refine

Author: ZhenglinZhou

augmentation_zoo/SmallObjectAugmentation.py

@@ -51,8 +51,7 @@ def create_copy_annot(self, h, w, annot, annots):
                                  np.random.randint(int(annot_h / 2), int(h - annot_h / 2))
             xmin, ymin = random_x - annot_w / 2, random_y - annot_h / 2
             xmax, ymax = xmin + annot_w, ymin + annot_h
-            if np.int(xmin) < 0 or np.floor(xmax) > w or \
-                    np.int(ymin) < 0 or np.floor(ymax) > h:
+            if xmin < 0 or xmax > w or ymin < 0 or ymax > h:
                 continue
             new_annot = np.array([xmin, ymin, xmax, ymax, annot[4]]).astype(np.int)
 

test_augmentation.py

@@ -26,17 +26,17 @@ def _make_transform():
     voc_train = VocDataset(VOC_ROOT_DIR, 'train', transform=transforms.Compose(transform_list))
     kitti_train = KittiDataset(KITTI_ROOT_DIR, 'train', transforms.Compose(transform_list))
 
-    # for i in range(voc_train.__len__()):
-    #     print(i)
-    #     sample = voc_train[i]
-    #     easy_visualization(sample)
+    for i in range(voc_train.__len__()):
+        print(i)
+        sample = voc_train[i]
+        # easy_visualization(sample)
 
     # sample = voc_train[19]
     # easy_visualization(sample)
 
-    for i in range(kitti_train.__len__()):
-        sample = kitti_train[i]
-        easy_visualization(sample)
+    # for i in range(kitti_train.__len__()):
+    #     sample = kitti_train[i]
+    #     easy_visualization(sample)
 
     # sample = kitti_train[0]
     # easy_visualization(sample)