In this task, a learning algorithm needs to recognize whether a rectangle contained in an image has a larger width or length. The rectangle can be situated anywhere in the 28 x 28 pixel image. We generated two datasets for this problem:
All the datasets are provided as zip archives. Each archive contains two files -- a training (and validation) set and a test set. We used the last 2000 examples of the training sets as validation sets for rectangles-images and 200 for rectangles. In the case of SVMs, retrained the models with the entire set after choosing the optimal parameters on these validation sets. Data is stored at one example per row, the features being space-separated. There are 784 features per example (=28*28 images), corresponding to the first 784 columns of each row. The last column is the label, which is 1 or 0.
Link to dataset | Size | File description |
---|---|---|
Rectangles | 2.7M packed; 599M + 15M unpacked | 12000 train, 50000 test |
Rectangles images | 82M packed; 599M + 144M unpacked | 12000 train, 50000 test |
Please contact us if you are interested in the (MATLAB) scripts that we used to generate this data.
-- DumitruErhan - 21 Jun 2007
I | Attachment | Action | Size | Date | Who | Comment |
---|---|---|---|---|---|---|
png | rectangles_images.png | manage | 9.5 K | 21 Jun 2007 - 11:07 | DumitruErhan | Rectangles images |
png | rectangles.png | manage | 1.0 K | 21 Jun 2007 - 11:08 | DumitruErhan | Rectangles |