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Dataset for car detection on aerial photos applications
Thank you very much for the dataset! What's the unit for the bounding box?
I would guess "2 0.160416666667 0.64212962963 0.11875 0.0527777777778" means bus object with corner at x =0.160416666667image width, y=0.64212962963image height, bounding box width = 0.11875**image width, bounding box height=0.0527777777778*image height. I plotted the bounding box but looks strange.
Thanks a lot! That's a super helpful dataset!
What train/validation split did you use? Any suggestions?
Hello,
How many epochs did you set when training the model? And, is this aerial-cars-dataset just part of your whole training data?
Thank you!
Hello, I'm trying to run your pretrained weights on this dataset, and the prediction results gives some "person" labels. I might be doing something wrong here. Is the following weights and commands the correct ones to use if I wish to reproduce your result on the same dataset?
Thank you very much for your time and help!
Weights:
https://drive.google.com/drive/folders/1fODck5uqfh3AXFE4ArqGcuPvIbdl7Z97
Yolo3:
https://github.com/jekhor/darknet
Commands:
./darknet detect cfg/yolov3-aerial.cfg yolov3-aerial.weights ../aerial-cars-dataset/DJI_0005-0078.jpg
Result:
As you have only a few images here, I am curious if you trained on this dataset from scratch or fine-tuned a few layers in the darknet architecture using a pre-trained model? Could you please share your training strategy?
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