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PaddleData

Document Tutorial

Installation

• Environment dependence:
  • PaddlePaddle >= 2.3.0
  • Python >= 3.6
  • CUDA >= 10.1

install with pip

pip

pip install paddledata

from source

python setup.py install

Examples

# load imagenet dataset
import sys
import time
import paddle
import paddledata

data_root = '/path/to/imagenet/ILSVRC2012/train/'

def imagenet_pipeline():
    image, label = paddle.vision.reader.file_label_reader(data_root, 
                                                          batch_size=64, 
                                                          shuffle=True, 
                                                          drop_last=True)

    def decode(image):
        image = paddledata.ops.decode_random_crop(image)
        return image

    def resize(image):
        image = paddle.vision.ops.image_resize(image, size=224, data_format='NHWC')
        return image
    def transpose(image):
        image = paddle.transpose(image, [0, 3, 1, 2])
        return image

    image = paddle.io.map(decode, image)

    image = paddle.io.map(resize, image)

    return {'image': image, 'label': label}


dataloader = paddle.io.DataLoader(imagenet_pipeline)

for i, data in enumerate(dataloader):
    print('index:', i, data['image'].shape, data['image'].place, data['image'].dtype)

Changelog

• v0.1.0 (2023.04.15)
  • Release first version

Contributing

Contributions and suggestions are highly welcomed. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring. When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA. Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA. For more, please reference contribution guidelines.

License

PaddleGAN is released under the Apache 2.0 license.