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check_gaze_recursive_with_acc.py
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import csv
import numpy as np
import os
import glob
import cv2
import json
from time import time
import datetime as dt
# import pickle as pkl
import math
import csv
import pandas as pd
import sys
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib as mpl
import match_intersection as objmatch_roi
from util_calc import *
from tkinter import filedialog
from tkinter import *
# 최대 줄 수 설정
pd.set_option('display.max_rows', 2500)
# 최대 열 수 설정
pd.set_option('display.max_columns', 200)
# 표시할 가로의 길이
pd.set_option('display.width', 160)
# 출력값 소숫점4자리로 설정
pd.options.display.float_format = '{:.4f}'.format
deg2Rad = math.pi/180
rad2Deg = 180/math.pi
bcheck_match = objmatch_roi.match_intersection_roi()
def funcname():
return sys._getframe(1).f_code.co_name + "()"
def callername():
return sys._getframe(2).f_code.co_name + "()"
def print_current_time(text=''):
tnow = dt.datetime.now()
print('%s-%2s-%2s %2s:%2s:%2s \t%s' % (tnow.year, tnow.month, tnow.day, tnow.hour, tnow.minute, tnow.second, text))
def eulerAnglesToRotationMatrix(theta):
R_x = np.array([[1, 0, 0],
[0, math.cos(theta[0]), -math.sin(theta[0])],
[0, math.sin(theta[0]), math.cos(theta[0])]])
R_y = np.array([[math.cos(theta[1]), 0, math.sin(theta[1])],
[0, 1, 0],
[-math.sin(theta[1]), 0, math.cos(theta[1])]])
R_z = np.array([[math.cos(theta[2]), -math.sin(theta[2]), 0],
[math.sin(theta[2]), math.cos(theta[2]), 0],
[0, 0, 1]])
R = np.dot(R_z, np.dot(R_y, R_x))
return R
def rotationMatrixToEulerAngles(R):
sy = math.sqrt(R[0, 0] * R[0, 0] + R[1, 0] * R[1, 0])
singular = sy < 1e-6
if not singular:
x = math.atan2(R[2, 1], R[2, 2])
y = math.atan2(-R[2, 0], sy)
z = math.atan2(R[1, 0], R[0, 0])
else:
x = math.atan2(-R[1, 2], R[1, 1])
y = math.atan2(-R[2, 0], sy)
z = 0
return np.array([x, y, z])
def intersectionWithPlan(linePoint, lineDir, planOrth, planPoint):
d = np.dot(np.subtract(linePoint, planPoint), planOrth) / (np.dot(lineDir, planOrth))
intersectionPoint = np.subtract(np.multiply(d, lineDir), linePoint)
return intersectionPoint
def changeAxis_opencv2daimler(nR, nT):
#opencv x y z axis-> daimler -y -z x
#opencv pitch, yaw, roll -> daimler -pitch -yaw roll
#daimler x y z axis-> opencv z -x -y
#daimler roll, pitch, yaw -> opencv roll -pitch -yaw
ret_nT = np.zeros((3, 1))
ret_nR = np.zeros((3, 1))
ret_nT[0] = nT[2]
ret_nT[1] = -nT[0]
ret_nT[2] = -nT[1]
ret_nR[0] = nR[2]
ret_nR[1] = -nR[0]
ret_nR[2] = -nR[1]
return ret_nR, ret_nT
def changeAxis_daimler2opencv(nR, nT):
#opencv x y z axis-> daimler -y -z x
#opencv pitch, yaw, roll -> daimler -pitch -yaw roll
#daimler x y z axis-> opencv z -x -y
#daimler roll, pitch, yaw -> opencv roll -pitch -yaw
ret_nT = np.zeros((3, 1))
ret_nR = np.zeros((3, 1))
ret_nT[0] = -nT[1]
ret_nT[1] = -nT[2]
ret_nT[2] = nT[0]
ret_nR[0] = -nR[1]
ret_nR[1] = -nR[2]
ret_nR[2] = nR[0]
return ret_nR, ret_nT
def load_jsonfile_ROI(fname):
print("//////////", funcname(), "//////////")
