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wheat's Introduction

wheat_detection

This is my repository with a baseline model for Wheat Detection challenge on Kaggle

Main frameworks used:

To use it for training, perform the following steps:

  • download the data, unzip in and put in some folder;
  • define that folder in config conf/data/data.yaml as a value of the key data.folder_path
  • run run_hydra.py script

There is no script for prediction, because in this competition we have to make prediction in kernels.

Refer to my kernel for more information: https://www.kaggle.com/artgor/object-detection-with-pytorch-lightning

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erlemar avatar tappyness1 avatar

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wheat's Issues

Pip install -r requirements.txt fails

Hi there I've tried to pip install the dependencies but I get the following error both on Ubuntu 18 and macOS ERROR: Could not find a version that satisfies the requirement pytorch_lightning==0.8.0. Any idea? Did you use python2?

Why is there no losses.backward and optimizer.step on training_steps?

I am using this as a baseline on my custom dataset. While I have used Pytorch for FasterRCNN before (not with Pytorch Lightning), I am curious as to why it does not have the typical ending of each training step like the ff:

...
losses = sum(loss for loss in loss_dict.values())
optimizer.zero_grad()
losses.backward()
optimizer.step()
...

I am not seeing this being implemented explicitly in the code and the utils. Am I missing something why isnt this included?

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