def test_loader(self):
coco_loader = VOCDataSet(
dataset_dir=self.image_dir,
image_dir=self.root_path,
anno_path=self.anno_path,
sample_num=240,
use_default_label=False,
label_list='/path/to/your/fl_fruit/label_list.txt')
sample_trans = [
DecodeImage(to_rgb=True),
RandomFlipImage(),
NormalizeImage(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225],
is_scale=True,
is_channel_first=False),
ResizeImage(target_size=800, max_size=1333, interp=1),
Permute(to_bgr=False)
]
batch_trans = [
PadBatch(pad_to_stride=32, use_padded_im_info=True),
]
inputs_def = {
'fields':
['image', 'im_info', 'im_id', 'gt_bbox', 'gt_class', 'is_crowd'],
}
data_loader = Reader(coco_loader,
sample_transforms=sample_trans,
batch_transforms=batch_trans,
batch_size=1,
shuffle=True,
drop_empty=True,
inputs_def=inputs_def)()
return data_loader
def test_loader_multi_threads(self):
coco_loader = COCODataSet(dataset_dir=self.root_path,
image_dir=self.image_dir,
anno_path=self.anno_path,
sample_num=10)
sample_trans = [
DecodeImage(to_rgb=True),
ResizeImage(target_size=800, max_size=1333, interp=1),
Permute(to_bgr=False)
]
batch_trans = [
PadBatch(pad_to_stride=32, use_padded_im_info=True),
]
inputs_def = {
'fields': [
'image', 'im_info', 'im_id', 'gt_bbox', 'gt_class', 'is_crowd',
'gt_mask'
],
}
data_loader = Reader(coco_loader,
sample_transforms=sample_trans,
batch_transforms=batch_trans,
batch_size=2,
shuffle=True,
drop_empty=True,
worker_num=2,
use_process=False,
bufsize=8,
inputs_def=inputs_def)()
for i in range(2):
for samples in data_loader:
for sample in samples:
im_shape = sample[0].shape
self.assertEqual(im_shape[0], 3)
self.assertEqual(im_shape[1] % 32, 0)
self.assertEqual(im_shape[2] % 32, 0)
im_info_shape = sample[1].shape
self.assertEqual(im_info_shape[-1], 3)
im_id_shape = sample[2].shape
self.assertEqual(im_id_shape[-1], 1)
gt_bbox_shape = sample[3].shape
self.assertEqual(gt_bbox_shape[-1], 4)
gt_class_shape = sample[4].shape
self.assertEqual(gt_class_shape[-1], 1)
self.assertEqual(gt_class_shape[0], gt_bbox_shape[0])
is_crowd_shape = sample[5].shape
self.assertEqual(is_crowd_shape[-1], 1)
self.assertEqual(is_crowd_shape[0], gt_bbox_shape[0])
mask = sample[6]
self.assertEqual(len(mask), gt_bbox_shape[0])
self.assertEqual(mask[0][0].shape[-1], 2)
data_loader.reset()