refine autoaugment

Author: ZhenglinZhou

Augmentation.py

@@ -76,7 +76,7 @@ def __call__(self, sample):
         image = image.astype(np.float32)/255.0
 
         sample = {'img': image, 'annot': annots}
-        # easy_visualization(sample)
+        easy_visualization(sample)
         return sample
 
 

config.py

@@ -2,22 +2,22 @@
     dataset_type = 1 => voc dataset
     dataset_type = 2 => kitti dataset
 """
-dataset_type = 2
+dataset_type = 1
 epochs = 100
 CUDA_DEVICES = '6'
 
 kitti_batch_size = 24
-voc_batch_size = 8
+voc_batch_size = 2
 
 # voc_root_dir = '/home/CN/zhenglin.zhou/Documents/VOC/VOCdevkit/'
 # kitti_root_dir = '/home/CN/zhenglin.zhou/Documents/Kitti/training/'
 
-voc_root_dir = 'D:\VOC\VOCdevkit'
+voc_root_dir = 'D:/VOC/VOCdevkit'
 kitti_root_dir = 'D:/KITTI/training'
 
 """    Mixup    """
 use_mixup = 0
 alpha = 1
 
 """    Autoaugment     """
-use_autoaugment = 1
+use_autoaugment = 0

retinanet/losses.py

@@ -171,7 +171,6 @@ def forward(self, classifications, regressions, anchors, annotations):
                     regression_losses.append(torch.tensor(0).float().cuda())
                 else:
                     regression_losses.append(torch.tensor(0).float())
-
         # return torch.stack(classification_losses).mean(dim=0, keepdim=True), torch.stack(regression_losses).mean(dim=0, keepdim=True)
         return torch.stack(classification_losses), torch.stack(regression_losses)
 

test_augmentation.py

@@ -7,11 +7,10 @@
 if __name__ == '__main__':
     voc_train = VocDataset(voc_root_dir, 'train',
                            transform=transforms.Compose([autoaugmenter('test')]))
-    for i in range(voc_train.__len__()):
-        print(i)
-        sample = voc_train[i]
-    # sample = voc_train[11]
-    # sample = voc_train[9]
+    # for i in range(voc_train.__len__()):
+    #     print(i)
+    #     sample = voc_train[i]
+    sample = voc_train[11]
     # SplitKittiDataset(kitti_root_dir, 0.5)  # 分割KITTI数据集，50%训练集，50%测试集
     #
     # kitti_train = KittiDataset(kitti_root_dir, 'train', transform=transforms.Compose([autoaugmenter('test')]))

train.py

@@ -16,8 +16,8 @@
     author: zhenglin.zhou
     date: 20200724
 """
-CUDA_DEVICES = config.CUDA_DEVICES
-os.environ["CUDA_VISIBLE_DEVICES"] = CUDA_DEVICES
+# CUDA_DEVICES = config.CUDA_DEVICES
+# os.environ["CUDA_VISIBLE_DEVICES"] = CUDA_DEVICES
 
 print('CUDA available: {}'.format(torch.cuda.is_available()))
 
@@ -26,12 +26,12 @@ def main():
     epochs = config.epochs
     if config.use_autoaugment:
         transform = transforms.Compose([Normalizer(),
-                                        autoaugmenter(),
+                                        autoaugmenter('v1'),
                                         Resizer(),
                                         ])
     else:
         transform = transforms.Compose([Normalizer(),
-                                        retinanet_augmentater('v1'),
+                                        retinanet_augmentater(),
                                         Resizer(),
                                         ])
 
@@ -56,9 +56,6 @@ def main():
     sampler = AspectRatioBasedSampler(dataset_train, batch_size=batch_size, drop_last=False)
     dataloader_train = DataLoader(dataset_train, num_workers=3,
                                   collate_fn=collater, batch_sampler=sampler)
-    sampler_val = AspectRatioBasedSampler(dataset_val, batch_size=batch_size, drop_last=False)
-    dataloader_val = DataLoader(dataset_train, num_workers=3,
-                                  collate_fn=collater, batch_sampler=sampler)
 
     retinanet = model.resnet18(num_classes=dataset_train.num_classes(), pretrained=True)