C-3-Framework
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gjy3035
An open-source PyTorch code for crowd counting
How to calculate the number of people in one picture? Can I just sum the normalized pred_map in your test.py? for exmaple: `pred_map = net.test_forward(img) pred_map = pred_map.cup().data.numpy()[0,0,:,:] pred =...
Could you tell me how to use your framework to train the model in Mall or UCSD?
hi!First of all ,thanks for your subtle framework!!but i have some questions, 1) in code,for example in datasets/SHHA/pre_data.py,you resize the imgs' size so that they can be divided by 16...
请问这个怎么解决
How to add pixel values of the density map. If there is code available?
If we run the test.py code on a single image it returns different density map each time(stored in pred_map) for CSRNet.
It is the test program. **when the program is run this row of code：` f1 = plt.figure(1)` it stops describe the issue and paste the code segment which is in...
Hi @gjy3035 I have trained the model VGG and resnet101-SFCN on my dataset. They didn't converge with the increasing training epochs. The best result for VGG is achieved at epoch...
您好。 您提供的： https://mailnwpueducn-my.sharepoint.com/personal/gjy3035_mail_nwpu_edu_cn/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Fgjy3035%5Fmail%5Fnwpu%5Fedu%5Fcn%2FDocuments%2F%E8%AE%BA%E6%96%87%E5%BC%80%E6%BA%90%E6%95%B0%E6%8D%AE%2FC3Data&originalPath=aHR0cHM6Ly9tYWlsbndwdWVkdWNuLW15LnNoYXJlcG9pbnQuY29tLzpmOi9nL3BlcnNvbmFsL2dqeTMwMzVfbWFpbF9ud3B1X2VkdV9jbi9Fa3h2T1ZKQlZ1eFBzdTc1WWZZaHY5VUJLUkZOUDdXZ0xkeFhGTVNlSEdoWGpRP3J0aW1lPWlzTnpRaFJNMTBn 可以查看，但下载的内容不正确。 另外，请问您使用的matlab的版本是多少？我用7.0执行preapre_SHHB.m，提示有语法错误。
非常感谢您的开源工作，大大减轻了我们的工作量。 现在主要有四点不懂的想向您请教，希望您不吝赐教： 1、我测试了resnet50，csrnet，VGG在shanghai_partA上的MAE，resnet50的MAE大概是110，CSRNET是72，VGG是75，似乎VGG系列在shanghai_partA上表现的更好，这与shanghai_partB不同，请问这是为什么？难道VGG系列在人群密集上的数据集特征提取能力更强？ 2、CSRNET在shanghai_partA上的MAE为72，和您提供的有差距，也不及作者原论文中的68，当然我的batch size设置为1，难道是数据增强的影响吗？因为当batch>1时，会有crop并且BN的表现应该更好。 3、关于 LabelNormalize和提高学习率，您能简单介绍一下区别吗？ 4、语义分割和人群计数的任务十分接近，人群计数中引入FPN这种特征金字塔将1/8的密度图输出转换到和输入相同的大小，是否会比直接上采样更好？ 再次感谢您的工作，希望您能抽空解答我的问题，感激不尽。
