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20241217

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This commit is contained in:
王庆刚
2024-12-17 17:32:09 +08:00
parent afd033b965
commit 39f94c7bd4
11 changed files with 768 additions and 250 deletions
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398
contrast/one2one_onsite.py
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@ -105,27 +105,56 @@ def test_compare():
plot_pr_curve(simiList)
def one2one_pr(paths):
'''
1:1
'''
paths = Path(paths)
# evtpaths = [p for p in paths.iterdir() if p.is_dir() and len(p.name.split('_'))>=2]
evtpaths = [p for p in paths.iterdir() if p.is_dir()]
evtpaths = []
for p in paths.iterdir():
condt1 = p.is_dir()
condt2 = len(p.name.split('_'))>=2
condt3 = len(p.name.split('_')[-1])>8
condt4 = p.name.split('_')[-1].isdigit()
if condt1 and condt2 and condt3 and condt4:
evtpaths.append(p)
# evtpaths = [p for p in paths.iterdir() if p.is_dir() and len(p.name.split('_'))>=2 and len(p.name.split('_')[-1])>8]
# evtpaths = [p for p in paths.iterdir() if p.is_dir()]
events, similars = [], []
##===================================== 扫A放A, 扫A放B场景
##===================================== 扫A放A, 扫A放B场景()
one2oneAA, one2oneAB = [], []
one2SNAA, one2SNAB = [], []
##===================================== 应用于展厅 1：N
##===================================== 应用于 1：1
_tp_events, _fn_events, _fp_events, _tn_events = [], [], [], []
_tp_simi, _fn_simi, _tn_simi, _fp_simi = [], [], [], []
##===================================== 应用于 1：SN
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 = [], [], [], []
other_event, other_simi = [], []
##===================================== barcodes总数、比对错误事件
bcdList, one2onePath = [], []
bcdList = []
one2onePath, one2onePath1 = [], []
one2SNPath, one2SNPath1 = [], []
one2nPath = []
errorFile_one2one, errorFile_one2SN, errorFile_one2n = [], [], []
for path in evtpaths:
barcode = path.stem.split('_')[-1]
datapath = path.joinpath('process.data')
@ -140,51 +169,93 @@ def one2one_pr(paths):
except Exception as e:
print(f"{path.stem}, Error: {e}")
'''放入为 1:1，相似度取最大值；取出时为 1:SN, 相似度取均值'''
one2one = SimiDict['one2one']
one2SN = SimiDict['one2SN']
one2n = SimiDict['one2n']
'''================== 0. 1:1 ==================='''
barcodes, similars = [], []
for dt in one2one:
one2onePath.append((path.stem))
if dt['similar']==0:
one2onePath1.append((path.stem))
continue
barcodes.append(dt['barcode'])
similars.append(dt['similar'])
if len(barcodes)==len(similars) and len(barcodes)!=0:
## 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)
## 相似度排序，barcode相等且排名第一为TP，适用于多的barcode相似度比较
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)
elif bcd!=barcode and simi==max_sim and barcode in barcodes:
_fp_simi.append(simi)
_fp_events.append(path.stem)
else:
errorFile_one2one.append(path.stem)
'''================== 2. 取出场景下的 1 : Small N ==================='''
barcodes, similars = [], []
for dt in one2SN:
barcodes.append(dt['barcode'])
similars.append(dt['similar'])
if len(barcodes)!=len(similars) or len(barcodes)==0:
continue
if len(barcodes)==len(similars) and len(barcodes)!=0:
## 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]
##===================================== 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)
one2onePath.append(path.stem)
##===================================== 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]
if path.stem.find('100321')>0:
print("hhh")
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)
one2SNAA.extend(simAA)
one2SNAB.extend(simAB)
one2SNPath.append(path.stem)
if len(simAA)==0:
one2SNPath1.append(path.stem)
## 相似度排序，barcode相等且排名第一为TP，适用于多的barcode相似度比较
max_idx = similars.index(max(similars))
max_sim = similars[max_idx]
# max_bcd = barcodes[max_idx]
for i in range(len(one2SN)):
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)
elif bcd!=barcode and simi==max_sim and barcode in barcodes:
fp_simi.append(simi)
fp_events.append(path.stem)
else:
errorFile_one2SN.append(path.stem)
##===================================== 以下应用适用1:n
'''===================== 3. 取出场景下的 1:n ========================'''
events, evt_barcodes, evt_similars, evt_types = [], [], [], []
for dt in one2n:
events.append(dt["event"])
@ -192,92 +263,132 @@ def one2one_pr(paths):
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 len(events)==len(evt_barcodes) and len(evt_barcodes)==len(evt_similars) \
and len(evt_similars)==len(evt_types) and len(events)>0:
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)
elif bcd!=barcode and simi==maxsim:
fpsimi.append(simi)
fpevents.append(path.stem)
else:
other_simi.append(simi)
other_event.append(path.stem)
one2nPath.append(path.stem)
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)
elif bcd!=barcode and simi==maxsim and barcode in evt_barcodes:
fpsimi.append(simi)
fpevents.append(path.stem)
else:
errorFile_one2n.append(path.stem)
