MNIST Double Digits Datasets Classification and Detectection
Datasets:
- 64x64 size images containing two digits
- digits range [0, 9]
- digits size (bounding box size) 28x28
Algorithm used:
-
Classes: classification
- two digits range from 0 to 9
- model returned labels range from 0 to 19
- reshape the labels into shape [N, 2]
- each n data contain two class that the two digits belongs to
-
Bounding Boxes: Classification
- two digits' position ranges from 0 to 37 ((64+1)-28)
- model returned labels range from 0 to 148 (4*37)
- reshape the labels in to shape [N, 2, 4]
- each n data contain [x1, y1, x1+28, y1+28], [x2, y2, x2+28, y2+28] where x and y represents the axis and 1 and 2 represent first and second digits
Model:
Result:
- Validation datasets with model.pt.172:
- Classification accuracy: 99.63
- Detection IoU: 95.17
- Valid time (GPU): ≈23.28
- Valid time (CPU): ≈418