fp = open(fname)
fjs = json.load(fp)
fp.close()
# print(fjs)
return fjs
def extract_availData_from_3D_target_ROI(pROI):
print("//////////", funcname(), "//////////")
tValid = []
target_roi = pROI['ROI']
for i, data in enumerate(target_roi):
# print(i, data)
bValid = True
tID = []
tTargetName = ["None"]
ttop_left = []
ttop_right = []
tbottom_left = []
tbottom_right = []
for name in data:
# print('name',name)
if (name == 'id'):
print('id', data['id'])
tID.append(data['id'])
elif(name == 'obj_params'):
# print('obj_params', data['obj_params'])
print('obj_params', data['obj_params']['top_left'], data['obj_params']['top_right'], data['obj_params']['bottom_left'])
if(data['obj_params']['top_left'][0]==0.0 and data['obj_params']['top_right'][0]==0.0 and data['obj_params']['bottom_left'][0]==0.0):
bValid = False
break
ttop_left.append(data['obj_params']['top_left'])
ttop_right.append(data['obj_params']['top_right'])
tbottom_left.append(data['obj_params']['bottom_left'])
temp = np.round((np.array(tbottom_left) + np.array(ttop_right) - np.array(ttop_left)),5).tolist()[0]
tbottom_right.append(temp)
elif(name == '_comment'):
print('_comment', data['_comment'])
tTargetName[-1] = data['_comment']
if(bValid == True):
tValid.append([tID, tTargetName, ttop_left, ttop_right, tbottom_left, tbottom_right])
print('tValid', tValid)
tValid = np.array(tValid.copy())
available_dict = {"tID":tValid.T[0][0],"tTargetName":tValid.T[0][1],
"ttop_left":tValid.T[0][2],
"ttop_right": tValid.T[0][3],
"tbottom_left": tValid.T[0][4],
"tbottom_right": tValid.T[0][5]
}
# available_df = pd.DataFrame({tframeId,theadPos3D, theadPos3D, theadOri,tisFaceDetected }, index=tframeId, columns=available_columns) # index 지정
# available_df = pd.DataFrame({'frameId':tframeId,"theadPos3D":theadPos3D}, columns=["frameId","theadPos3D"]) # index 지정
#
# fig = plt.figure(figsize=(10,8))
# ax3 = fig.add_subplot(111, projection='3d')
# plt.title('3D Target ROI')
#
# for i in tValid[:][0:-1]:
# print(i[2][0][0], i[2][0][1], i[2][0][2], '-----')
# x0 = i[2][0][0] * 1000
# y0 = i[2][0][1] * 1000
# z0 = i[2][0][2] * 1000
# # ax3.scatter(xs=x, ys=y, zs=z, label=i[1])
# x1 = i[3][0][0] * 1000
# y1 = i[3][0][1] * 1000
# z1 = i[3][0][2] * 1000
# # ax3.scatter(xs=x, ys=y, zs=z, label=i[1])
# x2 = i[4][0][0] * 1000
# y2 = i[4][0][1] * 1000
# z2 = i[4][0][2] * 1000
# # ax3.scatter(xs=x, ys=y, zs=z, label=i[1])
# x3 = i[5][0][0] * 1000
# y3 = i[5][0][1] * 1000
# z3 = i[5][0][2] * 1000
# ax3.scatter(xs=[x0,x1,x3,x2], ys=[y0,y1,y3,y2], zs=[z0,z1,z3,z2] )
# ax3.plot([x0,x1,x3,x2,x0], [y0,y1,y3,y2,y0], [z0,z1,z3,z2,z0], label=i[1])
#
# ax3.set_zlim(-1000, 1000)
# ax3.set_title("3D Target ROI")
# ax3.set_xlabel('veh X', fontsize=16)
# ax3.set_ylabel('veh Y', fontsize=16)
# ax3.set_zlabel('veh Z', fontsize=16)
# ax3.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))
# ax3.view_init(5, -10)
#
# plt.grid(True)
# plt.show()
available_df = pd.DataFrame(available_dict) # index 지정
print(available_df)
return available_df
