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Train new pretrained model #278
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I got a similar problem, my dataset has resolution 640x480 and my objects has around 80x30, to increase my performance I removed a convolution block from TinyDarknet, so the grid got a size of 16x16 instead 8x8 |
Presumably you'll need to adjust your anchors when training on the HD images - are you doing that? |
I am generating the anchors as shown in the readme file with gen_anchors. I am also confused because the anchor ratios are near to zero |
how do we generate own anchors for our custom dataset with the help of gen_anchors.py? |
@shivaram93 you just need to run the script and pass the config file as an argument. Make sure to adjust the config file to match your needs. |
Hello,
All the pretrained models didn't result in good accuracy.
So I decided to train my own pretrained model.
I have very small grasses to detect, in an image of 1920x1080 they aren't bigger than 100x100 pixels. So I trained Full Yolo on a 100x100 dataset, my accuracy is roundabout 90%.
When I use these model weights as Backend_pretrained model and start training yolo on HD images, the accuracy starts at 0.15 and degrees down to zero. I have no Recalls.
I can't find my mistake. Isn't yolo able to detect object with large x and very small y dimension? Do I have to note something by training the pretrained model?
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