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crowd-counting-cnn

This implementation is from mcnn-tensorflow The author implements MCNN model on Shanghaitech dataset.

I just modified some details to create UCSD dataset and UCF_50 dataset and test the MCNN model on these dataset.

I am not sure whether it is okay to upload the modified implementation and if it is wrong, please contatct me and I will delete it. [email protected].

UCF_50

在MCNN上测试UCF_50dataset，根据论文设置，使用5折交叉验证，所以，数据集分成了5份。而且，每一张图片截取9个patch，这样总数据大小是$50\times9=450$. 训练的时候每一个输入是一个patch，测试的时候也是一个patch。但是，在计算mae​和mse时，一定要将9个patch合并计算，这样得到的mae​和mse才是一张图片的测试结果。

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crowd-counting-cnn's Issues

Query on Model training

Hello

First of all thanks for your work. :)

I just had a small query. Using the architecture generally two data sets are separately trained on and two models are created , one on data set A and one on data set B. My query is can we not use only one model on both the datasets and use it for predictions on both the images on data set A and Data set B. I mean I am not clear why are we training the models separately on data set a and data set b.

Thanks and Regards
Arpit

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