def extract_availData_from_GT_short(inputPath_GT):
print("//////////", funcname(), "//////////")
extGT = pd.read_csv(inputPath_GT)
df_extGT = extGT[[
'HSVL_MS_S_Head_Pos_Veh_X', 'HSVL_MS_S_Head_Pos_Veh_Y', 'HSVL_MS_S_Head_Pos_Veh_Z',
'MS_S_Head_rot_X', 'MS_S_Head_rot_Y', 'MS_S_Head_rot_Z',
'MS_S_Gaze_rot_X', 'MS_S_Gaze_rot_Y', 'MS_S_Gaze_rot_Z',
'f_frame_counter_left_camera', 'HSVL_MS_CAN_S_Head_tracking_status',
'MS_S_Gaze_ROI_X_Raw', 'MS_S_Gaze_ROI_Y_Raw', 'CAN_S_Gaze_ROI', 'gt_s_gaze_roi_das'
]]
df_extGT = df_extGT.dropna()
# print('ret_ExtGT\n\n',ret_ExtGT)
print('df_extGT\n\n', df_extGT)
return df_extGT
def retcalcuate_head_eye_direction_short(extData):
print("//////////", funcname(), "//////////")
# print(extData)
extData['gt_name_gaze_roi'] = ""
extData['headDir_X_mid'] = 0
extData['headDir_Y_mid'] = 0
extData['headDir_Z_mid'] = 0
# extData['headDir_X_mid_rad'] = 0
# extData['headDir_Y_mid_rad'] = 0
# extData['headDir_Z_mid_rad'] = 0
for tindex in extData.index.values:
print(tindex)
tframecnt = extData.loc[tindex, 'f_frame_counter_left_camera']
# troi_result = extData.loc[tindex, 'gt_s_gaze_roi_das']
# troi_x = extData.loc[tindex, 'MS_S_Gaze_ROI_X_Raw']
# troi_y = extData.loc[tindex, 'MS_S_Gaze_ROI_Y_Raw']
thead_pos = np.array((extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_X'], extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_Y'], extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_Z']))
thead_rot = np.array((extData.loc[tindex, 'MS_S_Head_rot_X'], extData.loc[tindex, 'MS_S_Head_rot_Y'], extData.loc[tindex, 'MS_S_Head_rot_Z']))
tgaze_vec_mid = np.array((extData.loc[tindex, 'MS_S_Gaze_rot_X'], extData.loc[tindex, 'MS_S_Gaze_rot_Y'], extData.loc[tindex, 'MS_S_Gaze_rot_Z']))
# print(tframecnt, troi_result, troi_x, troi_y, thead_pos, thead_rot, tgaze_vec_mid)
print(tframecnt, thead_pos, thead_rot, tgaze_vec_mid)
# print(tframecnt, troi_result, troi_x, troi_y)
headPos3D_mm = thead_pos
# headOri_radian = thead_rot * deg2Rad
headOri_radian = np.array([0,0,0]) * deg2Rad
print("headPos3D_mm", headPos3D_mm)
print("headOri_radian", headOri_radian)
mideye_roll_pitch_yaw_rad = tgaze_vec_mid * deg2Rad
# print("eulerAngles\n", eulerAnglesToRotationMatrix(lpupil_roll_pitch_yaw_rad))
rt_2 = np.dot(eulerAnglesToRotationMatrix(np.array([0, 0, math.pi])), np.array([1, 1, 1])).round(5)
rt = eulerAnglesToRotationMatrix(headOri_radian * rt_2)
rot2_mid = eulerAnglesToRotationMatrix(mideye_roll_pitch_yaw_rad)
print('rot2_mid',rot2_mid)
headDir_mid = np.dot(rot2_mid, np.dot(rt, [1, 0, 0]))
# headDir_mid = np.dot(np.dot(rot2_mid , rt), [1,0,0])
print('headDir_mid',headDir_mid)
extData.loc[tindex, 'headDir_X_mid'] = headDir_mid[0]
extData.loc[tindex, 'headDir_Y_mid'] = headDir_mid[1]
extData.loc[tindex, 'headDir_Z_mid'] = headDir_mid[2]
# ccc = changeRotation_unitvec2radian('RPY', headDir_mid, 'RPY') * rad2Deg
# print('ccc',ccc)
# extData.loc[tindex,'headDir_X_mid_rad'] = ccc[0]
# extData.loc[tindex,'headDir_Y_mid_rad'] = ccc[1]
# extData.loc[tindex,'headDir_Z_mid_rad'] = ccc[2]
return extData
