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！
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()