| OpenCV 4.3.0 Open Source Computer Vision

Classes
Super Resolution
Framework for working with different datasets

## Classes
class | cv::datasets::SR_bsds
struct | cv::datasets::SR_bsdsObj
class | cv::datasets::SR_div2k
struct | cv::datasets::SR_div2kObj
class | cv::datasets::SR_general100
struct | cv::datasets::SR_general100Obj

## Detailed Description

### The Berkeley Segmentation Dataset and Benchmark

Implements loading dataset:

"The Berkeley Segmentation Dataset and Benchmark": https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/segbench/

Usage:

1. From link above download `BSDS300-images.tgz`.
2. Unpack.
3. To load data run:
   ./opencv/build/bin/example_datasets_sr_bsds -p=/home/user/path_to_unpacked_folder/

### DIV2K dataset: DIVerse 2K

Implements loading dataset:

"DIV2K dataset: DIVerse 2K": https://data.vision.ee.ethz.ch/cvl/DIV2K/

Usage:

1. From link above download 'Train data (HR images)' or any other of the dataset files.
2. Unpack.
3. To load data run:
   ./opencv/build/bin/example_datasets_sr_div2k -p=/home/user/path_to_unpacked_folder/folder_containing_the_images/

### The General-100 Dataset

Implements loading dataset:

"General-100 dataset contains 100 bmp-format images (with no compression). We used this dataset in our FSRCNN ECCV 2016 paper. The size of these 100 images ranges from 710 x 704 (large) to 131 x 112 (small). They are all of good quality with clear edges but fewer smooth regions (e.g., sky and ocean), thus are very suitable for the super-resolution training.": http://mmlab.ie.cuhk.edu.hk/projects/FSRCNN.html

Usage:

1. From link above download `General-100.zip`.
2. Unpack.
3. To load data run:
   ./opencv/build/bin/example_datasets_sr_general100 -p=/home/user/path_to_unpacked_folder/