1.3. Data

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1.3.1. Introducation

This document introduces the preparation of ImageNet1k and flowers102

1.3.2. Dataset

Dataset	train dataset size	valid dataset size	category
flowers102	1k	6k	102
ImageNet1k	1.2M	50k	1000

• Data format

Please follow the steps mentioned below to organize data, include train_list.txt and val_list.txt

# delimiter: "space"

ILSVRC2012_val_00000001.JPEG 65
...

1.3.2.1. ImageNet1k

After downloading data, please organize the data dir as below

PaddleClas/dataset/imagenet/
|_ train/
|  |_ n01440764
|  |  |_ n01440764_10026.JPEG
|  |  |_ ...
|  |_ ...
|  |
|  |_ n15075141
|     |_ ...
|     |_ n15075141_9993.JPEG
|_ val/
|  |_ ILSVRC2012_val_00000001.JPEG
|  |_ ...
|  |_ ILSVRC2012_val_00050000.JPEG
|_ train_list.txt
|_ val_list.txt

1.3.2.2. Flowers102 Dataset

Download Data then decompress:

jpg/
setid.mat
imagelabels.mat

Please put all the files under PaddleClas/dataset/flowers102

generate generate_flowers102_list.py and train_list.txt和val_list.txt

python generate_flowers102_list.py jpg train > train_list.txt
python generate_flowers102_list.py jpg valid > val_list.txt

Please organize data dir as below

PaddleClas/dataset/flowers102/
|_ jpg/
|  |_ image_03601.jpg
|  |_ ...
|  |_ image_02355.jpg
|_ train_list.txt
|_ val_list.txt