實用筆記系列2

• 獲取圖片Exif旋轉信息並旋轉圖片

  import cv2
  from PIL import Image, ExifTags
  def img_ratation(image, angle):
      # grab the dimensions of the image and then determine the
      # center
      (h, w) = image.shape[:2]
      (cX, cY) = (w // 2, h // 2)
      # grab the rotation matrix (applying the negative of the
      # angle to rotate clockwise), then grab the sine and cosine
      # (i.e., the rotation components of the matrix)
      M = cv2.getRotationMatrix2D((cX, cY), -angle, 1.0)
      cos = np.abs(M[0, 0])
      sin = np.abs(M[0, 1])
      # compute the new bounding dimensions of the image
      nW = int((h * sin) + (w * cos))
      nH = int((h * cos) + (w * sin))
      # adjust the rotation matrix to take into account translation
      M[0, 2] += (nW / 2) - cX
      M[1, 2] += (nH / 2) - cY
      # perform the actual rotation and return the image
      return cv2.warpAffine(image, M, (nW, nH))
      
  def img_rotation_correction(fpath):
      angle = None
      cv_img = None
      try:
          img = Image.open(fpath)
          for orientation in ExifTags.TAGS.keys() : 
              if ExifTags.TAGS[orientation]=='Orientation' : 
              	break
              	
          exif=dict(img._getexif().items())
          if exif[orientation] == 3 : # 180
              angle = 180
          elif exif[orientation] == 6 : # 90°
              angle = 270
          elif exif[orientation] == 8 : # -90°
              angle = 90
      except Exception as e:
          print(f"{e}")
      else:
          cv_img = cv2.imread(fpath)
          cv_img = img_ratation(cv_img, angle)
          return cv_img