https://github.com/sovit-123/yolov1_pytorch
A simple implementation of YOLOv1 PyTorch and training on the PASCAL VOC dataset.
https://github.com/sovit-123/yolov1_pytorch
pascal-voc yolo yolov1 yolov1-pytorch
Last synced: 6 months ago
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A simple implementation of YOLOv1 PyTorch and training on the PASCAL VOC dataset.
- Host: GitHub
- URL: https://github.com/sovit-123/yolov1_pytorch
- Owner: sovit-123
- Created: 2022-04-17T00:30:17.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-06-19T05:14:34.000Z (over 3 years ago)
- Last Synced: 2025-02-03T10:46:20.239Z (8 months ago)
- Topics: pascal-voc, yolo, yolov1, yolov1-pytorch
- Language: Python
- Homepage:
- Size: 932 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# YOLOV1 Training Pipeline on the PASCAL VOC Data using the PyTorch Framework
This repository contains YOLOV1 training pipeline on the PASCAL VOC 2007 and 2012 data using the PyTorch framework. **A few points:**
## ***Note: Use this repository/code for any project/learning. A simple reference/attribution to the repository is enough. Completely OPEN for any use.***
## Steps to Train
### First of All, Download and Extract the Data (Download to any directory of your choice)
* [Download VOC 2007 trainval from here](http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar).
* Or `wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar` in terminal.
* [Download VOC 2007 test from here](http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar).
* Or `wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar` in terminal.
* [Download the VOC 2012 trainval from here](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar).
* Or `wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar`
Execute the following commands in the directory where the downloaded `.tar` files are present.
```
tar xf VOCtrainval_06-Nov-2007.tar
```
```
tar xf VOCtest_06-Nov-2007.tar
```
```
tar xf VOCtrainval_11-May-2012.tar
```
### Prepare the Text Files and Labels
* Then execute `prepare_data.py` with the correct path argument to the `VOCdevkit` parent directory. Simply, the next folder after the path in the arugment should be `VOCdevkit` The following is an example:
```
python prepare_data.py --path my_pacal_voc_data
```
In the above command `my_pacal_voc_data` should contain the `VOCdevkit` directory for the dataset.
* Then execute `prepare_text_labels.py` with correct command line argument paths to the VOC 2007 and 2012 `Annotations` directory. See [`text_labels.py`](https://github.com/sovit-123/yolov1_pytorch_voc07/blob/main/prepare_text_labels.py) to know what the exact path should be. Example command:
```
python prepare_text_labels.py --annotations-2007 VOCdevkit/VOC2007/Annotations/ --annotations-2012 VOCdevkit/VOC2012/Annotations/
```
### Train
* Execute `python train.py`.
## References
* [YOLOv1 paper](https://arxiv.org/pdf/1506.02640v5.pdf): https://arxiv.org/pdf/1506.02640v5.pdf
* Some dataset preparation ideas borrowed from: https://github.com/aladdinpersson/Machine-Learning-Collection/blob/master/ML/Pytorch/object_detection/YOLO/dataset.py