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The pretrained weights on ImageNet #1
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@libzzluo yes it takes a long time to train from scratch. I've not trained ImageNet, only COCO and xView, and in general if takes about 100-200 epochs to fully train (before overtraining begins). On COCO I get about 10-15 epochs per day on a 1080 Ti, depending on the augmentation used on the input images (augmentation is generally slow, though I've sped it up as fast as I could using the latest opencv functions). About your second question I'm not sure I understand. The only pretrained weights I've used with the model are the yolov3 weights you can download by:
These darknet weights are loaded with weights_path = 'checkpoints/yolov3.weights'
if weights_path.endswith('.weights'): # saved in darknet format
load_weights(model, weights_path)
else: # endswith('.pt'), saved in pytorch format
checkpoint = torch.load(weights_path, map_location='cpu')
model.load_state_dict(checkpoint['model'])
del checkpoint |
@glenn-jocher If I understand correctly, your train.py trains a model (in this case a darknet on coco) from scratch, but not with an option to start the training with loading a pre-trained weight? |
update from original master
@glenn-jocher
Hi, First of all, thank you very much for your code. I have started training for 24 hours (10 epochs) on my GTX1080, but it seems that I can't load the pre-trained weights on ImageNet (the
darknet53.comv
). And it takes long time to train from scratch. TATThe text was updated successfully, but these errors were encountered: