Exemple #1
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def get_mnist_data(is_train, image_size, batchsize):
    ds = MNISTCh('train' if is_train else 'test', shuffle=True)

    if is_train:
        augs = [
            imgaug.RandomApplyAug(imgaug.RandomResize((0.8, 1.2), (0.8, 1.2)),
                                  0.3),
            imgaug.RandomApplyAug(imgaug.RotationAndCropValid(15), 0.5),
            imgaug.RandomApplyAug(
                imgaug.SaltPepperNoise(white_prob=0.01, black_prob=0.01),
                0.25),
            imgaug.Resize((224, 224), cv2.INTER_AREA)
        ]
        ds = AugmentImageComponent(ds, augs)
        ds = PrefetchData(ds, 128 * 10, multiprocessing.cpu_count())
        ds = BatchData(ds, batchsize)
        ds = PrefetchData(ds, 256, 4)
    else:
        # no augmentation, only resizing
        augs = [
            imgaug.Resize((image_size, image_size), cv2.INTER_CUBIC),
        ]
        ds = AugmentImageComponent(ds, augs)
        ds = BatchData(ds, batchsize)
        ds = PrefetchData(ds, 20, 2)
    return ds
Exemple #2
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def get_dataflow(path, is_train):
    ds = CocoPoseLMDB(path, is_train)  # read data from lmdb
    if is_train:
        ds = MapDataComponent(ds, pose_random_scale)
        ds = MapDataComponent(ds, pose_rotation)
        ds = MapDataComponent(ds, pose_flip)
        ds = MapDataComponent(ds, pose_resize_shortestedge_random)
        ds = MapDataComponent(ds, pose_crop_random)
        ds = MapData(ds, pose_to_img)
        augs = [
            imgaug.RandomApplyAug(
                imgaug.RandomChooseAug([
                    imgaug.BrightnessScale((0.6, 1.4), clip=False),
                    imgaug.Contrast((0.7, 1.4), clip=False),
                    imgaug.GaussianBlur(max_size=3)
                ]), 0.7),
        ]
        ds = AugmentImageComponent(ds, augs)
    else:
        ds = MapDataComponent(ds, pose_resize_shortestedge_fixed)
        ds = MapDataComponent(ds, pose_crop_center)
        ds = MapData(ds, pose_to_img)

    ds = PrefetchData(ds, 1000, multiprocessing.cpu_count())

    return ds
Exemple #3
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def sample_augmentations():
    ds = CocoPoseLMDB('/data/public/rw/coco-pose-estimation-lmdb/',
                      is_train=False,
                      only_idx=0)
    ds = MapDataComponent(ds, pose_random_scale)
    ds = MapDataComponent(ds, pose_rotation)
    ds = MapDataComponent(ds, pose_flip)
    ds = MapDataComponent(ds, pose_resize_shortestedge_random)
    ds = MapDataComponent(ds, pose_crop_random)
    ds = MapData(ds, pose_to_img)
    augs = [
        imgaug.RandomApplyAug(
            imgaug.RandomChooseAug([
                imgaug.GaussianBlur(3),
                imgaug.SaltPepperNoise(white_prob=0.01, black_prob=0.01),
                imgaug.RandomOrderAug([
                    imgaug.BrightnessScale((0.8, 1.2), clip=False),
                    imgaug.Contrast((0.8, 1.2), clip=False),
                    # imgaug.Saturation(0.4, rgb=True),
                ]),
            ]),
            0.7),
    ]
    ds = AugmentImageComponent(ds, augs)

