未验证 提交 1292e6c3 编写于 作者: C cnn 提交者: GitHub

remove print (#2838)

上级 03f79b00
...@@ -111,8 +111,6 @@ class BBoxPostProcess(object): ...@@ -111,8 +111,6 @@ class BBoxPostProcess(object):
pred_score = bboxes[:, 1:2] pred_score = bboxes[:, 1:2]
pred_bbox = bboxes[:, 2:] pred_bbox = bboxes[:, 2:]
# rescale bbox to original image # rescale bbox to original image
print('pred_bbox', pred_bbox.shape, 'scale_factor_list',
scale_factor_list.shape)
scaled_bbox = pred_bbox / scale_factor_list scaled_bbox = pred_bbox / scale_factor_list
origin_h = self.origin_shape_list[:, 0] origin_h = self.origin_shape_list[:, 0]
origin_w = self.origin_shape_list[:, 1] origin_w = self.origin_shape_list[:, 1]
...@@ -279,7 +277,6 @@ class S2ANetBBoxPostProcess(object): ...@@ -279,7 +277,6 @@ class S2ANetBBoxPostProcess(object):
including labels, scores and bboxes. The size of including labels, scores and bboxes. The size of
bboxes are corresponding to the original image. bboxes are corresponding to the original image.
""" """
print('im_shape', im_shape, 'scale_factor', scale_factor)
origin_shape = paddle.floor(im_shape / scale_factor + 0.5) origin_shape = paddle.floor(im_shape / scale_factor + 0.5)
origin_shape_list = [] origin_shape_list = []
...@@ -301,25 +298,15 @@ class S2ANetBBoxPostProcess(object): ...@@ -301,25 +298,15 @@ class S2ANetBBoxPostProcess(object):
scale_factor_list = paddle.concat(scale_factor_list) scale_factor_list = paddle.concat(scale_factor_list)
# bboxes: [N, 10], label, score, bbox # bboxes: [N, 10], label, score, bbox
print('bboxes', bboxes.shape)
pred_label_score = bboxes[:, 0:2] pred_label_score = bboxes[:, 0:2]
print('pred_label_score', pred_label_score.shape)
pred_bbox = bboxes[:, 2:10:1] pred_bbox = bboxes[:, 2:10:1]
print('pred_bbox', pred_bbox.shape)
# rescale bbox to original image # rescale bbox to original image
scaled_bbox = pred_bbox / scale_factor_list scaled_bbox = pred_bbox / scale_factor_list
origin_h = origin_shape_list[:, 0] origin_h = origin_shape_list[:, 0]
origin_w = origin_shape_list[:, 1] origin_w = origin_shape_list[:, 1]
print('scaled_bbox', bboxes.shape)
bboxes = scaled_bbox bboxes = scaled_bbox
#print('bboxes', bboxes.shape, 'scale_factor', scale_factor.shape)
#print('bboxes[:, 0::2]', bboxes[:, 0::2].shape)
#print('scale_factor[0]', scale_factor)
#bboxes[:, 0::2] = bboxes[:, 0::2] / scale_factor[:, 0]
#bboxes[:, 1::2] = bboxes[:, 1::2] / scale_factor[:, 1]
zeros = paddle.zeros_like(origin_h) zeros = paddle.zeros_like(origin_h)
x1 = paddle.maximum(paddle.minimum(bboxes[:, 0], origin_w - 1), zeros) x1 = paddle.maximum(paddle.minimum(bboxes[:, 0], origin_w - 1), zeros)
y1 = paddle.maximum(paddle.minimum(bboxes[:, 1], origin_h - 1), zeros) y1 = paddle.maximum(paddle.minimum(bboxes[:, 1], origin_h - 1), zeros)
......
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