Python mmdet.datasets.to_tensor() Examples
The following are 13
code examples of mmdet.datasets.to_tensor().
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Example #1
Source File: inference.py From AerialDetection with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #2
Source File: inference.py From GCNet with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #3
Source File: inference.py From mmdetection-annotated with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #4
Source File: inference.py From mmdetection_with_SENet154 with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #5
Source File: inference.py From PolarMask with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #6
Source File: inference.py From Grid-R-CNN with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #7
Source File: inference.py From Libra_R-CNN with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #8
Source File: inference.py From FoveaBox with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #9
Source File: inference.py From kaggle-imaterialist with MIT License | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #10
Source File: inference.py From hrnet with MIT License | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #11
Source File: inference.py From CenterNet with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #12
Source File: inference.py From AugFPN with Apache License 2.0 | 6 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale, keep_ratio=cfg.data.test.get('resize_keep_ratio', True)) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])
Example #13
Source File: inference.py From Reasoning-RCNN with Apache License 2.0 | 5 votes |
def _prepare_data(img, img_transform, cfg, device): ori_shape = img.shape img, img_shape, pad_shape, scale_factor = img_transform( img, scale=cfg.data.test.img_scale) img = to_tensor(img).to(device).unsqueeze(0) img_meta = [ dict( ori_shape=ori_shape, img_shape=img_shape, pad_shape=pad_shape, scale_factor=scale_factor, flip=False) ] return dict(img=[img], img_meta=[img_meta])