    ds.reset_state()
    for l1, l2, l3 in ds.get_data():
        CocoPoseLMDB.display_image(l1, l2, l3)
Exemple #4
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def get_dataflow(path, is_train):
    ds = CocoPoseLMDB(path, is_train)  # read data from lmdb
    if is_train:
        ds = MapDataComponent(ds, pose_random_scale)
        ds = MapDataComponent(ds, pose_rotation)
        ds = MapDataComponent(ds, pose_flip)
        ds = MapDataComponent(ds, pose_resize_shortestedge_random)
        ds = MapDataComponent(ds, pose_crop_random)
        ds = MapData(ds, pose_to_img)
        augs = [
            imgaug.RandomApplyAug(
                imgaug.RandomChooseAug([
                    imgaug.SaltPepperNoise(white_prob=0.01, black_prob=0.01),
                    imgaug.RandomOrderAug([
                        imgaug.BrightnessScale((0.8, 1.2), clip=False),
                        imgaug.Contrast((0.8, 1.2), clip=False),
                        # imgaug.Saturation(0.4, rgb=True),
                    ]),
                ]),
                0.7),
        ]
        ds = AugmentImageComponent(ds, augs)
    else:
        ds = MapDataComponent(ds, pose_resize_shortestedge_fixed)
        ds = MapDataComponent(ds, pose_crop_center)
        ds = MapData(ds, pose_to_img)

    ds = PrefetchData(ds, 1000, multiprocessing.cpu_count())

    return ds
Exemple #5
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def get_dataflow(is_train):
    ds = CocoPoseLMDB('/data/public/rw/coco-pose-estimation-lmdb/', is_train)
    if is_train:
        ds = MapDataComponent(ds, pose_rotation)
        ds = MapDataComponent(ds, pose_flip)
        ds = MapDataComponent(ds, pose_resize_shortestedge_random)
        ds = MapDataComponent(ds, pose_crop_random)
        ds = MapData(ds, pose_to_img)
        augs = [
            imgaug.RandomApplyAug(imgaug.RandomChooseAug([
                imgaug.SaltPepperNoise(white_prob=0.01, black_prob=0.01),
                imgaug.RandomOrderAug([
                    imgaug.BrightnessScale((0.8, 1.2), clip=False),
                    imgaug.Contrast((0.8, 1.2), clip=False),
                    # imgaug.Saturation(0.4, rgb=True),
                ]),
            ]), 0.7),
        ]
        ds = AugmentImageComponent(ds, augs)
    else:
        ds = MapDataComponent(ds, pose_resize_shortestedge_fixed)
        ds = MapDataComponent(ds, pose_crop_center)
        ds = MapData(ds, pose_to_img)

    return ds
Exemple #6
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def get_ilsvrc_data_alexnet(is_train, image_size, batchsize, directory):
    if is_train:
        if not directory.startswith('/'):
            ds = ILSVRCTTenthTrain(directory)
        else:
            ds = ILSVRC12(directory, 'train')
        augs = [
            imgaug.RandomApplyAug(imgaug.RandomResize((0.9, 1.2), (0.9, 1.2)),
                                  0.7),
            imgaug.RandomApplyAug(imgaug.RotationAndCropValid(15), 0.7),
            imgaug.RandomApplyAug(
                imgaug.RandomChooseAug([
                    imgaug.SaltPepperNoise(white_prob=0.01, black_prob=0.01),
                    imgaug.RandomOrderAug([
                        imgaug.BrightnessScale((0.8, 1.2), clip=False),
                        imgaug.Contrast((0.8, 1.2), clip=False),
                        # imgaug.Saturation(0.4, rgb=True),
                    ]),
                ]),
                0.7),
            imgaug.Flip(horiz=True),
            imgaug.ResizeShortestEdge(256, cv2.INTER_CUBIC),
            imgaug.RandomCrop((224, 224)),
        ]
        ds = AugmentImageComponent(ds, augs)
        ds = PrefetchData(ds, 1000, multiprocessing.cpu_count())
        ds = BatchData(ds, batchsize)
        ds = PrefetchData(ds, 10, 4)
    else:
        if not directory.startswith('/'):
            ds = ILSVRCTenthValid(directory)
        else:
            ds = ILSVRC12(directory, 'val')
        ds = AugmentImageComponent(ds, [
            imgaug.ResizeShortestEdge(224, cv2.INTER_CUBIC),
            imgaug.CenterCrop((224, 224)),
        ])
        ds = PrefetchData(ds, 100, multiprocessing.cpu_count())
        ds = BatchData(ds, batchsize)

    return ds