ImageFolder¶
- class paddle.vision.datasets. ImageFolder ( root, loader=None, extensions=None, transform=None, is_valid_file=None ) [源代码] ¶
一种通用的数据加载方式,数据需要以如下的格式存放:
root/1.ext
root/2.ext
root/sub_dir/3.ext
参数¶
root (str) - 根目录路径。
loader (Callable,可选) - 可以加载数据路径的一个函数,如果该值没有设定,默认使用
cv2.imread
。默认值为 None。extensions (list[str]|tuple[str],可选) - 允许的数据后缀列表,
extensions
和is_valid_file
不可以同时设置。如果该值没有设定,默认为('.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '.tif', '.tiff', '.webp')
。默认值为 None。transform (Callable,可选) - 图片数据的预处理,若为
None
即为不做预处理。默认值为None
。is_valid_file (Callable,可选) - 根据每条数据的路径来判断是否合法的一个函数。
extensions
和is_valid_file
不可以同时设置。默认值为 None。
属性¶
samples (list[str]) - 样本路径列表。
代码示例¶
import shutil
import tempfile
import cv2
import numpy as np
import paddle.vision.transforms as T
from pathlib import Path
from paddle.vision.datasets import ImageFolder
def make_fake_file(img_path: str):
if img_path.endswith((".jpg", ".png", ".jpeg")):
fake_img = np.random.randint(0, 256, (32, 32, 3), dtype=np.uint8)
cv2.imwrite(img_path, fake_img)
elif img_path.endswith(".txt"):
with open(img_path, "w") as f:
f.write("This is a fake file.")
def make_directory(root, directory_hierarchy, file_maker=make_fake_file):
root = Path(root)
root.mkdir(parents=True, exist_ok=True)
for subpath in directory_hierarchy:
if isinstance(subpath, str):
filepath = root / subpath
file_maker(str(filepath))
else:
dirname = list(subpath.keys())[0]
make_directory(root / dirname, subpath[dirname])
directory_hirerarchy = [
"abc.jpg",
"def.png",
{"ghi": [
"jkl.jpeg",
{"mno": [
"pqr.jpg"]}]},
"this_will_be_ignored.txt",
]
# You can replace this with any directory to explore the structure
# of generated data. e.g. fake_data_dir = "./temp_dir"
fake_data_dir = tempfile.mkdtemp()
make_directory(fake_data_dir, directory_hirerarchy)
image_folder_1 = ImageFolder(fake_data_dir)
print(image_folder_1.samples)
# ['./temp_dir/abc.jpg', './temp_dir/def.png',
# './temp_dir/ghi/jkl.jpeg', './temp_dir/ghi/mno/pqr.jpg']
print(len(image_folder_1))
# 4
for i in range(len(image_folder_1)):
(img,) = image_folder_1[i]
# do something with img
print(type(img), img.size)
# <class 'PIL.Image.Image'> (32, 32)
transform = T.Compose(
[
T.Resize(64),
T.ToTensor(),
T.Normalize(
mean=[0.5, 0.5, 0.5],
std=[0.5, 0.5, 0.5],
to_rgb=True,
),
]
)
image_folder_2 = ImageFolder(
fake_data_dir,
loader=lambda x: cv2.imread(x), # load image with OpenCV
extensions=(".jpg",), # only load *.jpg files
transform=transform, # apply transform to every image
)
print(image_folder_2.samples)
# ['./temp_dir/abc.jpg', './temp_dir/ghi/mno/pqr.jpg']
print(len(image_folder_2))
# 2
for (img,) in iter(image_folder_2):
# do something with img
print(type(img), img.shape)
# <class 'paddle.Tensor'> [3, 64, 64]
shutil.rmtree(fake_data_dir)