json格式的骨骼点实时显示问题

Question

在github上down其他人的代码后，只有train和valid，并没有实时显示，但是output文件中生成了大量的json文件。我应当如何将这些json文件生成实时显示的3D文件呢？我想要生成matplotlib这样的能够旋转的格式，如果能够抛弃3维坐标系驱动模型（例如smpl）那将是更好的。
麻烦各位帮帮忙，十分感谢！
  

Answer 1

仅供参考：

import json
import os

if __name__ == "__main__":
    fn=r'keypoints.json'
    f=open(fn, 'r')
    data = json.load(f)
    f.close()
#   print(data)

    people=data['people']
    L=len(people)
    for i in range(L):
        print("poeple %02d/%02d" %(i+1,L))
        for j in range(18):
            print("%02d: %5d %5d %4.2f" %(j, \
                int(round(people[i]['pose_keypoints_2d'][j*3+0])), \
                int(round(people[i]['pose_keypoints_2d'][j*3+1])), \
                          people[i]['pose_keypoints_2d'][j*3+2]))
        i+=1

#-*- encoding=GBK -*-

import cv2
import json
import os
import pickle
import sys

if __name__ == "__main__":
    if len(sys.argv)<2:
        print("Usage: jsons2dat.py fullpathvideofilename.ext")
        sys.exit()
    video = cv2.VideoCapture(sys.argv[1]) #r"video.mp4"
    if not video.isOpened():
        print("Could not open video")
        sys.exit()
    framecount = int(video.get(cv2.CAP_PROP_FRAME_COUNT ))
    datas=[]
    for i in range(framecount):
        fn=r"%s_%012d_keypoints.json" %(sys.argv[1][0:-4],i)
        try:
            f=open(fn,'r')
        except Exception as e:
            exceptmsg="f=open('%s','r') Exception:%s" %(fn,str(e))
            print(exceptmsg)
            sys.exit()
        data=json.load(f)
        f.close()
        datas.append(data)
        if i%100==0:
            print("%d/%d" %(i,framecount))

    with open(sys.argv[1][0:-4]+".dat", 'wb') as f:
        pickle.dump(datas, f)
        f.close()
    del datas
    with open(sys.argv[1][0:-4]+".dat", 'rb') as f:
        datas = pickle.load(f)
    print(len(datas))
    people=datas[framecount-1]['people']
    L=len(people)
    for i in range(L):
        print("poeple %02d/%02d" %(i+1,L))
        for j in range(18):
            print("%02d: %5d %5d %4.2f" %(j, \
                int(round(people[i]['pose_keypoints_2d'][j*3+0])), \
                int(round(people[i]['pose_keypoints_2d'][j*3+1])), \
                          people[i]['pose_keypoints_2d'][j*3+2]))

#-*- encoding=GBK -*-

import json
import os
from PIL import Image, ImageFont, ImageDraw
import cv2
import numpy as np
import pickle

