提交 a8d1f2db 编写于 作者: W WenmuZhou

update

上级 41c2af49
......@@ -5,8 +5,8 @@ Global:
print_batch_step: 10
save_model_dir: ./output/db_mv3/
save_epoch_step: 1200
# evaluation is run every 5000 iterations after the 4000th iteration
eval_batch_step: [4000, 5000]
# evaluation is run every 2000 iterations
eval_batch_step: [0, 2000]
# if pretrained_model is saved in static mode, load_static_weights must set to True
load_static_weights: True
cal_metric_during_train: False
......
......@@ -5,8 +5,8 @@ Global:
print_batch_step: 10
save_model_dir: ./output/det_r50_vd/
save_epoch_step: 1200
# evaluation is run every 5000 iterations after the 4000th iteration
eval_batch_step: [4000,5000]
# evaluation is run every 2000 iterations
eval_batch_step: [0,2000]
# if pretrained_model is saved in static mode, load_static_weights must set to True
load_static_weights: True
cal_metric_during_train: False
......
......@@ -47,12 +47,12 @@ class DBLoss(nn.Layer):
negative_ratio=ohem_ratio)
def forward(self, predicts, labels):
predicts = predicts['maps']
predict_maps = predicts['maps']
label_threshold_map, label_threshold_mask, label_shrink_map, label_shrink_mask = labels[
1:]
shrink_maps = predicts[:, 0, :, :]
threshold_maps = predicts[:, 1, :, :]
binary_maps = predicts[:, 2, :, :]
shrink_maps = predict_maps[:, 0, :, :]
threshold_maps = predict_maps[:, 1, :, :]
binary_maps = predict_maps[:, 2, :, :]
loss_shrink_maps = self.bce_loss(shrink_maps, label_shrink_map,
label_shrink_mask)
......
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