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PaddleOCR
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update

This commit is contained in:
WenmuZhou 2020-12-16 13:06:48 +08:00
parent 41c2af4924
commit a8d1f2db94
3 changed files with 8 additions and 8 deletions
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4
configs/det/det_mv3_db.yml
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@ -5,8 +5,8 @@ Global:
print_batch_step: 10 print_batch_step: 10
save_model_dir: ./output/db_mv3/ save_model_dir: ./output/db_mv3/
save_epoch_step: 1200 save_epoch_step: 1200
# evaluation is run every 5000 iterations after the 4000th iteration # evaluation is run every 2000 iterations
eval_batch_step: [4000, 5000] eval_batch_step: [0, 2000]
# if pretrained_model is saved in static mode, load_static_weights must set to True # if pretrained_model is saved in static mode, load_static_weights must set to True
load_static_weights: True load_static_weights: True
cal_metric_during_train: False cal_metric_during_train: False

4
configs/det/det_r50_vd_db.yml
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@ -5,8 +5,8 @@ Global:
print_batch_step: 10 print_batch_step: 10
save_model_dir: ./output/det_r50_vd/ save_model_dir: ./output/det_r50_vd/
save_epoch_step: 1200 save_epoch_step: 1200
# evaluation is run every 5000 iterations after the 4000th iteration # evaluation is run every 2000 iterations
eval_batch_step: [4000,5000] eval_batch_step: [0,2000]
# if pretrained_model is saved in static mode, load_static_weights must set to True # if pretrained_model is saved in static mode, load_static_weights must set to True
load_static_weights: True load_static_weights: True
cal_metric_during_train: False cal_metric_during_train: False

8
ppocr/losses/det_db_loss.py
View File

@ -47,12 +47,12 @@ class DBLoss(nn.Layer):
negative_ratio=ohem_ratio) negative_ratio=ohem_ratio)
def forward(self, predicts, labels): 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[ label_threshold_map, label_threshold_mask, label_shrink_map, label_shrink_mask = labels[
1:] 1:]
shrink_maps = predicts[:, 0, :, :] shrink_maps = predict_maps[:, 0, :, :]
threshold_maps = predicts[:, 1, :, :] threshold_maps = predict_maps[:, 1, :, :]
binary_maps = predicts[:, 2, :, :] binary_maps = predict_maps[:, 2, :, :]
loss_shrink_maps = self.bce_loss(shrink_maps, label_shrink_map, loss_shrink_maps = self.bce_loss(shrink_maps, label_shrink_map,
label_shrink_mask) label_shrink_mask)