def calc_match_roi(p0, p1, p3, p2, camPlaneOrthVector, pointOnPlan, headDir, headPos):
# tview_point = intersectionWithPlan(headPos, headDir, camPlaneOrthVector, pointOnPlan)
# print(' ', 'tview_point', tview_point)
tview_point2 = bcheck_match.line_plane_collision(camPlaneOrthVector, pointOnPlan, headDir, headPos)
print("tview_point2", tview_point2)
ret_match = bcheck_match.check_available_point_on_plane(p0, p1, p3, p2, tview_point2)
head_vector = np.dot(eulerAnglesToRotationMatrix(np.array([0, 0, math.pi])), headDir).round(5)
ret_sameDirect = bcheck_match.is_same_direction(tview_point2, head_vector, headPos)
print("ret_match", ret_match, 'ret_sameDirect', ret_sameDirect)
# print('각도', changeRotation_unitvec2radian_check2('RPY', headDir, 'RPY') * rad2Deg)
if (ret_match == True and ret_sameDirect == True):
return True, tview_point2
elif (ret_match == False and ret_sameDirect == True):
return False, tview_point2
return False, np.array([0,0,0])
def calc_score(roi_center, roi_one_of_points, target_point):
# calc 1 - (dist(target_point - roi_center) / dist(roi_one_of_points - roi_center))
dist1 = distance_xyz(roi_center, target_point)
dist2 = distance_xyz(roi_center, roi_one_of_points)
result = np.round(1 - (dist1/dist2),2)
return result
def check_match_roi(extData, ret_ExtROI, errDist = 0):
extData['roi_idx_h'] = ""
extData['roi_name_h'] = ""
extData['roi_X'] = 0
extData['roi_Y'] = 0
extData['intersect_x_h'] = 0
extData['intersect_y_h'] = 0
extData['intersect_z_h'] = 0
extData['roi_score'] = ""
for tindex in extData.index.values:
print(tindex,"번째 index, frameID = ", extData.loc[tindex, 'f_frame_counter_left_camera'],'\n')
headDir_mid = np.array((extData.loc[tindex, 'headDir_X_mid'], extData.loc[tindex, 'headDir_Y_mid'], extData.loc[tindex, 'headDir_Z_mid']))
headPos = np.array((extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_X'], extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_Y'], extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_Z']))
roi_idx_origin = extData.loc[tindex, 'gt_s_gaze_roi_das']
for tidx2 in ret_ExtROI.index.values:
troi_id = ret_ExtROI["tID"][tidx2]
troi_name = ret_ExtROI["tTargetName"][tidx2]
if(roi_idx_origin == troi_id):
extData.loc[tindex, 'gt_name_gaze_roi'] = troi_name
break
max_target_id = "0"
max_target_name = "UNKOWN"
max_target_point = np.array([0,0,0])
max_target_roi_x = 0
max_target_roi_y = 0
max_target_roi_score = 0
for tidx in ret_ExtROI.index.values:
offset = 0
# print(tidx)
# print(ret_ExtROI['tID'], ret_ExtROI['tTargetName'], ret_ExtROI['ttop_left'], ret_ExtROI['ttop_right'], ret_ExtROI['tbottom_left'], ret_ExtROI['tbottom_right'])
print(' ',tidx, ret_ExtROI['tID'][tidx], ret_ExtROI['tTargetName'][tidx])
troi_id = ret_ExtROI["tID"][tidx]
troi_name = ret_ExtROI["tTargetName"][tidx]
if(troi_id == 7 ):
offset = 135+ 40 + 5 + 10 + 10 + 10 + 10 + 5
elif (troi_id == 8):
offset = 170+40
elif(troi_id == 9):
offset = 60+ 40 + 20 + 25 + 20 + 20 + 10 + 15
elif(troi_id == 1):
offset = 80 + 0 + 5 + 10 + 20 + 10 +20 + 20 + 15
