From 6130b70fe7df8ecf542924b1014b2f90b77a0880 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Mon, 9 Mar 2020 16:00:05 -0700 Subject: [PATCH] updates --- models.py | 21 +++++---------------- 1 file changed, 5 insertions(+), 16 deletions(-) diff --git a/models.py b/models.py index 80976a66..9c651342 100755 --- a/models.py +++ b/models.py @@ -87,24 +87,13 @@ def create_modules(module_defs, img_size, arc): # Initialize preceding Conv2d() bias (https://arxiv.org/pdf/1708.02002.pdf section 3.3) try: - p = math.log(1 / (modules.nc - 0.99)) # class probability -> sigmoid(p) = 1/nc - if arc == 'default' or arc == 'Fdefault': # default - b = [-4.5, p] # obj, cls - elif arc == 'uBCE': # unified BCE (80 classes) - b = [0, -9.0] - elif arc == 'uCE': # unified CE (1 background + 80 classes) - b = [10, -0.1] - elif arc == 'uFBCE': # unified FocalBCE (5120 obj, 80 classes) - b = [0, -6.5] - elif arc == 'uFCE': # unified FocalCE (64 cls, 1 background + 80 classes) - b = [7.7, -1.1] + bo = -4.5 #  obj bias + bc = math.log(1 / (modules.nc - 0.99)) # cls bias: class probability is sigmoid(p) = 1/nc bias = module_list[-1][0].bias.view(len(mask), -1) # 255 to 3x85 - bias[:, 4] += b[0] - bias[:, 4].mean() # obj - bias[:, 5:] += b[1] - bias[:, 5:].mean() # cls - # bias = torch.load('weights/yolov3-spp.bias.pt')[yolo_index] # list of tensors [3x85, 3x85, 3x85] - module_list[-1][0].bias = torch.nn.Parameter(bias.view(-1)) - # utils.print_model_biases(model) + bias[:, 4] += bo - bias[:, 4].mean() # obj + bias[:, 5:] += bc - bias[:, 5:].mean() # cls + module_list[-1][0].bias = torch.nn.Parameter(bias.view(-1)) # utils.print_model_biases(model) except: print('WARNING: smart bias initialization failure.')