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This project demonstrates the use of TensorFlow Object Detection API (along with GCP ML Engine) to automatically detect Red Blood Cells (RBCs), White Blood Cells (WBCs), and Platelets in each image taken via microscopic image readings

License: MIT License

PureBasic 0.01% Jupyter Notebook 99.73% Python 0.26%
deep-learning object-detection tensorflow-object-detection-api ml-engine google-cloud-platform

blood-cell-detection-using-tfod-api's Issues

how to generate mAP for training dataset?

Hi @sayakpaul , Thanks very much for sharing your repository. I have noticed that you have put the tensorboard graph during your presentation. I would like to get some suggestions from you.

  1. how do we get the training metrics like mAP value for every 100 epochs?
  2. how to pass the validation data while training the model, so we can see how well the model perform with validation data?

It would be helpful you can provide us with some information.

Thanks very much :)

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