elif (troi_id == 3 or troi_id == 4): # or troi_id == 5
offset = 80
elif (troi_id == 5):
offset = 60 + 10
elif (troi_id == 6):
offset = 25 + 15 + 15 + 20 + 20 + 10 + 20 + 20
elif (troi_id == 14):
offset = 25 + 15 + 0 + 5
elif (troi_id == 19):
offset = 25 + 15 + 0 + 5 + 0 + 0 + 5
elif (troi_id == 16):
offset = 25 + 15 + 0 + 5 + 10 + 10
elif (troi_id == 11):
offset = 25 + 15 + 0 + -5
elif (troi_id == 10):
offset = 25 + 0 + 0 + 10 + 10 + 10 + 5
else:
offset = errDist
p0 = np.array(ret_ExtROI["ttop_left"][tidx]) * 1000 + np.array([0,-offset,offset])
p1 = np.array(ret_ExtROI["ttop_right"][tidx]) * 1000 + np.array([0,offset,offset])
p2 = np.array(ret_ExtROI["tbottom_left"][tidx]) * 1000 + np.array([0,-offset,-offset])
p3 = np.array(ret_ExtROI["tbottom_right"][tidx]) * 1000 + np.array([0,offset,-offset])
camPlaneOrthVector = np.cross((p3 - p1), (p2 - p3))/np.linalg.norm(np.cross((p3 - p1), (p2 - p3)))
pointOnPlan = (p0+p1+p2+p3)/4
print(' ',"p0", p0, "\n p1",p1, "\n p2", p2, "\n p3", p3)
print(' ','headPos',headPos)
print(' ','headDir_mid', headDir_mid)
print(' ','camPlaneOrthVector',camPlaneOrthVector)
print(' ','pointOnPlan',pointOnPlan)
ret_check, point_mapping = calc_match_roi(p0, p1, p3, p2, camPlaneOrthVector, pointOnPlan, headDir_mid, headPos)
if(ret_check == True):
if(point_mapping[0] != 0 or point_mapping[1] != 0 or point_mapping[2] != 0):
target_roi_score = calc_score(pointOnPlan, p0, [point_mapping[0], point_mapping[1], point_mapping[2]])
if(max_target_roi_score < target_roi_score):
max_target_roi_score = target_roi_score
max_target_id = str(troi_id)
max_target_name = troi_name
max_target_point = point_mapping
max_target_roi_x = int(bcheck_match.line_point_min_dist(point_mapping, p0, p2) / distance_xyz(p0, p1) * 100)
max_target_roi_y = int(bcheck_match.line_point_min_dist(point_mapping, p0, p1) / distance_xyz(p0,p2) * 100)
# if(ret_check == True):
# extData.loc[tindex, 'roi_idx_h'] = str(extData.loc[tindex, 'roi_idx_h']) + '/' + str(troi_id)
# extData.loc[tindex, 'roi_name_h'] = extData.loc[tindex, 'roi_name_h'] + '/' + troi_name
# # extData.loc[tindex, 'roi_name_h'] = troi_name
# extData.loc[tindex, 'intersect_x_h'] = point_mapping[0]
# extData.loc[tindex, 'intersect_y_h'] = point_mapping[1]
# extData.loc[tindex, 'intersect_z_h'] = point_mapping[2]
# extData.loc[tindex, 'roi_X'] = int(bcheck_match.line_point_min_dist(point_mapping, p0, p2) / distance_xyz(p0, p1) * 100)
# extData.loc[tindex, 'roi_Y'] = int(bcheck_match.line_point_min_dist(point_mapping, p0, p1) / distance_xyz(p0,p2) * 100)
# extData.loc[tindex, 'roi_score'] = str(extData.loc[tindex, 'roi_score']) + '/' + str(calc_score(pointOnPlan, p0, [point_mapping[0], point_mapping[1], point_mapping[2]]))
# # break
print('\n')
extData.loc[tindex, 'roi_idx_h'] = max_target_id
extData.loc[tindex, 'roi_name_h'] = max_target_name
extData.loc[tindex, 'intersect_x_h'] = max_target_point[0]
extData.loc[tindex, 'intersect_y_h'] = max_target_point[1]
extData.loc[tindex, 'intersect_z_h'] = max_target_point[2]
