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darpan-jain / crowd-counting-using-tensorflow

Tensorflow implementation of crowd counting using CNNs from overhead surveillance cameras.
MIT License
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How to use a larger dataset to build the model. #1

Closed SherlockHua1995 closed 5 years ago

SherlockHua1995 commented 5 years ago

Hello, thanks for your code. I am working on this field too and I want to build a project that counting people under a surveillance camera. How to use a large dataset to train the model? Although you have mentioned in readme , I didn't found the LabelImg . Any help would be appreciated.

darpan-jain commented 5 years ago

Hey @SherlockHua1995, here's the link for LabelImg (https://github.com/tzutalin/labelImg) This tool is pretty straightforward to use and will give you the coordinates of bounding boxes as XML files for each image, which can be converted to a csv and then into a TFR format. The csv and TFR conversion code is available in the official Tensorflow repo. You can also have look at these links for the same:

  1. https://pythonprogramming.net/creating-tfrecord-files-tensorflow-object-detection-api-tutorial/
  2. https://stackoverflow.com/questions/41402332/tensorflow-create-a-tfrecords-file-from-csv

Hope this helps!

SherlockHua1995 commented 5 years ago

Thanks for your reply. Is the train set in your repository made by yourself ? And what size of the training set is sufficient for a accurate model to count the people ? yours~

darpan-jain commented 5 years ago

Hey! Yes the train set is created by me using LabelImg. The size of the training set depends more your use case. You could try will about a 100 annotated images and add images as per the required accuracy. Thanks!