NGA xView 2018 Dataset Auto-Download (#3775)

* update clip_coords for numpy

* uncomment

* cleanup

* Add autosplits

* fix

* cleanup

utils/general.py

@@ -393,8 +393,10 @@ def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):
     return y
 
 
-def xyxy2xywhn(x, w=640, h=640):
+def xyxy2xywhn(x, w=640, h=640, clip=False):
     # Convert nx4 boxes from [x1, y1, x2, y2] to [x, y, w, h] normalized where xy1=top-left, xy2=bottom-right
+    if clip:
+        clip_coords(x, (h, w))  # warning: inplace clip
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
     y[:, 0] = ((x[:, 0] + x[:, 2]) / 2) / w  # x center
     y[:, 1] = ((x[:, 1] + x[:, 3]) / 2) / h  # y center
@@ -455,10 +457,16 @@ def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None):
 
 def clip_coords(boxes, img_shape):
     # Clip bounding xyxy bounding boxes to image shape (height, width)
-    boxes[:, 0].clamp_(0, img_shape[1])  # x1
-    boxes[:, 1].clamp_(0, img_shape[0])  # y1
-    boxes[:, 2].clamp_(0, img_shape[1])  # x2
-    boxes[:, 3].clamp_(0, img_shape[0])  # y2
+    if isinstance(boxes, torch.Tensor):
+        boxes[:, 0].clamp_(0, img_shape[1])  # x1
+        boxes[:, 1].clamp_(0, img_shape[0])  # y1
+        boxes[:, 2].clamp_(0, img_shape[1])  # x2
+        boxes[:, 3].clamp_(0, img_shape[0])  # y2
+    else:  # np.array
+        boxes[:, 0].clip(0, img_shape[1], out=boxes[:, 0])  # x1
+        boxes[:, 1].clip(0, img_shape[0], out=boxes[:, 1])  # y1
+        boxes[:, 2].clip(0, img_shape[1], out=boxes[:, 2])  # x2
+        boxes[:, 3].clip(0, img_shape[0], out=boxes[:, 3])  # y2
 
 
 def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=False, eps=1e-7):