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https://github.com/piyoki/yolov3-dataloader-cloud
https://github.com/piyoki/yolov3-dataloader-cloud
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/piyoki/yolov3-dataloader-cloud
- Owner: piyoki
- Created: 2020-04-16T08:42:40.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-04-23T06:03:01.000Z (over 4 years ago)
- Last Synced: 2024-10-14T07:36:08.728Z (3 months ago)
- Language: Jupyter Notebook
- Size: 2.24 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## yolov3-dataloader-colab
This tool is tailored for those who want to train their custom dataset on a Yolov3 Model using Colab. \
You may find more info about Google Colab [here](https://medium.com/deep-learning-turkey/google-colab-free-gpu-tutorial-e113627b9f5d).
### Prerequresites
- A valid Google Account to login to Colab
- Setup Yolov3 Darknet correctly on your local machine. If you are a Nvidia Jetson user, you may find instuctions [here](https://pysource.com/2019/08/29/yolo-v3-install-and-run-yolo-on-nvidia-jetson-nano-with-gpu/)
### How to use
- Clone this repository to your local machine by typing the command below in your terminal \
```
$ git clone https://github.com/yqlbu/yolov3-dataloader/
```
- Login to Colab [here](https://colab.research.google.com/)
- Upload "yolov3-dataloader.ipynb" to Colab.
*(You may find the open tab @ File >> Open Notebook)*
- Initiate the VM on Colab, and select the "GPU" one !!! \
*(You may find the option @ Runtime >> Change runtime type >> Hardware Acclerator >> GPU)*
- Hit the "Connect" button on the upper right corner, it is located next to the "edit" button. \
*(Once it is connected, you will see a green click on the upper right corner, and you will also see the hardware spec)*
### Demo
