perf(svm): 添加列表add_negative_list，保存后续添加的负样本边界框，判断是否需要添加

Author: zjZSTU

py/linear_svm.py

@@ -95,13 +95,13 @@ def hinge_loss(outputs, labels):
 
 def add_hard_negatives(hard_negative_list, negative_list, add_negative_list):
     for item in hard_negative_list:
-        if add_negative_list is None:
+        if len(add_negative_list) == 0:
             # 第一次添加负样本
             negative_list.append(item)
-            add_negative_list.append(item['rect'])
-        if item['rect'] not in add_negative_list:
+            add_negative_list.append(list(item['rect']))
+        if list(item['rect']) not in add_negative_list:
             negative_list.append(item)
-            add_negative_list.append(item['rect'])
+            add_negative_list.append(list(item['rect']))
 
 
 def get_hard_negatives(preds, cache_dicts):
@@ -199,7 +199,7 @@ def train_model(data_loaders, model, criterion, optimizer, lr_scheduler, num_epo
                 # 获取训练数据集的负样本集
                 negative_list = train_dataset.get_negatives()
                 # 记录后续增加的负样本
-                add_negative_list = data_loaders['add_negative']
+                add_negative_list = data_loaders.get('add_negative', [])
 
                 running_corrects = 0
                 # Iterate over data.