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@@ -21,7 +21,7 @@ from .imgaug_support import execute_imgaug
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from .cls_transforms import ClsTransform
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from .det_transforms import DetTransform
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from .seg_transforms import SegTransform
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-import paddlex
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+import paddlex as pdx
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from paddlex.cv.models.utils.visualize import get_color_map_list
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@@ -164,10 +164,10 @@ def det_compose(im, im_info=None, label_info=None, transforms=None, vdl_writer=N
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im = outputs[0]
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vdl_im = im
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if vdl_writer is not None:
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- if isinstance(op, paddlex.cv.transforms.det_transforms.ResizeByShort):
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+ if isinstance(op, pdx.cv.transforms.det_transforms.ResizeByShort):
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scale = outputs[1]['im_resize_info'][2]
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bboxes = bboxes * scale
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- elif isinstance(op, paddlex.cv.transforms.det_transforms.Resize):
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+ elif isinstance(op, pdx.cv.transforms.det_transforms.Resize):
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h = outputs[1]['image_shape'][0]
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w = outputs[1]['image_shape'][1]
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target_size = op.target_size
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@@ -183,7 +183,7 @@ def det_compose(im, im_info=None, label_info=None, transforms=None, vdl_writer=N
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bboxes[:,3] = bboxes[:,3] * h_scale
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else:
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bboxes = outputs[2]['gt_bbox']
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- if not isinstance(op, paddlex.cv.transforms.det_transforms.RandomHorizontalFlip):
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+ if not isinstance(op, pdx.cv.transforms.det_transforms.RandomHorizontalFlip):
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for i in range(bboxes.shape[0]):
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bbox = bboxes[i]
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cname = labels[outputs[2]['gt_class'][i][0]-1]
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@@ -194,7 +194,7 @@ def det_compose(im, im_info=None, label_info=None, transforms=None, vdl_writer=N
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int(bbox[3]),
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cname,
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catid2color[outputs[2]['gt_class'][i][0]-1])
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- if isinstance(op, paddlex.cv.transforms.det_transforms.Normalize):
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+ if isinstance(op, pdx.cv.transforms.det_transforms.Normalize):
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vdl_im = im
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else:
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im = execute_imgaug(op, im)
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sunyanfang01