def crop(image, boxes, classes):
height, width, _ = image.shape
while True:
mode = random.choice((
None,
(0.1, None),
(0.3, None),
(0.7, None),
(0.9, None),
(None, None),
))
if mode is None:
return image, boxes, classes
min_iou, max_iou = mode
if min_iou is None:
min_iou = float('-inf')
if max_iou is None:
max_iou = float('inf')
for _ in range(50):
w = random.randrange(int(0.3 * width), width)
h = random.randrange(int(0.3 * height), height)
if h / w < 0.5 or 2 < h / w:
continue
rect = Rect.LTWH(random.randrange(width - w),
random.randrange(height - h), w, h)
iou = matrix_iou(boxes, np.array((rect, )))
if iou.min() < min_iou and max_iou < iou.max():
continue
image = image[rect.top:rect.bottom, rect.left:rect.right]
centers = (boxes[:, :2] + boxes[:, 2:]) / 2
mask = np.logical_and((rect.left, rect.top) < centers, centers <
(rect.right, rect.bottom)).all(axis=1)
boxes = boxes[mask].copy()
classes = classes[mask]
boxes[:, :2] = np.maximum(boxes[:, :2], (rect.left, rect.top))
boxes[:, :2] -= (rect.left, rect.top)
boxes[:, 2:] = np.minimum(boxes[:, 2:], (rect.right, rect.bottom))
boxes[:, 2:] -= (rect.left, rect.top)
return image, boxes, classes
