def func_co(x):
x.sort()
Eval = NuScenesEval('', '', args.format)
fused_data = cu.matching_and_fusion(cam_test_list[x[0]],cam_test_list[x[1]])
fused_gt = cu.filt_gt_labels_tuple(cam_gt_list[x[0]],cam_gt_list[x[1]])
mAP_temp = Eval.my_evaluate(fused_data,fused_gt)
return 1- mAP_temp
def fuse_constellation(x):
#根据x的维度进行融合
x.sort()
size_n = x.shape[0]
main_cam = x[0]
gt_list = []
gt_list.append(cam_gt_list[main_cam])
for i in x[1:]:
fused_data = cu.matching_and_fusion(cam_test_list[main_cam],cam_test_list[i]) #融合
gt_list.append(cam_gt_list[i])
fused_gt = cu.filt_gt_labels_tuple(*gt_list)
Eval = NuScenesEval('', '', args.format)
mAP_temp = Eval.my_evaluate(fused_data,fused_gt)
return 1- mAP_temp
# for k in range(j+1,34):
# fused_data = cu.matching_and_fusion(fused_data,cam_test_list[k]) #融合
# for z in range(k+1,34):
# Eval = NuScenesEval('', '', args.format)
# fused_data = cu.matching_and_fusion(fused_data,cam_test_list[z]) #融合
# fused_gt = cu.filt_gt_labels_tuple(cam_gt_list[i],cam_gt_list[j],cam_gt_list[k],cam_gt_list[z])
# #评估
# mAP_temp = Eval.my_evaluate(fused_data,fused_gt)
# if mAP_temp > max_map:
# max_map = mAP_temp
# max_i,max_j = i,j
# print('temp max mAP: {}.......... time: ## i: {} j: {} k:{} z:{}'.format(max_map,i,j,k,z))
#print(mAP_temp)
max_map = 0
max_i, max_j = 0, 0
fused_gt = cu.filt_gt_labels_tuple(*cam_gt_list)
for i in range(34):
for j in range(i + 1, 34):
fused_data = cu.matching_and_fusion(cam_test_list[i],
cam_test_list[j]) #融合
Eval = NuScenesEval('', '', args.format)
#fused_gt = cu.filt_gt_labels_tuple(cam_gt_list[i],cam_gt_list[j],cam_gt_list[k])
#评估
mAP_temp = Eval.my_evaluate(fused_data, fused_gt)
if mAP_temp > max_map:
max_map = mAP_temp
max_i, max_j = i, j
print(
'temp max mAP: {}.......... time: ## i: {} j: {} '.
format(max_map, i, j))
#print(mAP_temp)