https://github.com/soumith/traffic-sign-detection-homework
nyu-cv-fall-2017 assignment 3
https://github.com/soumith/traffic-sign-detection-homework
Last synced: 4 months ago
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nyu-cv-fall-2017 assignment 3
- Host: GitHub
- URL: https://github.com/soumith/traffic-sign-detection-homework
- Owner: soumith
- Created: 2017-11-02T16:10:02.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-10-15T20:24:08.000Z (over 6 years ago)
- Last Synced: 2024-12-13T06:44:41.935Z (4 months ago)
- Language: Python
- Size: 7.81 KB
- Stars: 51
- Watchers: 4
- Forks: 40
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## NYU-CV-Fall-2018
### Assignment 2: Traffic sign competition
#### Requirements
1. Install PyTorch from http://pytorch.org
2. Run the following command to install additional dependencies
```bash
pip install -r requirements.txt
```
#### Training and validating your model
Run the script `main.py` to train your model.
Modify `main.py`, `model.py` and `data.py` for your assignment, with an aim to make the validation score better.
- By default the images are loaded and resized to 32x32 pixels and normalized to zero-mean and standard deviation of 1. See data.py for the `data_transforms`.
- By default a validation set is split for you from the training set and put in `[datadir]/val_images`. See data.py on how this is done.
#### Evaluating your model on the test set
As the model trains, model checkpoints are saved to files such as `model_x.pth` to the current working directory.
You can take one of the checkpoints and run:
```
python evaluate.py --data [data_dir] --model [model_file]
```
That generates a file `gtsrb_kaggle.csv` that you can upload to the private kaggle competition https://www.kaggle.com/c/nyu-cv-fall-2018/ to get onto the leaderboard.