update

configs/det/det_mv3_db.yml

@@ -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

configs/det/det_r50_vd_db.yml

@@ -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

ppocr/losses/det_db_loss.py

@@ -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)