lines and arcs training togeter

models/line_detect/line_detect.py

@@ -542,7 +542,7 @@ def linedetect_efficientnet(
         num_classes=num_classes,  # COCO 数据集有 91 类
         rpn_anchor_generator=get_anchor_generator(backbone_with_fpn, test_input=test_input),
         box_roi_pool=roi_pooler,
-        detect_line=False,
+        detect_line=True,
         detect_point=False,
         detect_arc=False,
         detect_ins=True,

models/line_detect/loi_heads.py

@@ -907,7 +907,7 @@ class RoIHeads(nn.Module):
         if  self.has_line() and self.detect_line:
             print(f'roi_heads forward has_line()!!!!')
             # print(f'labels:{labels}')
-            line_proposals = [p["boxes"] for p in result]
+            line_proposals = [p["boxes"][p["labels"] == 2] for p in result]
             point_proposals = [p["boxes"] for p in result]
             print(f'boxes_proposals:{len(line_proposals)}')
 

models/line_detect/trainer.py

@@ -567,7 +567,7 @@ class Trainer(BaseTrainer):
         )
 
         model, optimizer = self.load_best_model(model, optimizer,
-                                                r"\\192.168.50.222\share\rlq\weights\250725_arc_res152_best_val.pth",
+                                                r"/home/limin/PycharmProjects/pokouqiege/1126/MultiVisionModels/models/line_detect/train_results/20251213_145349/weights/best_val.pth",
                                                 device)
         # scheduler = StepLR(optimizer, step_size=10, gamma=0.1)
         scheduler = ReduceLROnPlateau(optimizer, 'min', patience=30)