unuse

experiments/dataset/dataloader.py

-##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-## Created by: Hang Zhang
-## ECE Department, Rutgers University
-## Email: zhang.hang@rutgers.edu
-## Copyright (c) 2017
-##
-## This source code is licensed under the MIT-style license found in the
-## LICENSE file in the root directory of this source tree 
-##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-
-# refer to https://github.com/pytorch/vision/blob/master/torchvision/
-import torch.utils.data as data
-import torchvision
-
-from PIL import Image
-import os
-import os.path
-
-IMG_EXTENSIONS = [
-    '.jpg', '.JPG', '.jpeg', '.JPEG',
-    '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP',
-]
-
-
-def is_image_file(filename):
-    return any(filename.endswith(extension) for extension in IMG_EXTENSIONS)
-
-
-def find_classes(dir):
-    classes = [d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d))]
-    classes.sort()
-    class_to_idx = {classes[i]: i for i in range(len(classes))}
-    return classes, class_to_idx
-
-
-def make_dataset(dir, class_to_idx):
-    images = []
-    for target in os.listdir(dir):
-        d = os.path.join(dir, target, 'images')
-        if not os.path.isdir(d):
-            continue
-
-        for root, _, fnames in sorted(os.walk(d)):
-            for fname in fnames:
-                if is_image_file(fname):
-                    path = os.path.join(root, fname)
-                    item = (path, class_to_idx[target])
-                    images.append(item)
-
-    return images
-
-
-def default_loader(path):
-    return Image.open(path).convert('RGB')
-
-
-class DatasetLoader(data.Dataset):
-    def __init__(self, root, transform=None, target_transform=None,
-                 loader=default_loader):
-        classes, class_to_idx = find_classes(root)
-        imgs = make_dataset(root, class_to_idx)
-        if len(imgs) == 0:
-            raise(RuntimeError("Found 0 images in subfolders of: " + root \
-                + "\nSupported image extensions are: " + \
-                ",".join(IMG_EXTENSIONS)))
-
-        self.root = root
-        self.imgs = imgs
-        self.classes = classes
-        self.class_to_idx = class_to_idx
-        self.transform = transform
-        self.target_transform = target_transform
-        self.loader = loader
-
-    def __getitem__(self, index):
-        path, target = self.imgs[index]
-        img = self.loader(path)
-        if self.transform is not None:
-            img = self.transform(img)
-        if self.target_transform is not None:
-            target = self.target_transform(target)
-
-        return img, target
-
-    def __len__(self):
-        return len(self.imgs)
-
-
-def annotation_reader(root, class_to_idx):
-    # read the tiny imagenet annotations.txt and returns the imgs and class
-    file = open(os.path.join(root,'val_annotations.txt'), 'r')
-    images = []
-    for line in file:
-        sp = line.split('\t')
-        path = os.path.join(root,'images',sp[0])
-        item = [path, class_to_idx[sp[1]]]
-        images.append(item)
-
-    return images
-
-
-class ValDatasetLoader(data.Dataset):
-    def __init__(self, root, classes, class_to_idx, 
-            transform=None, target_transform=None, loader=default_loader):
-        imgs = annotation_reader(root, class_to_idx)
-        self.root = root
-        self.imgs = imgs
-        self.classes = classes
-        self.class_to_idx = class_to_idx
-        self.transform = transform
-        self.target_transform = target_transform
-        self.loader = loader
-
-    def __getitem__(self, index):
-        path, target = self.imgs[index]
-        img = self.loader(path)
-        if self.transform is not None:
-            img = self.transform(img)
-        if self.target_transform is not None:
-            target = self.target_transform(target)
-
-        return img, target
-
-    def __len__(self):
-        return len(self.imgs)
-