THRESHOLD=0.2
nodecolors_COCO=[
    (192, 32, 96,150),# 0鼻头
    (128, 64,  0,150),# 1喉
    (192,128,  0,150),# 2右肩
    (192,192,  0,150),# 3右肘
    (128,192,  0,150),# 4右腕
    ( 64,192, 32,150),# 5左肩
    ( 00,192,  0,150),# 6左肘
    (  0,192, 64,150),# 7左腕
    ( 64,192,128,150),# 8右髋
    (  0,192,192,150),# 9右膝
    (  0,128,192,150),#10右踝
    (  0, 64,128,150),#11左髋
    ( 16, 16,128,150),#12左膝
    ( 64,  0,192,150),#13左踝
    (128, 16,128,150),#14右眼
    (192, 64,192,150),#15左眼
    (255, 16,192,150),#16右耳
    (192,  8, 64,150)]#17左耳
linkcolors_COCO=[
   [(  0,  0,160,150),( 90,  0,192,150),(160, 32,100,150)                  ],# 0鼻头
   [(160,  0,  0,150),(160, 64,  0,150),(  0,160,  0,150),(  0,160,160,150)],# 1喉
   [(160,100,  0,150)                                                      ],# 2右肩
   [(160,160,  0,150)                                                      ],# 3右肘
   [                                                                       ],# 4右腕
   [(100,160,  0,150)                                                      ],# 5左肩
   [( 64,160,  0,150)                                                      ],# 6左肘
   [                                                                       ],# 7左腕
   [(  0,160, 60,150)                                                      ],# 8右髋
   [(  0,160,100,150)                                                      ],# 9右膝
   [                                                                       ],#10右踝
   [(  0, 64,128,150)                                                      ],#11左髋
   [(  0, 64,160,150)                                                      ],#12左膝
   [                                                                       ],#13左踝
   [(120,  8,192,150)                                                      ],#14右眼
   [(160,  8,100,150)                                                      ],#15左眼
   [                                                                       ],#16右耳
   [                                                                       ]]#17左耳
links_COCO=[
    [1,14,15,-1],  # 0鼻头
    [2,5,8,11,-1], # 1喉
    [3,-1],        # 2右肩
    [4,-1],        # 3右肘
    [-1],          # 4右腕
    [6,-1],        # 5左肩
    [7,-1],        # 6左肘
    [-1],          # 7左腕
    [9,-1],        # 8右髋
    [10,-1],       # 9右膝
    [-1],          #10右踝
    [12,-1],       #11左髋
    [13,-1],       #12左膝
    [-1],          #13左踝
    [16,-1],       #14右眼
    [17,-1],       #15左眼
    [-1],          #16右耳
    [-1]]          #17左耳

if __name__ == "__main__":
    vfn=r'video.mp4'

    video = cv2.VideoCapture(vfn)
#   video.set(cv2.CAP_PROP_POS_FRAMES,50)  #设置要获取的帧号

    #include\opencv2\videoio.hpp
    #  0  CAP_PROP_POS_MSEC       Current position of the video file in milliseconds.
    #  1  CAP_PROP_POS_FRAMES     0-based index of the frame to be decoded/captured next.
    #  2  CAP_PROP_POS_AVI_RATIO  Relative position of the video file: 0 - start of the film, 1 - end of the film.
    #  3  CAP_PROP_FRAME_WIDTH    Width of the frames in the video stream.
    #  4  CAP_PROP_FRAME_HEIGHT   Height of the frames in the video stream.
    #  5  CAP_PROP_FPS            Frame rate.
    #  6  CAP_PROP_FOURCC         4-character code of codec.
    #  7  CAP_PROP_FRAME_COUNT    Number of frames in the video file.
    #  8  CAP_PROP_FORMAT         Format of the Mat objects returned by retrieve() .
    #  9  CAP_PROP_MODE           Backend-specific value indicating the current capture mode.
    # 10  CAP_PROP_BRIGHTNESS     Brightness of the image (only for cameras).
    # 11  CAP_PROP_CONTRAST       Contrast of the image (only for cameras).
    # 12  CAP_PROP_SATURATION     Saturation of the image (only for cameras).
    # 13  CAP_PROP_HUE            Hue of the image (only for cameras).
    # 14  CAP_PROP_GAIN           Gain of the image (only for cameras).
    # 15  CAP_PROP_EXPOSURE       Exposure (only for cameras).
    # 16  CAP_PROP_CONVERT_RGB    Boolean flags indicating whether images should be converted to RGB.
    # 17  CAP_PROP_WHITE_BALANCE  Currently unsupported
    # 18  CAP_PROP_RECTIFICATION  Rectification flag for stereo cameras (note: only supported by DC1394 v 2.x backend currently)

    width      = int(video.get(cv2.CAP_PROP_FRAME_WIDTH ))
    height     = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
    fps        = int(video.get(cv2.CAP_PROP_FPS         ))
    framecount = int(video.get(cv2.CAP_PROP_FRAME_COUNT ))
    print("width x height:%d x %d" %(width,height))
    print("           FPS:%d"      %(fps         ))
    print("    framecount:%d"      %(framecount  ))

