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dataset.py
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dataset.py
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import torch
from torch.utils.data import Dataset
import os.path as osp
from PIL import Image
import numpy as np
from glob import glob
from os.path import splitext
def read_gen(file_name, pil=False):
ext = splitext(file_name)[-1]
if ext == '.png' or ext == '.jpeg' or ext == '.ppm' or ext == '.jpg':
return Image.open(file_name)
class VideoDataset(Dataset):
def __init__(self,
root: str):
super(VideoDataset, self).__init__()
self.root = root
self.image_list = []
self.diff = []
images = sorted(glob(osp.join(self.root, '*.jpg')))
if len(images) == 0:
images = sorted(glob(osp.join(self.root, '*.png')))
self.image_list = images
def __len__(self):
return len(self.image_list)
def __getitem__(self, idx):
img = read_gen(self.image_list[idx])
img = np.array(img).astype(np.uint8)[..., :3]
H, W, _ = img.shape
img = img[:H//4*4, :W//4*4, :]
img = torch.from_numpy(img).permute(2, 0, 1).float()
return img