修改predict_demo.py,修正尺寸问题

models/line_detect/predict.py

@@ -28,7 +28,7 @@ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
 def box_line_(imgs, pred):  # 默认置信度
     im = imgs.permute(1, 2, 0).cpu().numpy()
-    lines = pred[-1]['wires']['lines'][0].cpu().numpy() / 128 * 512
+    lines = pred[-1]['wires']['lines'][0].cpu().numpy() / 128 * np.array([2000, 2000])
     scores = pred[-1]['wires']['score'].cpu().numpy()[0]
 
     # print(f'111:{len(lines)}')
@@ -114,7 +114,8 @@ def show_all(imgs, pred, threshold, save_path):
 
     boxes = pred[0]['boxes'].cpu().numpy()
     box_scores = pred[0]['scores'].cpu().numpy()
-    lines = pred[-1]['wires']['lines'][0].cpu().numpy() / 128 * 512
+    # lines = pred[-1]['wires']['lines'][0].cpu().numpy() / 128 * 512
+    lines = pred[-1]['wires']['lines'][0].cpu().numpy() / 128 * np.array([2000, 2000])
     scores = pred[-1]['wires']['score'].cpu().numpy()[0]
 
     for i in range(1, len(lines)):

models/line_detect/predict_demo.py

@@ -1,9 +1,10 @@
-from models.line_detect.line_net import linenet_resnet18_fpn
+from models.line_detect.line_net import linenet_resnet18_fpn, linenet_resnet50_fpn
 
 if __name__ == '__main__':
-    model=linenet_resnet18_fpn()
-    model.load_best_model(r'E:\projects\tmp\MultiVisionModels\models\line_detect\train_results\20250515_173829\weights\best_val.pth')
+    # model=linenet_resnet18_fpn()
+    model = linenet_resnet50_fpn()
+    model.load_best_model(r"\\192.168.50.222\share\zyh\best_val.pth")
 
-    img_path=r"\\192.168.50.222\share\rlq\datasets\修订513pcd转换彩图标注后汇总\2025-05-13-08-37-48_LaserData_ID019504_color.jpg"
+    img_path=r"\\192.168.50.222\share\zyh\5月彩色钢板数据汇总\total_325\2025-05-13-08-38-03_LaserData_ID019504_color.jpg"
 
     model.predict(img_path)