openCV - 2

在這個章節我們將介紹如何運用樹莓派所外接的攝影機，包括如何擷取相片、如何錄影、如何將錄影的資料寫到檔案當中。也介紹如何從檔案當中讀取影片，再將影片分析，例如從影片中篩選出變動程度大於門檻值的區域。

  1. 從攝影機擷取一張影像

    2. cap = cv2.VideoCapture(0)
    ret, frame = cap.read() 
    import cv2
# 選擇第1隻攝影機
cap = cv2.VideoCapture(0)
# 從攝影機擷取一張影像
ret, frame = cap.read()
# 在圖片上畫一條紅色的對角線，寬度為 5 px
cv2.line(frame, (0, 0), (255, 255), (0, 255, 255), 5)
# 寫入圖檔
cv2.imwrite("oc01.png", frame)
cv2.imshow('frame',frame)
if cv2.waitKey(6000) & 0xFF == ord('q'): pass
# 釋放攝影機
cap.release()
cv2.destroyAllWindows()

  2. 從攝影機擷取一張影像+矩形框圖

    3. cap = cv2.VideoCapture(0)
    ret, frame = cap.read() 
    import numpy as np
import cv2

cap = cv2.VideoCapture(0)
ret, frame = cap.read()
cv2.line(frame, (0, 0), (255, 255), (0, 255, 255), 5)
cv2.imwrite("YCC_1.png", frame)
cv2.imshow('frame',frame)
if cv2.waitKey(2000) & 0xFF == ord('q'): pass
cap.release()
cv2.destroyAllWindows()


for i in range(10):
    x1=50+50*i; x2=x1+100
    y1=200; y2=300
    print(i,(x1,y1),(x2,y2))
    img=np.copy(frame)
    cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2)
    cv2.imshow('img',img)
    if cv2.waitKey(3000) & 0xFF == ord('q'): break
cv2.destroyAllWindows()

  3. 設定/取得擷取影像的尺寸大小 

    4. import cv2
cap = cv2.VideoCapture(0)
# 設定擷取影像的尺寸大小
# 800x600, 1024x768, 1280x720(HD720), 1920x1080(HD1080)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)

def decode_fourcc(v):
    v = int(v)
    return "".join([chr((v >> 8 * i) & 0xFF) for i in range(4)])

# 取得影像的尺寸大小
w = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
h = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
print("Image Size: %d x %d" % (w, h))
# 取得 Codec 名稱
fourcc = cap.get(cv2.CAP_PROP_FOURCC)
codec = decode_fourcc(fourcc)
print("Codec: " + codec)
cap.release()

    Image Size: 1280 x 720
Codec: YUYV


  4. 開啟影片檔案並且播放

    5. firework-2.mp4
    
import cv2
cap = cv2.VideoCapture('firework-2.mp4')
while(cap.isOpened()):
    ret, frame = cap.read()
    if(ret==False): break
    cv2.imshow('frame',frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()
print('cv2 done')


  5. 從檔案讀進一個影片，再將影片改為灰階後另存為一個新的影片檔案 

    6. import cv2
cap = cv2.VideoCapture('firework-2.mp4')
# 取得影像的尺寸大小
w = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
h = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
# 記得長寬要先改成整數
print(type(w)); w=int(w); h=int(h)
print("Image Size: %d x %d" % (w, h))
# 使用 XVID 編碼
fourcc = cv2.VideoWriter_fourcc(*'XVID')
# FPS 值為 20.0，解析度為 w x h
# 要寫成灰階輸出的檔案必須在長寬(w,h)之後加個零 ,0)
out = cv2.VideoWriter('oc04d.mp4', fourcc, 20.0, (w,h),0)
while(cap.isOpened()):
  ret, frame = cap.read()
  if ret == True:
    # 轉為灰階並寫入
    frame2 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    out.write(frame2)
    cv2.imshow('frame',frame2)
    if cv2.waitKey(1) & 0xFF == ord('q'):
      break
  else:
    break
# 釋放所有資源
cap.release()
out.release()
cv2.destroyAllWindows()


  6. 從攝影機擷取影像並使用imshow

    7. import cv2
cap = cv2.VideoCapture(0)
t=0
while(t<500 and cap.isOpened()):
    ret, frame = cap.read()
    if cv2.waitKey(1) & 0xFF == ord('q'): break
    cv2.imshow('frame',frame)
    t+=1
    if(t%100==0): print(t)
cap.release()
cv2.destroyAllWindows()


  7. 從攝影機擷取影像/video影片儲存寫入檔案

    8. import cv2
cap = cv2.VideoCapture(0)
# 設定擷取影像的尺寸大小
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 360)
# 使用 XVID 編碼
fourcc = cv2.VideoWriter_fourcc(*'XVID')
# 建立 VideoWriter 物件，輸出影片至 output.avi
# FPS 值為 20.0，解析度為 640x360
out = cv2.VideoWriter('cam_1.mp4', fourcc, 20.0, (640, 360))
t=0
while(t<200 and cap.isOpened()):
  if(t%50 == 0): print(t)
  ret, frame = cap.read()
  t+=1
  if ret == True:
    out.write(frame)
    cv2.imshow('frame',frame)
    if cv2.waitKey(1) & 0xFF == ord('q'): break
  else: break
# 釋放所有資源
cap.release()
out.release()
cv2.destroyAllWindows()


  8. 快速篩選監視器影像

    9. import cv2
import numpy as np
import os

# 影片檔案
videoFile = "op4B.avi"
# 輸出目錄
outputFolder = "my_output"
# 自動建立目錄
if not os.path.exists(outputFolder):
  os.makedirs(outputFolder)
# 開啟影片檔
cap = cv2.VideoCapture(videoFile)
# 取得畫面尺寸
width = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
height = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
# 計算畫面面積
area = width * height
# 初始化平均畫面
ret, frame = cap.read()
avg = cv2.blur(frame, (4, 4))
avg_float = np.float32(avg)
# 輸出圖檔用的計數器
outputCounter = 0
while(cap.isOpened()):
  # 讀取一幅影格
  ret, frame = cap.read()
  # 若讀取至影片結尾，則跳出
  if ret == False:
    break
  # 模糊處理
  blur = cv2.blur(frame, (4, 4))
  # 計算目前影格與平均影像的差異值
  diff = cv2.absdiff(avg, blur)
  # 將圖片轉為灰階
  gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
  # 篩選出變動程度大於門檻值的區域
  ret, thresh = cv2.threshold(gray, 25, 255, cv2.THRESH_BINARY)
  # 使用型態轉換函數去除雜訊
  kernel = np.ones((5, 5), np.uint8)
  thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)
  thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=2)
  # 產生等高線
  cntImg, cnts, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  hasMotion = False
  for c in cnts:
    # 忽略太小的區域
    if cv2.contourArea(c) < 2500:
      continue
    hasMotion = True
    # 計算等高線的外框範圍
    (x, y, w, h) = cv2.boundingRect(c)
    # 畫出外框
    cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
  if hasMotion:
    # 儲存有變動的影像
    cv2.imwrite("%s/output_%04d.jpg" % (outputFolder, outputCounter), frame)
    outputCounter += 1
  # 更新平均影像
  cv2.accumulateWeighted(blur, avg_float, 0.01)
  avg = cv2.convertScaleAbs(avg_float)
cap.release()