extData.loc[tindex, 'roi_X'] = max_target_roi_x
extData.loc[tindex, 'roi_Y'] = max_target_roi_y
extData.loc[tindex, 'roi_score'] = max_target_roi_score
return extData
def distance_xyz(a,b):
temp = a - b
dist = np.sqrt(temp[0] * temp[0] + temp[1] * temp[1] + temp[2] * temp[2])
return dist
def rendering_roi_with_head_gaze(pROI, extData):
fig = plt.figure(figsize=(10,8))
ax3 = fig.add_subplot(111, projection='3d')
plt.title('3D Target ROI')
# for i in pROI:
# print(i)
for i in pROI.index[0:-1]:
# print(pROI.tID[i])
# print(pROI.tTargetName[i])
# print(pROI.ttop_left[i][0],pROI.ttop_left[i][1],pROI.ttop_left[i][2])
# print(pROI.ttop_right[i])
# print(pROI.tbottom_left[i])
# print(pROI.tbottom_right[i])
x0 = pROI.ttop_left[i][0] * 1000
y0 = pROI.ttop_left[i][1] * 1000
z0 = pROI.ttop_left[i][2] * 1000
# ax3.scatter(xs=x, ys=y, zs=z, label=i[1])
x1 = pROI.ttop_right[i][0] * 1000
y1 = pROI.ttop_right[i][1] * 1000
z1 = pROI.ttop_right[i][2] * 1000
# ax3.scatter(xs=x, ys=y, zs=z, label=i[1])
x2 = pROI.tbottom_left[i][0] * 1000
y2 = pROI.tbottom_left[i][1] * 1000
z2 = pROI.tbottom_left[i][2] * 1000
# ax3.scatter(xs=x, ys=y, zs=z, label=i[1])
x3 = pROI.tbottom_right[i][0] * 1000
y3 = pROI.tbottom_right[i][1] * 1000
z3 = pROI.tbottom_right[i][2] * 1000
# print([x0,x1,x3,x2])
ax3.scatter(xs=np.array([x0,x1,x3,x2]), ys=np.array([y0,y1,y3,y2]), zs=np.array([z0,z1,z3,z2]) )
ax3.plot([x0,x1,x3,x2,x0], [y0,y1,y3,y2,y0], [z0,z1,z3,z2,z0], label=str("%.2d_"%pROI.tID[i])+pROI.tTargetName[i])
for tindex in extData.index.values:
# print(tindex, "번째 index, frameID = ",extData.loc[tindex, 'f_frame_counter_left_camera'], extData.loc[tindex, 'intersect_x_h'],extData.loc[tindex, 'intersect_y_h'],extData.loc[tindex, 'intersect_z_h'], '\n')
h_x = extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_X']
h_y = extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_Y']
h_z = extData.loc[tindex, 'HSVL_MS_S_Head_Pos_Veh_Z']
in_x = extData.loc[tindex, 'intersect_x_h']
in_y = extData.loc[tindex, 'intersect_y_h']
in_z = extData.loc[tindex, 'intersect_z_h']
# ax3.scatter(xs=np.array([h_x, in_x]), ys=np.array([h_y, in_y]), zs=np.array([h_z, in_z]), s=50, c='r')
ax3.scatter(xs=np.array([h_x]), ys=np.array([h_y]), zs=np.array([h_z]), s=50, c='r')
ax3.scatter(xs=np.array([in_x]), ys=np.array([in_y]), zs=np.array([in_z]), s=10, c='b')
ax3.plot([h_x, in_x], [h_y, in_y], [h_z, in_z] ) #label=str(extData.loc[tindex, 'f_frame_counter_left_camera'])
# ax3.scatter(xs=np.array([h_x0, x1, x3, x2]), ys=np.array([y0, y1, y3, y2]), zs=np.array([z0, z1, z3, z2]))
# print(1/0)
# for ii in extData.index:
# print(ii)
# tview_point2[0]
ax3.set_zlim(-1000, 1000)
ax3.set_title("3D Target ROI")
ax3.set_xlabel('veh X', fontsize=16)
ax3.set_ylabel('veh Y', fontsize=16)
ax3.set_zlabel('veh Z', fontsize=16)
ax3.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))
ax3.view_init(5, -10)
plt.show()
pass
def save_csvfile(tdatas, filename):
print("//////////", funcname(), "//////////")
if (tdatas.empty is True):
print("저장할 데이터가 없습니다.")
