二进制.bin文件切分、bintopng、write

import numpy as np
import cv2
import os


# Your file path
file_dep = open(r"E:\\data\\3DHuman-Detection\\withoutlabel\\20180715_50_50_uint16_amp0.bin", 'rb')
i=0
while 1:
    frame = np.frombuffer(file_dep.read(320 * 240 * 2), dtype=np.uint16)
    img = frame.copy().reshape(240,320)
    img_u8 = (img.copy() / (6000/255)).astype(np.uint8)
    cv2.imshow("img", img_u8)
    
    __path__="E:\\data\\3DHuman-Detection\\1\\"
    #实现增加后缀名存储
    fileName = str(i)+".png"
    i=i+1
    fileName = os.path.join(__path__, fileName)
   
    #cv2.imwrite(__path__, img_u8)
    cv2.imwrite(fileName, img_u8 , [cv2.IMWRITE_PNG_COMPRESSION, 0])
    #img_rgb = cv2.applyColorMap(img_u8, cv2.COLORMAP_JET)
   # cv2.imshow("img_rgb", img_rgb)
    cv2.waitKey(10)

划分bin文件成128k

# -*- coding: utf-8 -*- 
#按照大小分割文件
 
import os
 
filename = "E:\\data\\3DHuman-Detection\\withoutlabel\\20180715_50_50_uint16_amp0.bin"#需要进行分割的文件，请修改文件名
size = 131072 #分割大小约128K
 
def mk_SubFile(srcName,sub,buf):
    [des_filename, extname] = os.path.splitext(srcName)
    filename  = des_filename + '_' + str(sub) + extname
    print( '生成子文件ing: %s' %filename)
    with open(filename,'wb') as fout:
        fout.write(buf)
        return sub+1
            
            
def split_By_size(filename,size):
    with open(filename,'rb') as fin:
        buf = fin.read(size)
        sub = 1
        while len(buf)>0:
            sub = mk_SubFile(filename,sub,buf)
            buf = fin.read(size)  
    print("ok")
            
 
if __name__=="__main__":
    split_By_size(filename, size)

将bin转换成8位的灰度图（具有resize功能）

# coding=utf-8
import cv2
import numpy as np
import os


def convert_bin2png():
    """把单通道的bin文件转换为png"""
    for i in range(pic_num):
        bin_name = "20180715_50_50_uint16_amp0_"+"{}.bin".format(i+1)
        # bin_name = "manba_1650_1800_rgb_888-"+"{}.bin".format(i)
        input_name = path + bin_name  # 输入图像文件名
        # input_name = path+"xy_1800_2600_rgb_888-"+bin_name
        # input_name = path+"xy_1800_2600_depth_u16-"+bin_name
        image = np.fromfile(input_name, dtype=np.uint16)  # 和bin文件的位数一致才可以转，不然报错
        # image = np.fromfile(input_name, dtype=np.uint8)# rgb图像为8位3通道
        image_gray = np.reshape(image, (height, width, channel))
        output_name = "20180715_50_50_uint16_amp0_"+"{}.png".format(i+1)  # 输出图片文件名
        # output_name ="manba_1650_1800_rgb_888-" "{}.png".format(i)
        out_path_name = path1 + output_name  # 输出图片路径
        #dst = cv2.resize(image_gray, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_LINEAR)
        cv2.imwrite(out_path_name, image_gray , [cv2.IMWRITE_PNG_COMPRESSION, 0])
        print("already wrote", i + 1, "/", pic_num, "pictures")  # 浏览写入进度


def convert_bin2video():
    """"""
    size = (width, height)  # 保存图片的尺寸
    fourcc = cv2.VideoWriter_fourcc('M', 'J', 'P', 'G')
    video_writer = cv2.VideoWriter(path + '_out_video.avi', fourcc, fps, size)
    for i in range(0, pic_num):
        bin_name = "{}.bin".format(i)
        input_name = path + bin_name
        image = np.fromfile(input_name, dtype=np.uint8)
        frame = np.reshape(image, (height, width, channel))
        video_writer.write(frame)
        print("converting", i, "th picture to video")
    video_writer.release()


if __name__ == '__main__':
    path = r"E:\\data\\3DHuman-Detection\\withoutlabel\\"  # 输入bin文件的路径
    path1 = r"E:\\data\\3DHuman-Detection\\1\\"  # 输入png文件的路径
    # path1= "E:\\data\\img\\"
    pic_num = len(os.listdir(path))  # 自动获取图片数量
    width = 320  # 图片宽度
    height = 240  # 图片高度
    channel = 1  # 通道数
    # channel = 1  # 灰度图和深度图通道数
    fps = 30  # 保存视频的FPS，30：正常速度， 60:2倍速
    # 转换成图片帧
    convert_bin2png()
    # 转换成视频
    #convert_bin2video()