You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: I'd like to train a super-resolution network.

Keyphrases: single image super-resolution images

Dataset description:
REDS: The realistic and dynamic scenes (REDS) dataset was proposed in the NTIRE19 Challenge. The dataset is composed of 300 video sequences with resolution of 720×1,280, and each video has 100 frames, where the training set, the validation set and the testing set have 240, 30 and 30 videos, respectively
ImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.
Flickr1024: Contains 1024 pairs of high-quality images and covers diverse scenarios.
OST300: OST300 is an outdoor scene dataset with 300 test images of outdoor scenes, and a training set of 7 categories of images with rich textures.
DRealSR: DRealSR establishes a Super Resolution (SR) benchmark with diverse real-world degradation processes, mitigating the limitations of conventional simulated image degradation. It has been collected from five DSLR cameras in natural scenes and cover indoor and outdoor scenes avoiding moving objects, e.g., advertising posters, plants, offices, buildings.
BSD: BSD is a dataset used frequently for image denoising and super-resolution. Of the subdatasets, BSD100 is aclassical image dataset having 100 test images proposed by Martin et al..
Set5: The Set5 dataset is a dataset consisting of 5 images (“baby”, “bird”, “butterfly”, “head”, “woman”) commonly used for testing performance of Image Super-Resolution models.

Options:- A: REDS  B: ImageNet  C: Flickr1024  D: OST300  E: DRealSR  F: BSD  G: Set5
["ImageNet", "Set5"]