return
tdata = tdatas.copy()
tfile = os.path.splitext(filename)
for num in range(100):
tfilename = '%s' % (tfile[len(tfile) - 2]) + '%03d' % (num) + tfile[len(tfile) - 1]
if not os.path.exists(tfilename):
break
print("파일을 저장합니다.", tfilename)
tdata.to_csv(tfilename, mode='w', index=False, header=True, sep=',', quotechar=" ", float_format='%.4f')
pass
def policy_gaze_roi_accuracy(tdata, text_column):
tdata['hit_green_roi'] = "None"
tdata['hit_amber_roi'] = "None"
roi_group_green = {1: [1], 3: [3,4], 4: [3,4], 5: [5,9], 6:[6], 7:[7], 8:[8], 9:[9], 10:[10], 11:[11,19],
12:[12, 13], 14:[14, 12], 15:[15], 16:[16], 17:[17], 19:[19, 11]}
roi_group_amber = {1: [1,4,6,13], 3: [1,3,4,5,11,13,19], 4: [1,3,4,5,11,13,19], 5: [4,5,9,11,13,17,19], 6:[1,6,10,12,13,18,20], 7:[7,13,14,15],
8: [5,8,10,13,16,17], 9:[4,5,9,11,19], 10:[6,8,10,13,16,17,18], 11:[4,5,9,11,15,17,19],
12:[1,6,12,13,14,20], 14:[7,12,13,14,15], 15:[7,14,15], 16:[8,10,16,17,18,20], 17:[5,8,16,17], 19:[4,5,9,11,15,17,19]}
for idx in tdata.index.values:
# print(idx, 'index')
# tdata.loc()
tvalue = tdata.loc[idx, text_column]
t_gt = tdata.loc[idx, 'gt_s_gaze_roi_das']
# print(t_gt)
try:
fcheck = False
for i, tkey in enumerate(roi_group_green[t_gt]):
# print(i, tkey)
if(tkey == tvalue):
fcheck = True
break
if(fcheck == True):
tdata.loc[idx, 'hit_green_roi'] = "TRUE"
else:
tdata.loc[idx, 'hit_green_roi'] = "FALSE"
except KeyError:
print("Skip...", KeyError)
try:
fcheck = False
for i, tkey in enumerate(roi_group_amber[t_gt]):
# print(i, tkey)
if(tkey == tvalue):
fcheck = True
break
if(fcheck == True):
tdata.loc[idx, 'hit_amber_roi'] = "TRUE"
else:
tdata.loc[idx, 'hit_amber_roi'] = "FALSE"
except KeyError:
print("Skip...", KeyError)
# print(1/0)
print(tdata)
return tdata
def counting_gaze_roi(tdata):
# tdata['hit_green_roi'] = "None"
# tdata['hit_amber_roi'] = "None"
# tdata['hit_amber_roi'] = "None"
# 'gt_s_gaze_roi_das', 'Load_file'
print('unique', tdata['gt_s_gaze_roi_das'].unique())
print('value_counts', tdata['gt_s_gaze_roi_das'].value_counts())
# print(tdata[(tdata['hit_green_roi'] == 'TRUE') & (tdata['gt_s_gaze_roi_das'] == 1)])
print(tdata[(tdata['hit_amber_roi'] == 'TRUE') & (tdata['gt_s_gaze_roi_das'] == 1)])
for i in tdata['gt_s_gaze_roi_das'].unique():
print()
tcount_green = tdata[(tdata['gt_s_gaze_roi_das'] == i)]['hit_green_roi'].count()
tpass_green = tdata[(tdata['hit_green_roi'] == 'TRUE') & (tdata['gt_s_gaze_roi_das'] == i) ]['hit_green_roi'].count()
print('green roi',i,' - ',tpass_green, '/' , tcount_green, '={:.2f}'.format(tpass_green/tcount_green*100), '%')
tcount_amber = tdata[(tdata['gt_s_gaze_roi_das'] == i)]['hit_amber_roi'].count()
tpass_amber = tdata[(tdata['hit_amber_roi'] == 'TRUE') & (tdata['gt_s_gaze_roi_das'] == i) ]['hit_amber_roi'].count()
print('amber roi',i,' - ',tpass_amber, '/' , tcount_amber, '={:.2f}'.format(tpass_amber/tcount_amber*100), '%')
