Comments (1)
Hey,
The aspect ratios for those images are preserved whose original width is greater than 384. However, for images with original width less than 384, we decided to resize it to a fixed size of 384 * 384. For such images, the aspect ratios are not preserved. We did this so as to prevent the images from becoming too small. Also, we have conducted experiments at the original image size, and we did not notice any improvement in performance when the training is done at original image size.
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Related Issues (20)
- The standard deviation of the Gaussian kernel HOT 3
- About FSC-147 dataset image licensing? HOT 1
- About other benchmarks HOT 1
- About training time HOT 1
- Details for training few-shot detectors on FSC 147 dataset. HOT 2
- Dot annotations HOT 1
- locate each object which have been counted HOT 1
- Hi, I really like your work.I want to use it for my customized dataset, could you please tell me how can I train it for my customized dataset?plus which format u r using for training? like coco format? HOT 5
- LearningToCountEverything HOT 1
- The multi-scale feature extraction module consists of the first four blocks from a pre-trained ResNet-50 backbone HOT 4
- Questions about the difference between the real image size and annotated image size HOT 4
- How to append new data HOT 2
- Experiments on CARPK HOT 2
- Code for this
- Bounding boxes for FSC HOT 1
- Available platform plugins are: eglfs, minimal, minimalegl, offscreen, vnc, xcb.
- Cannot open Google link "https://drive.google.com/file/d/1ymDYrGs9DSRicfZbSCDiOu0ikGDh5k6S/view?usp=sharing" HOT 3
- how to create my datasets HOT 3
- Cannot open the link "https://archive.org/details/FSC147-GT" HOT 2
- About annotation.json HOT 4
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