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王庆刚
2024-11-25 18:05:08 +08:00
parent c47894ddc0
commit 8bbee310ba
109 changed files with 1003 additions and 305 deletions
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contrast/one2one_onsite.py
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@ -7,7 +7,12 @@ Created on Wed Sep 11 11:57:30 2024
"""
import os
import numpy as np
from pathlib import Path
import matplotlib.pyplot as plt
import sys
sys.path.append(r"D:\DetectTracking")
from tracking.utils.read_data import read_similar
def read_one2one_data(filepath):
simiList = []
@ -85,7 +90,7 @@ def plot_pr_curve(matrix):
pass
def main():
def test_compare():
filepaths = [r"\\192.168.1.28\share\测试_202406\0913_扫A放B\0913_1\OneToOneCompare.txt",
r"\\192.168.1.28\share\测试_202406\0913_扫A放B\0913_2\OneToOneCompare.txt",
r"\\192.168.1.28\share\测试_202406\0914_扫A放B\0914_1\OneToOneCompare.txt",
@ -99,10 +104,251 @@ def main():
plot_pr_curve(simiList)
def one2one_pr(paths):
paths = Path(paths)
evtpaths = [p for p in paths.iterdir() if p.is_dir() and len(p.name.split('_'))>=2]
events, similars = [], []
##===================================== 扫A放A, 扫A放B场景
one2oneAA, one2oneAB = [], []
##===================================== 应用于展厅 1：N
tp_events, fn_events, fp_events, tn_events = [], [], [], []
tp_simi, fn_simi, tn_simi, fp_simi = [], [], [], []
##===================================== 应用于1:n
tpevents, fnevents, fpevents, tnevents = [], [], [], []
tpsimi, fnsimi, tnsimi, fpsimi = [], [], [], []
for path in evtpaths:
barcode = path.stem.split('_')[-1]
datapath = path.joinpath('process.data')
if not barcode.isdigit() or len(barcode)<10: continue
if not datapath.is_file(): continue
try:
SimiDict = read_similar(datapath)
except Exception as e:
print(f"{path.stem}, Error: {e}")
one2one = SimiDict['one2one']
one2n = SimiDict['one2n']
barcodes, similars = [], []
for dt in one2one:
barcodes.append(dt['barcode'])
similars.append(dt['similar'])
if len(barcodes)!=len(similars) or len(barcodes)==0:
continue
##===================================== 扫A放A, 扫A放B场景
simAA = [similars[i] for i in range(len(barcodes)) if barcodes[i]==barcode]
simAB = [similars[i] for i in range(len(barcodes)) if barcodes[i]!=barcode]
one2oneAA.extend(simAA)
one2oneAB.extend(simAB)
##===================================== 以下应用适用于展厅 1：N
max_idx = similars.index(max(similars))
max_sim = similars[max_idx]
# max_bcd = barcodes[max_idx]
for i in range(len(one2one)):
bcd, simi = barcodes[i], similars[i]
if bcd==barcode and simi==max_sim:
tp_simi.append(simi)
tp_events.append(path.stem)
elif bcd==barcode and simi!=max_sim:
fn_simi.append(simi)
fn_events.append(path.stem)
elif bcd!=barcode and simi!=max_sim:
tn_simi.append(simi)
tn_events.append(path.stem)
else:
fp_simi.append(simi)
fp_events.append(path.stem)
##===================================== 以下应用适用1:n
events, evt_barcodes, evt_similars, evt_types = [], [], [], []
for dt in one2n:
events.append(dt["event"])
evt_barcodes.append(dt["barcode"])
evt_similars.append(dt["similar"])
evt_types.append(dt["type"])
if len(events)!=len(evt_barcodes) or len(evt_barcodes)!=len(evt_similars) \
or len(evt_barcodes)!=len(evt_similars) or len(events)==0: continue
maxsim = evt_similars[evt_similars.index(max(evt_similars))]
for i in range(len(one2n)):
bcd, simi = evt_barcodes[i], evt_similars[i]
if bcd==barcode and simi==maxsim:
tpsimi.append(simi)
tpevents.append(path.stem)
elif bcd==barcode and simi!=maxsim:
fnsimi.append(simi)
fnevents.append(path.stem)
elif bcd!=barcode and simi!=maxsim:
tnsimi.append(simi)
tnevents.append(path.stem)
else:
fpsimi.append(simi)
fpevents.append(path.stem)
'''命名规则:
1:1 1:n 1:N
TP_ TP TPX
PPrecise_ PPrecise PPreciseX
tpsimi tp_simi
'''
''' 1:1 数据存储'''
PPrecise_, PRecall_ = [], []
NPrecise_, NRecall_ = [], []
''' 1:n 数据存储'''
PPrecise, PRecall = [], []
NPrecise, NRecall = [], []
''' 展厅 1:N 数据存储'''
PPreciseX, PRecallX = [], []
NPreciseX, NRecallX = [], []
