How to input images and have them count only

[sima05020]

I was able to successfully run the test case using train_val.py, but when I wanted to test the effect of this code on the general image case, I couldn't figure out how to get the count results by inputting only the query image we had prepared and the cropped support image. Do I have to prepare a json file with the boxes and points information?

If anyone is reading this, I would like to know.

I write this description with DeepL , so sorry for some discomfort.

[zhiyuanyou]

Hello, thanks for your question.

Our codes have two settings.

• The support images are in the query image.
• The support images are not in the query image.

I think you are in the second case.

In this case, you need to:

• First, pre-train the model in FSC-147. Please directly run this shell https://github.com/zhiyuanyou/SAFECount/blob/main/experiments/FSC147_to_CARPK/pretrain/pretrain_torch.sh.

• Second, organize your support images as exemplar.json. Please refer to https://github.com/zhiyuanyou/SAFECount/blob/main/data/CARPK_devkit/exemplar.json and organize your own json file.

• Then, with the pre-trained weights and exemplar.json, you need to set the exemplar.json in your own config file (Please refer to https://github.com/zhiyuanyou/SAFECount/blob/main/experiments/CARPK/config.yaml) and run eval shell (The same as https://github.com/zhiyuanyou/SAFECount/blob/main/experiments/CARPK/eval_torch.sh).

Feel free to let me know if you have further questions.