Features:
- fusion blocks: FPN, PAN, ASFF, BiFPN
- network modules: ResNet, CPS, SPP, RFB
- network architecture search: CSPResNext50, CSPDarknet53, SpineNet49, EfficientNetB0, MixNet-M
- activations: SWISH, MISH
- other features: weighted-[shortcut], Sigmoid scaling (Scale-sensitivity), Label smoothing, Optimal hyper parameters, Dynamic mini batch size for random shapes, Squeeze-and-excitation, Grouped convolution, MixConv (grouped [route]), Elastic-module
- data augmentation: MixUp, CutMix, Mosaic
- losses: MSE, GIoU, CIoU, DIoU
- detection layers: [yolo] (fixed iou_thresh), [Gaussian_yolo]
- detection on video (sequence of frames) - layers: [crnn] (convolutional-RNN), [conv_lstm] (Convolutional LSTM)