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HaloTrouvaille / YOLO-Multi-Backbones-Attention

Model Compression—YOLOv3 with multi lightweight backbones(ShuffleNetV2 HuaWei GhostNet), attention, prune and quantization
https://github.com/HaloTrouvaille/YOLO-Multi-Backbones-Attention
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Parameters for Ghostnet + YoloV3 #17

Closed ghost closed 3 years ago

ghost commented 3 years ago

Hi, You have mentioned the number of parameters for Ghostnet + Yolov3 to be 23.49M. I wanted to confirm if it is correct or it should be 2.349M? The number of parameters seem to be too larger than the other models.

Thanks.

HaloTrouvaille commented 3 years ago

Because I didn't change the head of yolov3, so its size is relatively large though the backbone is small

ghost commented 3 years ago

Ok, Thanks.