Thresh = np.linspace(-0.2, 1, 100)
for th in Thresh:
'''============================= 1:1'''
TP_ = sum(np.array(one2oneAA) >= th)
FP_ = sum(np.array(one2oneAB) >= th)
FN_ = sum(np.array(one2oneAA) < th)
TN_ = sum(np.array(one2oneAB) < th)
PPrecise_.append(TP_/(TP_+FP_+1e-6))
PRecall_.append(TP_/(TP_+FN_+1e-6))
NPrecise_.append(TN_/(TN_+FN_+1e-6))
NRecall_.append(TN_/(TN_+FP_+1e-6))
'''============================= 1:n'''
TP = sum(np.array(tpsimi) >= th)
FP = sum(np.array(fpsimi) >= th)
FN = sum(np.array(fnsimi) < th)
TN = sum(np.array(tnsimi) < th)
PPrecise.append(TP/(TP+FP+1e-6))
PRecall.append(TP/(TP+FN+1e-6))
NPrecise.append(TN/(TN+FN+1e-6))
NRecall.append(TN/(TN+FP+1e-6))
'''============================= 1:N 展厅'''
TPX = sum(np.array(tp_simi) >= th)
FPX = sum(np.array(fp_simi) >= th)
FNX = sum(np.array(fn_simi) < th)
TNX = sum(np.array(tn_simi) < th)
PPreciseX.append(TPX/(TPX+FPX+1e-6))
PRecallX.append(TPX/(TPX+FNX+1e-6))
NPreciseX.append(TNX/(TNX+FNX+1e-6))
NRecallX.append(TNX/(TNX+FPX+1e-6))
'''============================= 1:1 曲线'''
fig, ax = plt.subplots()
ax.plot(Thresh, PPrecise_, 'r', label='Precise_Pos: TP/TPFP')
ax.plot(Thresh, PRecall_, 'b', label='Recall_Pos: TP/TPFN')
ax.plot(Thresh, NPrecise_, 'g', label='Precise_Neg: TN/TNFP')
ax.plot(Thresh, NRecall_, 'c', label='Recall_Neg: TN/TNFN')
ax.set_xlim([0, 1])
ax.set_ylim([0, 1])
ax.grid(True)
ax.set_title('Precise & Recall')
ax.set_xlabel(f"Num: {len(evtpaths)}")
ax.legend()
plt.show()
'''============================= 1:1 直方图'''
fig, axes = plt.subplots(2, 1)
axes[0].hist(np.array(one2oneAA), bins=60, edgecolor='black')
axes[0].set_xlim([-0.2, 1])
axes[0].set_title('AA')
axes[1].hist(np.array(one2oneAB), bins=60, edgecolor='black')
axes[1].set_xlim([-0.2, 1])
axes[1].set_title('BB')
plt.show()
'''============================= 1:n 曲线'''
fig, ax = plt.subplots()
ax.plot(Thresh, PPrecise, 'r', label='Precise_Pos: TP/TPFP')
ax.plot(Thresh, PRecall, 'b', label='Recall_Pos: TP/TPFN')
ax.plot(Thresh, NPrecise, 'g', label='Precise_Neg: TN/TNFP')
ax.plot(Thresh, NRecall, 'c', label='Recall_Neg: TN/TNFN')
ax.set_xlim([0, 1])
ax.set_ylim([0, 1])
ax.grid(True)
ax.set_title('Precise & Recall')
ax.set_xlabel(f"Num: {len(evtpaths)}")
ax.legend()
plt.show()
'''============================= 1:n 直方图'''
fig, axes = plt.subplots(2, 2)
axes[0, 0].hist(tpsimi, bins=60, edgecolor='black')
axes[0, 0].set_xlim([-0.2, 1])
axes[0, 0].set_title('TP')
axes[0, 1].hist(fpsimi, bins=60, edgecolor='black')
axes[0, 1].set_xlim([-0.2, 1])
axes[0, 1].set_title('FP')
axes[1, 0].hist(tnsimi, bins=60, edgecolor='black')
axes[1, 0].set_xlim([-0.2, 1])
axes[1, 0].set_title('TN')
axes[1, 1].hist(fnsimi, bins=60, edgecolor='black')
axes[1, 1].set_xlim([-0.2, 1])
axes[1, 1].set_title('FN')
plt.show()
'''============================= 1:N 展厅 曲线'''
fig, ax = plt.subplots()
ax.plot(Thresh, PPreciseX, 'r', label='Precise_Pos: TP/TPFP')
ax.plot(Thresh, PRecallX, 'b', label='Recall_Pos: TP/TPFN')
ax.plot(Thresh, NPreciseX, 'g', label='Precise_Neg: TN/TNFP')
ax.plot(Thresh, NRecallX, 'c', label='Recall_Neg: TN/TNFN')
ax.set_xlim([0, 1])
ax.set_ylim([0, 1])
ax.grid(True)
ax.set_title('Precise & Recall')
ax.set_xlabel(f"Num: {len(evtpaths)}")
ax.legend()
plt.show()
'''============================= 1:N 展厅 直方图'''
fig, axes = plt.subplots(2, 2)
axes[0, 0].hist(tp_simi, bins=60, edgecolor='black')
axes[0, 0].set_xlim([-0.2, 1])
axes[0, 0].set_title('TP')
axes[0, 1].hist(fp_simi, bins=60, edgecolor='black')
axes[0, 1].set_xlim([-0.2, 1])
axes[0, 1].set_title('FP')
axes[1, 0].hist(tn_simi, bins=60, edgecolor='black')
axes[1, 0].set_xlim([-0.2, 1])
axes[1, 0].set_title('TN')
axes[1, 1].hist(fn_simi, bins=60, edgecolor='black')
axes[1, 1].set_xlim([-0.2, 1])
axes[1, 1].set_title('FN')
plt.show()
print('Done!')
if __name__ == "__main__":
main()
evtpaths = r"\\192.168.1.28\share\测试视频数据以及日志\各模块测试记录\展厅测试\1120_展厅模型v801测试\扫A放A"
one2one_pr(evtpaths)