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MovpointPR.py

+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+
+import imageio
+
+from PIL import Image
+import os
+from pathlib import Path
+import json
+import csv
+from jsonpath import jsonpath
+import math
+import cv2
+import imageio
+#滤波操作
+class MovAvg(object):
+    def __init__(self, window_size=10):
+        self.window_size = window_size
+        self.data_queue = []
+    def update(self, data):
+        if len(self.data_queue) == self.window_size:
+            del self.data_queue[0]
+        #if data>0:
+        self.data_queue.append(data)
+        return sum(self.data_queue)/len(self.data_queue)
+
+def changejointupper(pose,jointlist):
+    for jointindex in jointlist:
+        if (jointindex+3) not in jointlist:
+            continue
+        if pose[jointindex,0]>pose[jointindex+3,0]:
+            pose[jointindex, 0],pose[jointindex + 3, 0]=pose[jointindex + 3, 0],pose[jointindex, 0]
+            pose[jointindex, 1], pose[jointindex + 3, 1] = pose[jointindex + 3, 1], pose[jointindex, 1]
+
+def changejointlower(pose,jointlist):
+    for jointindex in jointlist:
+        if (jointindex+3) not in jointlist:
+            continue
+        if pose[jointindex,0]<pose[jointindex+3,0]:
+            pose[jointindex, 0],pose[jointindex + 3, 0]=pose[jointindex + 3, 0],pose[jointindex, 0]
+            pose[jointindex, 1], pose[jointindex + 3, 1] = pose[jointindex + 3, 1], pose[jointindex, 1]
+
+def selectjointdistance(PoseX,PoseY,jointlist):
+    newPoseX=[]
+    newPoseY=[]
+    for jointindex in jointlist:
+        #PoseX[jointindex]=updateArray(deleterror(searcherror(PoseX[jointindex]), PoseX[jointindex]))
+        #PoseY[jointindex] = updateArray(deleterror(searcherror(PoseY[jointindex]), PoseY[jointindex]))
+        #PoseX[jointindex]=deleterror(searcherror(PoseX[jointindex]), PoseX[jointindex])
+        #PoseY[jointindex] = deleterror(searcherror(PoseY[jointindex]), PoseY[jointindex])
+        newPoseX.append(PoseX[jointindex])
+        newPoseY.append(PoseY[jointindex])
+    return computedistance(np.array(newPoseX),np.array(newPoseY))
+
+def selectjointdistancestd(PoseX,PoseY,jointlist):
+    newPoseX=[]
+    newPoseY=[]
+    for jointindex in jointlist:
+        #PoseX[jointindex]=updateArray(deleterror(searcherror(PoseX[jointindex]), PoseX[jointindex]))
+        #PoseY[jointindex] = updateArray(deleterror(searcherror(PoseY[jointindex]), PoseY[jointindex]))
+        newPoseX.append(PoseX[jointindex])
+        newPoseY.append(PoseY[jointindex])
+    return computedistancestd(np.array(newPoseX),np.array(newPoseY))
+
+def sumerror(Array):
+    #sum=0
+    Sum=0
+    for i_1 in range(1,len(Array),2):
+        #print('i:',i_1)
+        sum=Array[i_1]-Array[i_1-1]
+        Sum=Sum+sum
+    return Sum
+
+def deletezero(Array):
+    newArray=[]
+    for array in Array:
+        if array!=0:
+            newArray.append(array)
+    return newArray
+def computedistance(X,Y):
+    inDistanceList=[]
+    for i_1 in range(0,len(X[0])-1):
+        innerdistance=0
+        for j_1 in range(0,len(X[:,])):
+            #print('length:',len(X[:,]))
+            distance=math.sqrt(math.pow((X[j_1,i_1]-X[j_1,i_1+1]),2)+math.pow((Y[j_1,i_1]-Y[j_1,i_1+1]),2))
+            #print('distance:',distance)
+            innerdistance=innerdistance+distance
+        inDistanceList.append(innerdistance)
+    return np.mean(inDistanceList)
+
+def zeorexist(Array):
+    Zero=1
+    for i_exist in range(0,25):
+        if sum(Array[i_exist])==0:
+           Zero=0
+    return Zero
+def multi(N):
+    result=1
+    for n in N:
+        result=result*n
+    return result
+
+
+def computedistancestd(X,Y):
+    inDistanceList=[]
+    for i_1 in range(0,len(X[0])-1):
+        innerdistance=0
+        for j_1 in range(0,len(X[:,])):
+            distance=math.sqrt(math.pow((X[j_1,i_1]-X[j_1,i_1+1]),2)+math.pow((Y[j_1,i_1]-Y[j_1,i_1+1]),2))
+            innerdistance=innerdistance+distance
+        inDistanceList.append(innerdistance)
+    return np.std(inDistanceList,ddof=1)
+
+def updateArray(Prearray):
+    Newarray=[]
+    ma=MovAvg()
