parser.add_argument(
    "--ocr",
    type=bool,
    default=False,
    help="use paddlepaddle-ocr")

from python.visualize import visualize_box_mask, visualize_attr, visualize_pose, visualize_action, visualize_vehicleplate, visualize_vehiclepress, visualize_lane, visualize_vehicle_retrograde, visualize_ocr

class PipePredictor(object):  
    def __init__(self, args, cfg, is_video=True, multi_camera=False):
    	self.ocr = args.ocr

def visualize_video(self,
                    image_rgb,
                    result,
                    collector,
                    frame_id,
                    fps,
                    entrance=None,
                    records=None,
                    center_traj=None,
                    do_illegal_parking_recognition=False,
                    illegal_parking_dict=None):
    image = cv2.cvtColor(image_rgb, cv2.COLOR_RGB2BGR)
    mot_res = copy.deepcopy(result.get('mot'))

    if self.ocr:
        lock.acquire() # 加锁，paddleOCR是线程不安全的
        ocr_result = ocr.ocr(image, cls=True)[0]
        lock.release()
        ocr_boxes = [line[0] for line in ocr_result]
        ocr_txts = [line[1][0] for line in ocr_result]
        ocr_scores = [line[1][1] for line in ocr_result]
        
        image = visualize_ocr(image, ocr_boxes, ocr_txts, ocr_scores)

def visualize_ocr(im, boxes, texts, score):
    if isinstance(im, str):
        im = Image.open(im)
        im = np.ascontiguousarray(np.copy(im))
        im = cv2.cvtColor(im, cv2.COLOR_RGB2BGR)
    else:
        im = np.ascontiguousarray(np.copy(im))

    # 创建透明图层，为图像添加文字水印
    im = Image.fromarray(im)
    im = im.convert('RGBA')
    im_canvas = Image.new('RGBA', im.size, (255, 255, 255, 0))

    for i, res in enumerate(texts):
        if boxes is not None:
            box = boxes[i]
            text = res
            if text == "":
                continue

            text_scale = max(1.0, int(box[2][1] - box[1][1]))

            draw = ImageDraw.Draw(im_canvas)
            draw.text(
                (box[0][0], box[0][1]),
                text,
                font=ImageFont.truetype(font_file, size=int(text_scale)),
                fill=(255, 255, 0, 85)) # 第四位是透明度
            try:
                draw.rectangle(
                    ((box[0][0], box[0][1]), (box[2][0], box[2][1])),
                    fill=None,
                    outline=(255, 255, 0),
                    width=1)
            except ValueError:
                pass

    # 复合图层
    im = Image.alpha_composite(im, im_canvas)
    im = im.convert('RGB')
    # 还原连续存储数组
    im = np.ascontiguousarray(np.copy(im))
    return im

from PIL import Image, ImageDraw, ImageFile, ImageFont

font_file = '/exp/work/video/PaddleDetection/deploy/pipeline/SourceHanSansCN-Medium.otf'

def visualize_attr(im, results, boxes=None, is_mtmct=False):
    if isinstance(im, str):
        im = Image.open(im)
        im = np.ascontiguousarray(np.copy(im))
        im = cv2.cvtColor(im, cv2.COLOR_RGB2BGR)
    else:
        im = np.ascontiguousarray(np.copy(im))

    line_inter = im.shape[0] / 40.
    text_scale = max(0.5, im.shape[0] / 100.)
    # 将nparray图像转PIL图像
    im = Image.fromarray(im)

    for i, res in enumerate(results):
        print(i, res)
        if boxes is None:
            text_w = 3
            text_h = 1
        elif is_mtmct:
            box = boxes[i]  # multi camera, bbox shape is x,y, w,h
            text_w = int(box[0]) + 3
            text_h = int(box[1])
        else:
            box = boxes[i]  # single camera, bbox shape is 0, 0, x,y, w,h
            text_w = int(box[2]) + 3
            text_h = int(box[3])
        for text in res:
            text_h += int(line_inter)
            text_loc = (text_w, text_h)
            # 写入
            draw = ImageDraw.Draw(im)
            draw.text(
                text_loc,
                text,
                font=ImageFont.truetype(font_file, size=int(text_scale)), # 字体位置
                fill=(0, 255, 255))
    # 还原连续存储数组
    im = np.ascontiguousarray(np.copy(im))
    return im

tools/test_recognition.py:627: DeprecationWarning: getsize is deprecated and will be removed in Pillow 10 (2023-07-01). Use getbbox or getlength instead.
  tw = font.getsize(text)[0]

out_path = os.path.join(self.output_dir, video_out_name + ".mp4")
fourcc = cv2.VideoWriter_fourcc(* 'mp4v')
writer = cv2.VideoWriter(out_path, fourcc, fps, (width, height))

df = spark.read.format(
  "com.vesoft.nebula.connector.NebulaDataSource").option(
    "type", "vertex").option(
    "spaceName", "basketballplayer").option(
    "label", "player").option(
    "returnCols", "name,age").option(
    "metaAddress", "metad0:9559").option(
    "partitionNumber", 1).load()

>>> df.show(n=2)
+---------+--------------+---+
|_vertexId|          name|age|
+---------+--------------+---+
|player105|   Danny Green| 31|
|player109|Tiago Splitter| 34|
+---------+--------------+---+
only showing top 2 rows

from pyspark.sql import SparkSession

# 通过builder方法来构建SparkSession对象
# appName：设置程序名称
# config：配置常用属性
# getOrCreate：完成创建SparkSession对象
spark = SparkSession.builder.appName("test").master("local[*]").config("spark.sql.shuffle.partitions", "4").getOrCreate()

from pyspark.sql import SparkSession

spark = SparkSession.builder.appName("test").master("local[*]").config("spark.sql.shuffle.partitions", "4").getOrCreate()

sc = spark.sparkContext

# 1.将本地对象标记为广播变量
broadcast = sc.broadcast(var)
# 2.使用广播变量，从broadcast对象中取出本地对象
value = broadcast.value
# 当传输的是广播对象时，spark会只给每个Executor分发一份数据

# spark提供累加器变量，参数是初始值
acmlt = sc.accumulator(0)

from pyspark import SparkConf, SparkContext

conf = SparkConf().setAppName("test").setMaster("local[*]")
sc = SparkContext(conf=conf)

acmlt = sc.accumulator(0)


def counts(data):
    global acmlt
    acmlt += 1
    return data


rdd1 = sc.parallelize([1, 2, 3], 3)
rdd2 = rdd1.map(counts)
print(rdd2.collect())
print(acmlt)