A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Spiking-YOLOv3-Tiny at present.
GNU General Public License v3.0
207
stars
58
forks
source link
Is it possible to fine-tune using Darknet weights #29
Hi community, first of all, thanks for this amazing contribution.
I was wondering if it is possible to fine tune a pre-trained yolo network, for that I assume that --weights parameter should point to a downloaded file, in my case darknet53.conv.74 and then use --freze parameter and set it to True.
Sorry, it is impossible to fine-tune directly using Darknet weights. Because some operators(layers) can't be supported for now. You have to convert them first and train a converted pre-train model.
Hi community, first of all, thanks for this amazing contribution.
I was wondering if it is possible to fine tune a pre-trained yolo network, for that I assume that
--weights
parameter should point to a downloaded file, in my case darknet53.conv.74 and then use--freze
parameter and set it to True.Would the conversion to spiking be run properly?
Thanks in advance!