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calc_gaze_acc2.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 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
def load_jsonfile_ROI(fname):
print("//////////", funcname(), "//////////")
fp = open(fname)
fjs = json.load(fp)
fp.close()
# print(fjs)
return fjs
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 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(available_dict) # index 지정
print(available_df)
return available_df
def extract_availData_from_GT_and_result(inputPath_GT):
print("//////////", funcname(), "//////////")
extGT = pd.read_csv(inputPath_GT)
df_extGT = extGT[[
'CAN_S_Gaze_ROI', 'gt_s_gaze_roi_das', 'gt_name_gaze_roi', 'roi_idx_h','roi_name_h',
'max_target_id', 'max_roi_score', 'Load_file'
]]
df_extGT = df_extGT.dropna()
df_extGT = df_extGT.sort_values(['gt_s_gaze_roi_das', 'Load_file'], ascending=(True, True))
# print('df_extGT\n\n', df_extGT)
return df_extGT
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
if __name__ == '__main__':
print("\n\n\n test/////////////////////")
if(0):
sys.stdout = open('DebugLog.txt', 'w')
inputfile = "./save_output023.csv"
df_data = extract_availData_from_GT_and_result(inputfile)
df_data = df_data.astype({'max_roi_score': "int64", "gt_s_gaze_roi_das":"int64"})
df_data2 = policy_gaze_roi_accuracy(df_data, 'max_roi_score') #max_target_id
counting_gaze_roi(df_data2)
save_csvfile(df_data2, 'save2_output.csv')
print(1/0)
# 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)
inputPath_ROI = "./refer/roi_config_eva.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) # 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)
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))
save_csvfile(df_merge, "./accuracy_output.csv")
# rendering_roi_with_head_gaze(ret_ExtROI, df_merge)
print(1/0)
# inputPath_GT = "./refer/GT_3531_96_670222_0001_all.csv"
# inputPath_GT = "./refer/GT_3531_96_670222_0001_small.csv"
# inputPath_GT = "./refer/GT_3531_96_670222_0001_mix.csv"
inputPath_GT = "./refer/GT/3810_10_811709_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_20_811728_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_30_811746_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_40_811766_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_50_811786_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_70_811824_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_60_811805_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_80_811843_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_80_811843_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_80_811843_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_90_811862_0001_all.csv"
# inputPath_GT = "./refer/GT/3810_100_811882_0001_all.csv"
ret_ExtGT = extract_availData_from_GT_short(inputPath_GT)
# print('ret_ExtGT\n\n', ret_ExtGT)
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, 0) #150
# save_csvfile(ret_match, "./accuracy_output.csv")
# ret_match.to_csv("filename.csv", mode='w', index=False, header=False, sep=',', quotechar=" ",
# float_format='%.4f')
# rendering_roi_with_head_gaze(ret_ExtROI, ret_match)
# ret_match.to_csv("filename.csv", mode='w', index=False, header=False, sep=',', quotechar=" ", float_format='%.4f')
# print(1/0)