    dfn=vfn[0:-4]+".dat"
    with open(dfn, 'rb') as f:
        datas = pickle.load(f)
    f.close()
#   fm2=0
    while True:
        # 读取视频流
        fm1=video.get(cv2.CAP_PROP_POS_FRAMES)
        ms1=video.get(cv2.CAP_PROP_POS_MSEC)
        ok, frame = video.read()
        if not ok:
            break
        newrgb=Image.fromarray(cv2.cvtColor(frame,cv2.COLOR_BGR2RGB))
        dw=ImageDraw.Draw(newrgb)

        people=datas[int(fm1)]['people']
        L=len(people)
        for i in range(L):
#           print("poeple %02d/%02d" %(i+1,L))
            Xlist = []
            Ylist = []
            for j in range(18):
                for k in range(4):
                    if links_COCO[j][k]==-1:
                        break
                    x =int(round(people[i]['pose_keypoints_2d'][           j    *3+0]))
                    y =int(round(people[i]['pose_keypoints_2d'][           j    *3+1]))
                    c =          people[i]['pose_keypoints_2d'][           j    *3+2]
                    x1=int(round(people[i]['pose_keypoints_2d'][links_COCO[j][k]*3+0]))
                    y1=int(round(people[i]['pose_keypoints_2d'][links_COCO[j][k]*3+1]))
                    c1=          people[i]['pose_keypoints_2d'][links_COCO[j][k]*3+2]
                    if c>THRESHOLD and c1>THRESHOLD:
                        dw.line(((x,y),(x1,y1)),fill=linkcolors_COCO[j][k],width=4)

                x=int(round(people[i]['pose_keypoints_2d'][j*3+0]))
                y=int(round(people[i]['pose_keypoints_2d'][j*3+1]))
                c=          people[i]['pose_keypoints_2d'][j*3+2]
                if c>THRESHOLD:
                    dw.ellipse(((x-5,y-5),(x+5,y+5)),fill=nodecolors_COCO[j])
                    Xlist.append(x)
                    Ylist.append(y)
            if len(Xlist)>0:
                maxX = int(max(Xlist))
                minX = int(min(Xlist))
                maxY = int(max(Ylist))
                minY = int(min(Ylist))
                w=maxX-minX
                h=maxY-minY
                left=minX-w//4
                if left<0:
                    left=0
                top=minY-h//4
                if top<0:
                    top=0
                right=maxX+w//4
                if right>width-1:
                    right=width-1
                bottom=maxY+h//4
                if bottom>height-1:
                    bottom=height-1
                dw.rectangle(((left  ,top  ),(right  ,bottom  )),outline=(  0,255,  0,255))
                dw.rectangle(((left+1,top+1),(right-1,bottom-1)),outline=(  0,255,  0,255))

#       dw.text((48, 48), "fm1 %6d==%6d fm2" %(fm1,fm2), font=ImageFont.truetype('simhei.ttf', 48),fill=(255,255,255,255))
        mss=int(framecount/fps*1000) #总毫秒数
        dw.text((24, 24), "%06d/%06d %02d:%02d:%02d.%03d/%02d:%02d:%02d" %(fm1,framecount,\
            ms1//(3600*1000),ms1//(60*1000)%60,ms1//(1000)%60,ms1%1000,\
            mss//(3600*1000),mss//(60*1000)%60,mss//(1000)%60,         \
            ), font=ImageFont.truetype('simhei.ttf', 24),fill=(255,255,255,255))

#       fm2+=1

        imgs=cv2.cvtColor(np.asarray(newrgb),cv2.COLOR_RGB2BGR)
        cv2.imshow('video', imgs)
        key = cv2.waitKey(1) & 0xFF
        if key == 27:
            break
        if key == 32:
            cv2.waitKey(0)
    video.release()
    cv2.destroyAllWindows()