# print(tcount_amber, " ", tpass_amber)
# print(1 / 0)
# tpass_amber = tdata[(tdata['hit_amber_roi'] == 'TRUE') & (tdata['gt_s_gaze_roi_das'] == i) & (tdata['hit_amber_roi'] == 'TRUE')].count()
# print(tpass_amber, '/' , tcount_amber, '=', tpass_amber/tcount_amber*100, '%')
# df_sort[(df_sort['title'] == tTitle) & (df_sort['compare_group'] == tGcomp)]
# tdata[
pass
if __name__ == '__main__':
print("\n\n\n test/////////////////////")
if(0):
sys.stdout = open('DebugLog.txt', 'w')
fold_names = filedialog.askdirectory()
files_to_replace_base = []
if (1):
for dirpath, dirnames, filenames in os.walk(fold_names):
for filename in [f for f in filenames if f.endswith(".csv")]:
files_to_replace_base.append(os.path.join(dirpath, filename))
print(os.path.join(dirpath, filename))
# if (filename.__contains__("GT_") == True):
# files_to_replace_base.append(os.path.join(dirpath, filename))
# print(os.path.join(dirpath, filename))
# elif (filename.__contains__("DisplayCenter") == True):
# files_to_replace.append(os.path.join(dirpath, filename))
# print(os.path.join(dirpath, filename))
print(len(files_to_replace_base))
if(len(files_to_replace_base)== 0):
print("No select file..!!!")
print(1/0)
# files_to_replace_target = files_to_replace_base.copy()
print("*" * 50)
print(sorted(files_to_replace_base,key=lambda x: str(x).split() ))
print(files_to_replace_base)
# print(1/0)
inputPath_ROI = "./refer/roi_config_eva5.json"
# roi_config.json
ret_roi = load_jsonfile_ROI(inputPath_ROI)
ret_ExtROI = extract_availData_from_3D_target_ROI(ret_roi)
test = ['D:/Project/CVT/demo/ROI_GT/3810(EVA2DAS_GazeROI)\\3810_285_812238_0001_all.csv', 'D:/Project/CVT/demo/ROI_GT/3810(EVA2DAS_GazeROI)\\3810_2860_817361_0001_all.csv']
test1 = ['D:\Source\convert_head_pos_and_gaze_roi/refer\GT/3810_8600_827980_0001_all_19.csv']
test2 = ['./refer/GT_3531_96_670222_0001_all.csv']
df_merge = pd.DataFrame()
if(1):
for i, tname in enumerate(files_to_replace_base):
ttext = str(i) + '/' + str(len(files_to_replace_base)) +' - ' + os.path.basename(tname)
print_current_time(ttext)
# print('\n',i,'/',len(files_to_replace_base), tname)
# print(1/0)
inputPath_GT = tname
ret_ExtGT = extract_availData_from_GT_short(inputPath_GT)
ret_ExtGT_with_direction = retcalcuate_head_eye_direction_short(ret_ExtGT)
# print('\n\n', ret_ExtGT_with_direction)
ret_match = check_match_roi(ret_ExtGT_with_direction, ret_ExtROI, 25) # 150
ret_match['Load_file'] = os.path.basename(tname)
# print('ret_match', ret_match)
df_merge = pd.concat([df_merge, ret_match]).reset_index(drop=True)
# save_csvfile(df_merge, 'save_output.csv')
# print(1/0)
print("df_merge",df_merge)
df_merge = df_merge.astype({'roi_idx_h':"int64", "gt_s_gaze_roi_das":"int64"})
df_merge['hit'] = (df_merge['roi_idx_h'] == df_merge['gt_s_gaze_roi_das'])
print("***Final hit accuracy\nTrue={}개, Total={}개, {}%".format(df_merge['hit'].value_counts()[1], df_merge['hit'].size, df_merge['hit'].value_counts()[1]/df_merge['hit'].size*100))
df_data2 = policy_gaze_roi_accuracy(df_merge, 'roi_idx_h')
counting_gaze_roi(df_data2)
save_csvfile(df_data2, 'save_output.csv')
# save_csvfile(df_merge, "./accuracy_output.csv")
# rendering_roi_with_head_gaze(ret_ExtROI, df_merge)
# print(1/0)