height) - 80
position=(word_x, word_y)
font=cv2.FONT_HERSHEY_SIMPLEX
font_size= 3
color=(0, 0, 255)
A = 3
return cv2.putText(img, text, position, font, font_size, color, A)
def show_glare(img,time,count):
# 设置中心点
centerX = height / 2
centerY = width / 2
radius = int(((height/2)/time)*count)
# 设置光照强度
strength = 200
# 图像光照特效
for i in range(height):
for j in range(width):
# 计算当前点到光照中心距离(平面坐标系中两点之间的距离)
distance = math.pow((centerY - j), 2) + math.pow((centerX - i), 2)
# 获取原始图像
B = img[i, j][0]
G = img[i, j][1]
R = img[i, j][2]
if (distance < radius * radius):
# 按照距离大小计算增强的光照值
result = (int)(strength * (1.0 - math.sqrt(distance) / radius))
B = img[i, j][0] + result
G = img[i, j][1] + result
R = img[i, j][2] + result
# 判断边界 防止越界
B = min(255, max(0, B))
G = min(255, max(0, G))
R = min(255, max(0, R))
img[i, j] = np.uint8((B, G, R))
else:
img[i, j] = np.uint8((B, G, R))
glare_time = int(fps_video*5)-1
glare_count = 0
frame_id = 0
while (cap.isOpened()):
ret, frame = cap.read()
if ret == True:
frame_id +=1
time_s = int(frame_id / fps_video)
if (0 < time_s <= 5):
show_text(frame,text1,500)
elif (6 < time_s <= 15):
show_text(frame,text2,350)
elif (20 < time_s <= 25):
glare_count += 1
show_glare(frame,glare_time,glare_count)
elif (25 < time_s <= 30):
glare_count -= 1
show_glare(frame,glare_time,glare_count)
videoWriter.write(frame)
else:
break
# Release everything if job is finished
cap.release()
videoWriter.release()
cv2.destroyAllWindows()
二、结果展示
参考链接:
https://blog.csdn.net/weixin_45861496/article/details/124224815?spm=1001.2014.3001.5502