fix name bug

zhedahe · Nov 26, 2020 · 540cb78 · 540cb78
1 parent b36ad21
commit 540cb78
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Showing 3 changed files with 24 additions and 24 deletions.
diff --git a/pytorch_object_detection/yolov3_spp/train.py b/pytorch_object_detection/yolov3_spp/train.py
@@ -144,19 +144,19 @@ def train(hyp):
 
     # dataset
     # 训练集的图像尺寸指定为multi_scale_range中最大的尺寸
-    train_dataset = LoadImageAndLabels(train_path, imgsz_train, batch_size,
-                                       augment=True,
-                                       hyp=hyp,  # augmentation hyperparameters
-                                       rect=opt.rect,  # rectangular training
-                                       cache_images=opt.cache_images,
-                                       single_cls=opt.single_cls)
+    train_dataset = LoadImagesAndLabels(train_path, imgsz_train, batch_size,
+                                        augment=True,
+                                        hyp=hyp,  # augmentation hyperparameters
+                                        rect=opt.rect,  # rectangular training
+                                        cache_images=opt.cache_images,
+                                        single_cls=opt.single_cls)
 
     # 验证集的图像尺寸指定为img_size(512)
-    val_dataset = LoadImageAndLabels(test_path, imgsz_test, batch_size,
-                                     hyp=hyp,
-                                     rect=True,  # 将每个batch的图像调整到合适大小，可减少运算量(并不是512x512标准尺寸)
-                                     cache_images=opt.cache_images,
-                                     single_cls=opt.single_cls)
+    val_dataset = LoadImagesAndLabels(test_path, imgsz_test, batch_size,
+                                      hyp=hyp,
+                                      rect=True,  # 将每个batch的图像调整到合适大小，可减少运算量(并不是512x512标准尺寸)
+                                      cache_images=opt.cache_images,
+                                      single_cls=opt.single_cls)
 
     # dataloader
     nw = min([os.cpu_count(), batch_size if batch_size > 1 else 0, 8])  # number of workers

diff --git a/pytorch_object_detection/yolov3_spp/train_multi_GPU.py b/pytorch_object_detection/yolov3_spp/train_multi_GPU.py
@@ -157,19 +157,19 @@ def main(opt, hyp):
     # 训练集的图像尺寸指定为multi_scale_range中最大的尺寸
     # Make sure only the first process in DDP process the dataset first, and the following others can use the cache.
     with torch_distributed_zero_first(opt.rank):
-        train_dataset = LoadImageAndLabels(train_path, imgsz_train, batch_size,
-                                           augment=True,
-                                           hyp=hyp,  # augmentation hyperparameters
-                                           rect=opt.rect,  # rectangular training
-                                           cache_images=opt.cache_images,
-                                           single_cls=opt.single_cls,
-                                           rank=opt.rank)
+        train_dataset = LoadImagesAndLabels(train_path, imgsz_train, batch_size,
+                                            augment=True,
+                                            hyp=hyp,  # augmentation hyperparameters
+                                            rect=opt.rect,  # rectangular training
+                                            cache_images=opt.cache_images,
+                                            single_cls=opt.single_cls,
+                                            rank=opt.rank)
         # 验证集的图像尺寸指定为img_size(512)
-        val_dataset = LoadImageAndLabels(test_path, imgsz_test, batch_size,
-                                         hyp=hyp,
-                                         cache_images=opt.cache_images,
-                                         single_cls=opt.single_cls,
-                                         rank=opt.rank)
+        val_dataset = LoadImagesAndLabels(test_path, imgsz_test, batch_size,
+                                          hyp=hyp,
+                                          cache_images=opt.cache_images,
+                                          single_cls=opt.single_cls,
+                                          rank=opt.rank)
 
     # 给每个rank对应的进程分配训练的样本索引
     train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)

diff --git a/pytorch_object_detection/yolov3_spp/utils/datasets.py b/pytorch_object_detection/yolov3_spp/utils/datasets.py
@@ -49,7 +49,7 @@ def exif_size(img):
     return s
 
 
-class LoadImageAndLabels(Dataset):  # for training/testing
+class LoadImagesAndLabels(Dataset):  # for training/testing
     def __init__(self,
                  path,   # 指向data/my_train_data.txt路径或data/my_val_data.txt路径
                  # 这里设置的是预处理后输出的图片尺寸