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182 compooter wision fwinal pwoject
Hello, here are instructions for running inference on our project: File Content: README.txt - This file requirements.txt - The python requirments necessary to run this project train_sample.py - A sample training file which trains a simple model on the data, and save the checkpoint to be loaded in the test_submission.py file. conform_validation_set.py - python script needed to reformat the validation set to match what the training script is expecting. test_submission.py - The file which will return an output for every input in the eval.csv eval.csv - An example test file data/get_data.sh - A script which will download the tiny-imagenet data into the data/tiny-imagenet-200 file Note: You should be using Python 3 to run this code. To run inferences first install dependencies through `pip3 install -r requirements.txt`, and then run script: `python3 test_submission.py eval.csv`. Training is relatively straightforward as well. Please do the following from the directory this file is in: `pip3 install -r requirements.txt` if you haven't already. Then run the data downloading script `./data/get_data.sh` Then conform the validation dataset: `python3 conform_validation_set.py`. A folder called val-fixed will be created Finally, run `python3 train_sample_torch.py` Validation of the data is easy too: `python3 evaluation_tools.py`
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