def img2strimg(frame, K=5):  
  if type(frame) != np.ndarray:
    frame = np.array(frame)
  height, width, *_ = frame.shape 
  frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
  frame_array = np.float32(frame_gray.reshape(-1))
  criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
  flags = cv2.KMEANS_RANDOM_CENTERS
  # 得到 labels(类别)、centroids(矩心)
  compactness, labels, centroids = cv2.kmeans(frame_array, K, None, criteria, 10, flags)
  centroids = np.uint8(centroids)
  # labels 的数个矩心以随机顺序排列，所以需要简单处理矩心
  centroids = centroids.flatten()
  centroids_sorted = sorted(centroids)
  # 获得不同 centroids 的明暗程度，0 为最暗
  centroids_index = np.array([centroids_sorted.index(value) for value in centroids])
  bright = [abs((3 * i - 2 * K) / (3 * K)) for i in range(1, 1 + K)]
  bright_bound = bright.index(np.min(bright))
  shadow = [abs((3 * i - K) / (3 * K)) for i in range(1, 1 + K)]
  shadow_bound = shadow.index(np.min(shadow))
  labels = labels.flatten()
  # 将 labels 转变为实际的明暗程度列表
  labels = centroids_index[labels]
  # 解析列表
  labels_picked = [labels[rows * width:(rows + 1) * width:2] for rows in range(0, height, 2)]
  canvas = np.zeros((3 * height, 3 * width, 3), np.uint8)
	# 创建长宽为原图三倍的白色画布
  canvas.fill(255)
  y = 8
  for rows in labels_picked:
    x = 0
    for cols in rows:
      if cols <= shadow_bound:
        cv2.putText(canvas, str(random.randint(2, 9)),
              (x, y), cv2.FONT_HERSHEY_PLAIN, 0.45, 1)
      elif cols <= bright_bound:
        cv2.putText(canvas, "-", (x, y),
              cv2.FONT_HERSHEY_PLAIN, 0.4, 0, 1)
      x += 6
    y += 6
  return canvas

# 拆分 gif 将每一帧处理成字符画
def gif2pic(file, ascii_chars, isgray, font, scale):
  '''
  file: gif 文件
  ascii_chars: 灰度值对应的字符串
  isgray: 是否黑白
  font: ImageFont 对象
  scale: 缩放比例
  '''
  im = Image.open(file)
  path = os.getcwd()
  if(not os.path.exists(path+"/tmp")):
    os.mkdir(path+"/tmp")
  os.chdir(path+"/tmp")
  # 清空 tmp 目录下内容
  for f in os.listdir(path+"/tmp"):
    os.remove(f)
  try:
    while 1:
      current = im.tell()
      name = file.split('.')[0]+'_tmp_'+str(current)+'.png'
      # 保存每一帧图片
      im.save(name)
      # 将每一帧处理为字符画
      img2ascii(name, ascii_chars, isgray, font, scale)
      # 继续处理下一帧
      im.seek(current+1)
  except:
    os.chdir(path)

# 将不同的灰度值映射为 ASCII 字符
def get_char(ascii_chars, r, g, b):
  length = len(ascii_chars)
  gray = int(0.2126 * r + 0.7152 * g + 0.0722 * b)
  return ascii_chars[int(gray/(256/length))]


# 将图片处理成字符画
def img2ascii(img, ascii_chars, isgray, font, scale):
  scale = scale
  # 将图片转换为 RGB 模式
  im = Image.open(img).convert('RGB')
  # 设定处理后的字符画大小
  raw_width = int(im.width * scale)
  raw_height = int(im.height * scale)
  # 获取设定的字体的尺寸
  font_x, font_y = font.getsize(' ')
  # 确定单元的大小
  block_x = int(font_x * scale)
  block_y = int(font_y * scale)
  # 确定长宽各有几个单元
  w = int(raw_width/block_x)
  h = int(raw_height/block_y)
  # 将每个单元缩小为一个像素
  im = im.resize((w, h), Image.NEAREST)
  # txts 和 colors 分别存储对应块的 ASCII 字符和 RGB 值
  txts = []
  colors = []
  for i in range(h):
    line = ''
    lineColor = []
    for j in range(w):
      pixel = im.getpixel((j, i))
      lineColor.append((pixel[0], pixel[1], pixel[2]))
      line += get_char(ascii_chars, pixel[0], pixel[1], pixel[2])
    txts.append(line)
    colors.append(lineColor)
  # 创建新画布
  img_txt = Image.new('RGB', (raw_width, raw_height), (255, 255, 255))
  # 创建 ImageDraw 对象以写入 ASCII
  draw = ImageDraw.Draw(img_txt)
  for j in range(len(txts)):
    for i in range(len(txts[0])):
      if isgray:
        draw.text((i * block_x, j * block_y), txts[j][i], (119,136,153))
      else:
        draw.text((i * block_x, j * block_y), txts[j][i], colors[j][i])
  img_txt.save(img)

# 读取 tmp 目录下文件合成 gif
def pic2gif(dir_name, out_name, duration):
  path = os.getcwd()
  os.chdir(dir_name)
  dirs = os.listdir()
  images = []
  num = 0
  for d in dirs:
    images.append(imageio.imread(d))
    num += 1
  os.chdir(path)
  imageio.mimsave(out_name + '_ascii.gif',images,duration = duration)