Tencent / ObjectDetection-OneStageDet

单阶段通用目标检测器

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New weight file syntax

Adrian-Yan16 opened this issue · comments

2022-10-24 17:14:18,275:DEBUG:Creating network
2022-10-24 17:14:18,320:DEBUG:Loading weights from darknet file
2022-10-24 17:14:18,320:DEBUG:Loading weight file: version 67324752.134742016.0
2022-10-24 17:14:18,320:ERROR:New weight file syntax! Loading of weights might not work properly. Please submit an issue with the weight file version number. [Run with DEBUG logging level]
2022-10-24 17:14:18,336:DEBUG:Layer skipped: TinyYolov3
2022-10-24 17:14:18,336:DEBUG:Layer skipped: TinyYolov3
2022-10-24 17:14:18,337:INFO:Net structure
TinyYolov3(
(backbone): TinyYolov3(
(layers): ModuleList(
(0): Sequential(
(0_convbatch): Conv2dBatchLeaky (3, 16, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
(1_max): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(2_convbatch): Conv2dBatchLeaky (16, 32, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
(3_max): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(4_convbatch): Conv2dBatchLeaky (32, 64, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
)
(1): Sequential(
(5_max): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(6_convbatch): Conv2dBatchLeaky (64, 128, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
)
(2): Sequential(
(7_max): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(8_convbatch): Conv2dBatchLeaky (128, 256, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
)
(3): Sequential(
(9_max): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(10_convbatch): Conv2dBatchLeaky (256, 512, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
(11_max): MaxPool2d(kernel_size=3, stride=1, padding=1, dilation=1, ceil_mode=False)
(12_convbatch): Conv2dBatchLeaky (512, 1024, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
(13_convbatch): Conv2dBatchLeaky (1024, 256, kernel_size=1, stride=1, padding=0, negative_slope=0.1)
)
)
)
(head): TinyYolov3(
(layers): ModuleList(
(0): Sequential(
(14_convbatch): Conv2dBatchLeaky (256, 512, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
(15_conv): Conv2d(512, 24, kernel_size=(1, 1), stride=(1, 1))
)
(1): Sequential(
(18_convbatch): Conv2dBatchLeaky (256, 128, kernel_size=1, stride=1, padding=0, negative_slope=0.1)
(19_upsample): Upsample(scale_factor=2.0, mode=nearest)
)
(2): Sequential(
(21_convbatch): Conv2dBatchLeaky (384, 256, kernel_size=3, stride=1, padding=1, negative_slope=0.1)
(22_conv): Conv2d(256, 24, kernel_size=(1, 1), stride=(1, 1))
)
)
)
)