def _transform_fn(*data):
"""
This function is used as the parameter of dataset.transform(). The coords in mx_label is absolute coords.
The processing procedure of image contains resize, augmentation, color_normalize, and to_tensor.
The processing procedure of label just contains resize.
:param data: (img, label), img: np.array, int, (h, w, c), label: absolute, np.array, int, (N, 5)
:return: (mx_img, mx_label), mx_img: mx.nd.array, float, (c, h, w), mx_label: absolute, mx.nd.array, (N, 5)
"""
img, label = data
img = img.astype('float32') / 255 # deepcopy
label = label.astype('float32')
aug_img, aug_label = myutils.data_augment(img,
label,
size=self.model_img_size,
rb=0.0,
rc=0.0,
rh=0.0,
rs=0.0,
rflr=False,
re=True,
rcp=False)
aug_img = mx.img.color_normalize(mx.nd.array(aug_img),
mean=mx.nd.array(myutils.mean),
std=mx.nd.array(myutils.std))
mx_img = myutils.to_tensor(aug_img)
aug_label[:, 1:] = myutils.bbox_abs_to_rel(aug_label[:, 1:],
mx_img.shape[-2:])
mx_label = mx.nd.array(aug_label)
return mx_img, mx_label
def transform_fn(*data):
"""
This function is used as the parameter of dataset.transform(). The coords in mx_label is absolute coords.
The processing procedure of image contains resize, augmentation, color_normalize, and to_tensor.
The processing procedure of label just contains resize.
:param data: (img, label), img: np.array, int, (h, w, c), label: absolute, np.array, int, (N, 5)
:return: (mx_img, mx_label), mx_img: mx.nd.array, float, (c, h, w), mx_label: absolute, mx.nd.array, (N, 5)
"""
img, label = data
img = img.astype('float32') # deepcopy
label = label.astype('float32')
aug_img, aug_label = myutils.data_augment(img, label, size=(300, 300))
norm_img = mx.img.color_normalize(mx.nd.array(aug_img),
mean=mx.nd.array(myutils.mean),
std=mx.nd.array(myutils.std))
mx_img = myutils.to_tensor(norm_img)
mx_label = mx.nd.array(aug_label)
return mx_img, mx_label