'''命名规则:
1:1 1:n 1:N
TP_ TP TPX
PPrecise_ PPrecise PPreciseX
tpsimi tp_simi
1:1 (max) 1:1 (max) 1:n 1:N
_TP TP_ TP TPX
_PPrecise PPrecise_ PPrecise PPreciseX
tpsimi tp_simi
'''
''' 1:1 数据存储'''
''' 1:1 数据存储, 相似度计算方式：最大值、均值'''
_PPrecise, _PRecall = [], []
_NPrecise, _NRecall = [], []
PPrecise_, PRecall_ = [], []
NPrecise_, NRecall_ = [], []
''' 1:n 数据存储'''
PPrecise, PRecall = [], []
NPrecise, NRecall = [], []
''' 展厅 1:N 数据存储'''
''' 1:SN 数据存储，需根据相似度排序'''
PPreciseX, PRecallX = [], []
NPreciseX, NRecallX = [], []
''' 1:n 数据存储，需根据相似度排序'''
PPrecise, PRecall = [], []
NPrecise, NRecall = [], []
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)
'''(Precise, Recall) 计算方式, 若 1:1 与 1:SN 相似度选择方式相同，则可以合并'''
'''===================================== 1:1 最大值'''
_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/(len(one2oneAA)+1e-6))
_NPrecise.append(_TN/(_TN+_FN+1e-6))
_NRecall.append(_TN/(len(one2oneAB)+1e-6))
'''===================================== 1:SN 均值'''
TP_ = sum(np.array(one2SNAA) >= th)
FP_ = sum(np.array(one2SNAB) >= th)
FN_ = sum(np.array(one2SNAA) < th)
TN_ = sum(np.array(one2SNAB) < th)
PPrecise_.append(TP_/(TP_+FP_+1e-6))
# PRecall_.append(TP_/(TP_+FN_+1e-6))
PRecall_.append(TP_/(len(one2oneAA)+1e-6))
PRecall_.append(TP_/(len(one2SNAA)+1e-6))
NPrecise_.append(TN_/(TN_+FN_+1e-6))
# NRecall_.append(TN_/(TN_+FP_+1e-6))
NRecall_.append(TN_/(len(one2oneAB)+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))
PRecall.append(TP/(len(tpsimi)+len(fnsimi)+1e-6))
NPrecise.append(TN/(TN+FN+1e-6))
# NRecall.append(TN/(TN+FP+1e-6))
NRecall.append(TN/(len(tnsimi)+len(fpsimi)+1e-6))
'''============================= 1:N 展厅'''
NRecall_.append(TN_/(len(one2SNAB)+1e-6))
'''适用于 (Precise, Recall) 计算方式：多个相似度计算并排序，barcode相等且排名第一为 TP '''
'''===================================== 1:SN '''
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))
PRecallX.append(TPX/(len(tp_simi)+len(fn_simi)+1e-6))
NPreciseX.append(TNX/(TNX+FNX+1e-6))
# NRecallX.append(TNX/(TNX+FPX+1e-6))
NRecallX.append(TNX/(len(tn_simi)+len(fp_simi)+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/(len(tpsimi)+len(fnsimi)+1e-6))
NPrecise.append(TN/(TN+FN+1e-6))
NRecall.append(TN/(len(tnsimi)+len(fpsimi)+1e-6))
'''============================= 1:1 曲线'''
'''1. ============================= 1:1 最大值方案 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('1:1 Precise & Recall')
ax.set_xlabel(f"Event Num: {len(one2oneAA)+len(one2oneAB)}")
ax.legend()
plt.show()
## ============================= 1:1 最大值方案 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()
'''2. ============================= 1:1 均值方案 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')
@ -287,21 +398,50 @@ def one2one_pr(paths):
ax.set_ylim([0, 1])
ax.grid(True)
ax.set_title('1:1 Precise & Recall')
ax.set_xlabel(f"Event Num: {len(one2oneAA)}")
ax.set_xlabel(f"Event Num: {len(one2SNAA)}")
ax.legend()
plt.show()
'''============================= 1:1 直方图'''
## ============================= 1:1 均值方案 直方图'''
fig, axes = plt.subplots(2, 1)
axes[0].hist(np.array(one2oneAA), bins=60, edgecolor='black')
axes[0].hist(np.array(one2SNAA), 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].hist(np.array(one2SNAB), bins=60, edgecolor='black')
axes[1].set_xlim([-0.2, 1])
axes[1].set_title('BB')
plt.show()
''''3. ============================= 1:SN 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('1:SN Precise & Recall')
ax.set_xlabel(f"Event Num: {len(one2SNAA)}")
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()
'''============================= 1:n 曲线'''
'''4. ============================= 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')
@ -311,11 +451,10 @@ def one2one_pr(paths):
ax.set_ylim([0, 1])
ax.grid(True)
ax.set_title('1:n Precise & Recall')
ax.set_xlabel(f"Event Num: {len(one2oneAA)}")
ax.set_xlabel(f"Event Num: {len(tpsimi)+len(fnsimi)}")
ax.legend()
plt.show()
'''============================= 1:n 直方图'''
## ============================= 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])
@ -332,35 +471,18 @@ def one2one_pr(paths):
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('1:N Precise & Recall')
ax.set_xlabel(f"Event Num: {len(one2oneAA)}")
ax.legend()
plt.show()
fpsnErrFile = str(paths.joinpath("one2SN_Error.txt"))
with open(fpsnErrFile, "w") as file:
for item in fp_events:
file.write(item + "\n")
fpErrFile = str(paths.joinpath("one2n_Error.txt"))
with open(fpErrFile, "w") as file:
for item in fpevents:
file.write(item + "\n")
'''============================= 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()
# bcdSet = set(bcdList)
# one2nErrFile = str(paths.joinpath("one_2_Small_n_Error.txt"))
@ -378,7 +500,7 @@ def one2one_pr(paths):
if __name__ == "__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\1129_展厅模型v801测试组测试"
evtpaths = r"\\192.168.1.28\share\测试视频数据以及日志\算法全流程测试\202412\images"
one2one_pr(evtpaths)