debug circle on 4080(single channel 4points)

models/line_detect/line_detect.py

@@ -342,7 +342,7 @@ def linedetect_newresnet18fpn(
     if num_points is None:
         num_points = 4
 
-    size=512
+    size=768
     backbone =resnet18fpn()
     featmap_names=['0', '1', '2', '3','4','pool']
     # print(f'featmap_names:{featmap_names}')
@@ -387,7 +387,7 @@ def linedetect_newresnet50fpn(
     if num_points is None:
         num_points = 4
 
-    size=512
+    size=768
     backbone =resnet50fpn(out_channels=256)
     featmap_names=['0', '1', '2', '3','4','pool']
     # print(f'featmap_names:{featmap_names}')

models/line_detect/train.yaml

@@ -7,7 +7,7 @@ io:
 #  datadir: /data/share/rlq/datasets/250718caisegangban
 
 #  datadir: /data/share/rlq/datasets/singepoint_Dataset0709_2
-  datadir: \\192.168.50.222/share/rlq/datasets/guanban_circle
+  datadir: /data/share/rlq/datasets/guanban_circle
 #  datadir: \\192.168.50.222/share/rlq/datasets/singepoint_Dataset0709_2
 #  datadir: \\192.168.50.222/share/rlq/datasets/250718caisegangban
   data_type: rgb

models/line_detect/train_demo.py

@@ -17,8 +17,8 @@ if __name__ == '__main__':
     # model = lineDetect_resnet18_fpn()
 
     # model=linedetect_resnet18_fpn()
-    model=linedetect_newresnet18fpn(num_points=4)
-    # model=linedetect_newresnet50fpn(num_points=4)
+    # model=linedetect_newresnet18fpn(num_points=4)
+    model=linedetect_newresnet50fpn(num_points=4)
     # model = linedetect_newresnet101fpn(num_points=3)
     # model = linedetect_newresnet152fpn(num_points=3)
     # model.load_weights(save_path=r'/home/admin/projects/MultiVisionModels/models/line_detect/train_results/20250711_114046/weights/best_val.pth')