highreso_resnet18fpn trained on 4080

models/line_detect/line_dataset.py

@@ -183,10 +183,10 @@ def get_boxes_lines(target):
             line_point_pairs.append([a[1], a[0]])
             line_point_pairs.append([b[1], b[0]])
 
-            xmin = min(a[0], b[0]) - 1
-            xmax = max(a[0], b[0]) + 1
-            ymin = min(a[1], b[1]) - 1
-            ymax = max(a[1], b[1]) + 1
+            xmin = max(0, (min(a[0], b[0]) - 6))
+            xmax = min(511, (max(a[0], b[0]) + 6))
+            ymin = max(0, (min(a[1], b[1]) - 6))
+            ymax = min(511, (max(a[1], b[1]) + 6))
 
             boxs.append([ymin, xmin, ymax, xmax])
 

models/line_detect/train.yaml

@@ -1,6 +1,6 @@
 io:
   logdir: train_results
-  datadir: \\192.168.50.222/share/rlq/datasets/250612
+  datadir: /data/share/lm/Dataset_all
 #  datadir: D:\python\PycharmProjects\data_20250223\0423_
 #  datadir: I:\datasets\wirenet_1000
 

models/line_detect/train_demo.py

@@ -10,12 +10,12 @@ if __name__ == '__main__':
 
     # model = LineNet('line_net.yaml')
     # model=linenet_resnet50_fpn()
-    model = linedetect_resnet18_fpn()
+    # model = linedetect_resnet50_fpn()
     # model=get_line_net_convnext_fpn(num_classes=2).to(device)
     # model=linenet_newresnet50fpn()
     # model = lineDetect_resnet18_fpn()
 
     # model=linedetect_resnet18_fpn()
-    # model=linedetect_newresnet18fpn()
+    model=linedetect_newresnet18fpn()
 
     model.start_train(cfg='train.yaml')