+    for prearray in Prearray:
+        Newarray.append(ma.update(prearray))
+    #print('updateArray:',len(Newarray))
+    return Newarray
+
+def searcherror(Array):
+    newArray=[]
+    for i_1 in range(1,len(Array)):
+        if abs(Array[i_1-1]-Array[i_1])>30:
+            newArray.append(i_1-1)
+    #print('newArray:',newArray)
+    #print('error length:',len(newArray))
+    return newArray
+
+def deleterror(index,Array):
+    begin=[]
+    end=[]
+    newArray=[]
+    for i_1 in range(0,len(index)):
+        if i_1%2!=0:
+            begin.append(index[i_1-1])
+            end.append(index[i_1])
+    newArray=Array
+    for i_2 in range(0,len(begin)):
+        be=begin[i_2]
+        en=end[i_2]
+        for j_1 in range(be+1,en+1):
+            #newArray[j_1] = 0
+            newArray[j_1]=newArray[be]
+    #print('deleteerror:',newArray)
+    #return deletezero(newArray)
+    return newArray
+
+def str2sec(x):
+    h, m, s = x.strip().split(':')
+    return (int(h) * 3600 + int(m) * 60 + int(s)) * 30
+
+
+def dict_generator(indict, pre=None):
+    pre = pre[:] if pre else []
+    if isinstance(indict, dict):
+        for key, value in indict.items():
+            if isinstance(value, dict):
+                if len(value) == 0:
+                    yield pre + [key, '{}']
+                else:
+                    for d in dict_generator(value, pre + [key]):
+                        yield d
+            elif isinstance(value, list):
+                if len(value) == 0:
+                    yield pre + [key, '[]']
+                else:
+                    for v in value:
+                        for d in dict_generator(v, pre + [key]):
+                            yield d
+            elif isinstance(value, tuple):
+                if len(value) == 0:
+                    yield pre + [key, '()']
+                else:
+                    for v in value:
+                        for d in dict_generator(v, pre + [key]):
+                            yield d
+            else:
+                yield pre + [key, value]
+    else:
+        yield indict
+
+def get_file_path(root_path, file_list, dir_list):
+    dir_or_files = os.listdir(root_path)
+    for dir_file in dir_or_files:
+
+        dir_file_path = os.path.join(root_path, dir_file)
+
+        if os.path.isdir(dir_file_path):
+            dir_list.append(dir_file_path)
+
+        else:
+            file_list.append(dir_file_path)
+
+def countdistance(pre,next):
+    Distance=0
+    for i in range(0,4):
+        #print('前一时刻第',i,'个点的坐标：','(',pre[i,0],',',pre[i,1],')')
+        #print('后一时刻第', i, '个点的坐标：', '(', next[i, 0], ',', next[i,1], ')')
+        distance=math.sqrt(math.pow((pre[i,0]-next[i,0]),2)+math.pow((pre[i,1]-next[i,1]),2))
+        Distance=Distance+distance
+    return Distance
+
+def getclip(mp4_list):
+    clip_list=[]
+    for mp4 in mp4_list:
+        clip_list.append(int(mp4[-6:-4]))
+    #clip_list.sort()
+    return clip_list
+
+point_path = r"/mnt/data1/zhanghongyi/origin_CS_PR/PR/"
+point_file_list=[]
+point_dir_list=[]
+get_file_path(point_path, point_file_list, point_dir_list)
+point_dir_list.sort()
+point_file_list.sort()
+Raw_x = []
+Raw_y = []
+for point_file in point_file_list:
+    if 'json' not in point_file or 'correct' in point_file:
+        continue
+    print('point_file:',point_file)
+    json_result={}
+    Value = json.load(open(point_file))
+    #print('shape:',np.array(jsonpath(Value, "$..data")).shape)
+    pose = np.array(jsonpath(Value, "$..data")).reshape(300,25,3)
+    #print('pose:',pose)
+    Raw_x = []
+    Raw_y = []
+    Raw_c=[]
+    for i in range(0,300):
+        changejointupper(np.array(pose)[i], [2,3,4,5,6,7,9,10,11,12,13, 14,15,16,17,18])
+        changejointlower(np.array(pose)[i], [19,20,21,22,23,24])
+        Raw_x.append(np.array(pose)[i][:, 0])
+        Raw_y.append(np.array(pose)[i][:, 1])
+        Raw_c.append(np.array(pose)[i][:, 2])
+
+    #print('Raw_x:',np.array(Raw_x).shape)
+    #print('Raw_y:',np.array(Raw_y).shape)
+    #print('Raw_c:',np.array(Raw_c).shape)
+    my_Raw_x=[]
+    my_Raw_y=[]
+    my_Raw_c=np.array(Raw_c)
+
+    for j in range(0,25):
