# YOLOv5 🚀 by Ultralytics, GPL-3.0 license # Parameters nc: 80 # number of classes depth_multiple: 1.0 # save_models depth multiple width_multiple: 1.0 # layer channel multiple anchors: - [10,14, 23,27, 37,58] # P4/16 - [81,82, 135,169, 344,319] # P5/32 # YOLOv3-tiny backbone backbone: # [from, number, module, args] [[-1, 1, Conv, [16, 3, 1]], # 0 [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 1-P1/2 [-1, 1, Conv, [32, 3, 1]], [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 3-P2/4 [-1, 1, Conv, [64, 3, 1]], [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 5-P3/8 [-1, 1, Conv, [128, 3, 1]], [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 7-P4/16 [-1, 1, Conv, [256, 3, 1]], [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 9-P5/32 [-1, 1, Conv, [512, 3, 1]], [-1, 1, nn.ZeroPad2d, [[0, 1, 0, 1]]], # 11 [-1, 1, nn.MaxPool2d, [2, 1, 0]], # 12 ] # YOLOv3-tiny head head: [[-1, 1, Conv, [1024, 3, 1]], [-1, 1, Conv, [256, 1, 1]], [-1, 1, Conv, [512, 3, 1]], # 15 (P5/32-large) [-2, 1, Conv, [128, 1, 1]], [-1, 1, nn.Upsample, [None, 2, 'nearest']], [[-1, 8], 1, Concat, [1]], # cat backbone P4 [-1, 1, Conv, [256, 3, 1]], # 19 (P4/16-medium) [[19, 15], 1, Detect, [nc, anchors]], # Detect(P4, P5) ]