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Hi Author,
Great work. Could you please answer me two questions?
1. What is the ground truth data you used to train the ISP from SID data.
In your code `train_isp.py`, I found `gt_paths = gl…
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I would like to ask how Data Augmentation is performed in the case of the Baseline RCNN that only uses groundtruth ROIs as Primary Regions.
More specifically within the paper, you mention that:
…
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下面是yolov4原论文中给出的方法,请问您的代码全部实现了这些功能吗?如果没有的话具体哪些还没有实现呢?谢谢!
YOLO v4 uses:
• Bag of Freebies (BoF) for backbone: CutMix and Mosaic data augmentation, DropBlock regularization,Class label smoothing
• …
TMRin updated
4 years ago
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Hello,
I would like to ask, if I want to retrain the models on the UCF and JHU datasets, what changes need to be made to the existing code?
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Thanks for this light weight faster rcnn implementation!
However, I have been using Detectron2, and it is able to train on images without objects.
I think it would be good to use them as negative e…
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I was wondering if it is possible to use Augmentor to augment a single image or augment multiple images in exactly the same manner (e.g. multiple np.array as input, not filename)? if you have image +…
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Hi,
Thanks for sharing the code. I am recently trying to train the R-MVSNet on a subset of ScanNet dataset. I first run the colmap and then using the provided code to get the ```cam.txt``` and ```pa…
fuy34 updated
2 years ago
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Hi,
have you tried training on real scene such as market or subway? I have finetuned the model according to IRR-PWC by using your './checkpoints/fastflownet_ft_mix.pth' in subway real scene, but th…
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@AlexeyAB @lukeai is there a way to show the ground truth on predicted images when using:
`darknet.exe detector test data/obj.data yolo-obj.cfg yolo-obj_8000.weights`
Thank you !
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Hello
How are you?
Thanks for contributing to this project.
I found that you used a random crop of images in the training step.
If we random-crop the images, I think that the boxes info should be …