boolean index did not match indexed array along dimension 0;

[Amirjomaa]

----------------- Options ---------------
SA_mode: BAM
angle: 15 [default: 0]
arch: mynet3
batch_size: 8 [default: 1]
beta1: 0.5
checkpoints_dir: ./checkpoints
continue_train: False
crop_size: 256
dataroot: path-to-LEVIR-CD-train [default: /content/gdrive/MyDrive/STANet/data1]
dataset_mode: changedetection
dataset_type: CD_LEVIR
display_env: main
display_freq: 400
display_id: 1
display_ncols: 4
display_port: 8097
display_server: http://localhost/
display_winsize: 256
ds: 1 [default: 1]
epoch: latest
epoch_count: 1
f_c: 64
gpu_ids: 0
init_gain: 0.02
init_type: normal
input_nc: 3
isTrain: True [default: None]
istest: False
json_name: train_val_test
load_iter: 0 [default: 0]
load_size: 256 [default: 286]
lr: 0.001 [default: 0.0002]
lr_decay: 1
lr_decay_iters: 50
lr_policy: linear
max_dataset_size: inf
model: CDF0 [default: CDFA]
n_class: 2
name: LEVIR-CDF0 [default: experiment_name]
niter: 50
niter_decay: 100
no_flip: True
no_html: False
num_threads: 4
output_nc: 3
phase: train
preprocess: rotate_and_crop [default: resize_and_crop]
print_freq: 100
save_by_iter: False
save_epoch_freq: 1 [default: 5]
save_latest_freq: 5000
serial_batches: False
split: train
suffix:
update_html_freq: 1000
val_dataroot: path-to-LEVIR-CD-val [default: /content/gdrive/MyDrive/STANet/data1/val]
val_dataset_mode: changedetection
val_dataset_type: CD_LEVIR
val_json_name: train_val_test
val_split: val
verbose: False
----------------- End -------------------
changedetection
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dataset [ChangeDetectionDataset] was created
/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
cpuset_checked))
The number of training images = 445
using mynet3 backbone
arch: mynet3
in_c: 3
model [CDF0Model] was created
---------- Networks initialized -------------
[Network F] Total number of parameters : 16.892 M

Setting up a new session...
create web directory ./checkpoints/LEVIR-CDF0/web...
/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
cpuset_checked))
(epoch: 1, iters: 200, time: 0.082, data: 6.002) f: 156.634
(epoch: 1, iters: 400, time: 0.087, data: 0.009) f: 124.886
(epoch: 1) current_t_epoch: 77.929
saving the model at the end of epoch 1, iters 440
changedetection
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dataset [ChangeDetectionDataset] was created
tcmalloc: large alloc 2147483648 bytes == 0x558f43b66000 @ 0x7fd19bed2b6b 0x7fd19bef2379 0x7fd09b6d7cde 0x7fd09b6d9452 0x7fd0ed700cf3 0x7fd0ed788158 0x7fd0ede5f49f 0x7fd0ede3f870 0x7fd0edc2a48a 0x7fd0ed77929d 0x7fd0edf58aca 0x7fd0ede3b70e 0x7fd0eda00d17 0x7fd0ef3637c4 0x7fd0ef363c8d 0x7fd0eda766e8 0x7fd0ed7773d5 0x7fd0edfdf970 0x7fd0edd2c069 0x7fd196b382c3 0x7fd196c9204e 0x558ed7cb9390 0x558ed7dabb3d 0x558ed7d2d458 0x558ed7d2802f 0x558ed7cbaaba 0x558ed7d29cd4 0x558ed7cba9da 0x558ed7d28eae 0x558ed7d2802f 0x558ed7d27d43
Traceback (most recent call last):
File "train.py", line 169, in
miou_current = val(opt, model)
File "train.py", line 86, in val
score = model.test(val=True) # run inference
File "/content/STANet/models/CDF0_model.py", line 79, in test
metrics.update(self.L.detach().cpu().numpy(), pred.detach().cpu().numpy())
File "/content/STANet/util/metrics.py", line 121, in update
self.confusion_matrix += self.__fast_hist(lt.flatten(), lp.flatten())
File "/content/STANet/util/metrics.py", line 108, in __fast_hist
hist = np.bincount(self.num_classes * label_gt[mask].astype(int) + label_pred[mask],
IndexError: boolean index did not match indexed array along dimension 0; dimension is 67108864 but corresponding boolean dimension is 1048576

[ZhaoRuu]

这个问题你解决了吗，我也有同样的问题

[ABCD121-SOURCE]

这个问题你解决了吗，我也有同样的问题

你是怎么解决这个问题的？我也遇到了同样的问题

[ABCD121-SOURCE]

这个问题目前有解决方案吗？

[ep20012001]

i have the same problem.Has anyone found a solution?