+        #print('pre x:',np.array(Raw_x)[:,j])
+        #fig, axes = plt.subplots(2, 2)
+        #ax1 = axes[0, 0]
+        #ax2 = axes[0, 1]
+        #print('error length x:',sumerror(searcherror(np.array(Raw_x)[:,j])))
+        #print('error length y:', sumerror(searcherror(np.array(Raw_y)[:,j])))
+
+
+        #if sumerror(searcherror(np.array(Raw_x)[:,j]))<70 and sumerror(searcherror(np.array(Raw_y)[:,j]))<70:
+        my_Raw_x.append(updateArray(deleterror(searcherror(np.array(Raw_x)[:, j]), np.array(Raw_x)[:, j])))
+        my_Raw_y.append(updateArray(deleterror(searcherror(np.array(Raw_y)[:, j]), np.array(Raw_y)[:, j])))
+        #else:
+         #   my_Raw_x.append(np.zeros(300))
+          #  my_Raw_y.append(np.zeros(300))
+        #print('shape:',updateArray(deleterror(searcherror(np.array(Raw_x)[:,j]), np.array(Raw_x)[:,j])))
+
+        #ax1.plot(np.array(Raw_x)[:,j], label='raw_r_wrist_x')
+        #ax1.plot(updateArray(deleterror(searcherror(np.array(Raw_x)[:,j]), np.array(Raw_x)[:,j])), label='new_raw_r_wrist_x')
+        #ax1.plot(deleterror(searcherror(np.array(Raw_x)[:, j]), np.array(Raw_x)[:, j]),label='new_raw_r_wrist_x')
+
+        #print('after x:',updateArray(deleterror(searcherror(np.array(Raw_x)[:,j]), np.array(Raw_x)[:,j])))
+        #print('pre y:', np.array(Raw_y)[:, j])
+
+        #print('after y:',updateArray(deleterror(searcherror(np.array(Raw_y)[:, j]), np.array(Raw_y)[:, j])))
+        #ax2.plot(np.array(Raw_y)[:,j], label='raw_r_wrist_x')
+        #ax2.plot(updateArray(deleterror(searcherror(np.array(Raw_y)[:, j]), np.array(Raw_y)[:, j])),label='new_raw_r_wrist_y')
+        #plt.legend()
+        #titlename='the'+str(j)+'joints'+' error:'+str(sumerror(searcherror(np.array(Raw_x)[:,j])))
+        #plt.title(titlename)
+        #plt.show()
+        #plt.close()
+    #print('shape:',np.array(my_Raw_x).shape)
+    #print('zerox:',zeorexist(np.array(my_Raw_x)))
+    #print('zeroy:', zeorexist(np.array(my_Raw_y)))
+    #if zeorexist(np.array(my_Raw_x))==0 or zeorexist(np.array(my_Raw_y))==0:
+        #new_Raw=np.zeros((300,3,25,1))
+        #print('new_Raw',new_Raw)
+    #else:
+    new_my_Raw_x=np.transpose(np.array(my_Raw_x))
+    new_my_Raw_y = np.transpose(np.array(my_Raw_y))
+    #print('my_Raw_x.shape:',np.array(my_Raw_x))
+    #print('my_Raw_y.shape:', np.array(my_Raw_y))
+    new_Raw_x=np.expand_dims(np.array(new_my_Raw_x),2)
+    new_Raw_y = np.expand_dims(np.array(new_my_Raw_y), 2)
+    new_Raw_c = np.expand_dims(np.array(my_Raw_c), 2)
+    new_Raw=np.hstack((new_Raw_x,new_Raw_y,new_Raw_c)).reshape(300,3,25,1)
+    New=[]
+
+    for k in range(0,300):
+        #print('shape:',new_Raw[k].shape)
+        #print('array:', new_Raw[k])
+        #print('array[0]:',new_Raw[k][0])
+        #print('array[1]:',new_Raw[k][1])
+        #print('array[2]:',new_Raw[k][2])
+        new=np.hstack((new_Raw[k][0],new_Raw[k][1],new_Raw[k][2]))
+        #print('new:',new)
+        New.append(new)
+
+    #print('New:',sum(sum(sum(np.array(New)))))
+    #print('New.shape:',np.array(New).shape)
+    #print('new Raw:', np.array(new_Raw).shape)
+    '''
+    print('new Raw_x:',np.array(new_Raw_x).shape)
+    print('new Raw_x:',np.array(new_Raw_x))
+    print('new Raw_y:', np.array(new_Raw_y).shape)
+    print('new Raw_y:', np.array(new_Raw_y))
+    print('new Raw_c:',np.array(new_Raw_c).shape)
+    print('new Raw_c:', np.array(new_Raw_c))
+    print('new Raw:',np.array(new_Raw).shape)
+    print('new Raw:',np.array(new_Raw))
+    '''
+    if sum(sum(sum(np.array(New))))>0:
+        distance = selectjointdistance(np.array(my_Raw_x),np.array(my_Raw_y), [4,7,11,14,20,23])
+        #distance=selectjointdistance(np.transpose(np.array(my_Raw_x)),np.transpose(np.array(my_Raw_y)),[11,14])
+        print('distance:',distance)
+        if distance>3 and distance<10:
+            json_result['category'] = 'PR'
+            json_result['data'] = np.expand_dims(New, axis=3).tolist()  # 300 * 25 * 3 * 1
+            json_result['distance']=distance
+            with open(point_file[:-5] + '_correct.json', 'w') as f2:
+                json.dump(json_result, f2)
+
+
+
+
+
+
+
+