https://github.com/koushik-elite/dog-identification-app
Implementation of Convolutional Neural Networks using Dog Identification App
https://github.com/koushik-elite/dog-identification-app
Last synced: 2 months ago
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Implementation of Convolutional Neural Networks using Dog Identification App
- Host: GitHub
- URL: https://github.com/koushik-elite/dog-identification-app
- Owner: koushik-elite
- Created: 2019-03-04T02:12:18.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2019-03-04T02:20:55.000Z (about 6 years ago)
- Last Synced: 2025-01-22T01:36:34.977Z (4 months ago)
- Language: Jupyter Notebook
- Size: 2.13 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Dog-Identification-App
## Convolutional Neural Networks
### Project: Write an Algorithm for a Dog Identification App
Implementation of Convolutional Neural Networks using Dog Identification App
In this notebook, you will make the first steps towards developing an algorithm that could be used as part of a mobile or web app. At the end of this project, your code will accept any user-supplied image as input. If a dog is detected in the image, it will provide an estimate of the dog's breed. If a human is detected, it will provide an estimate of the dog breed that is most resembling
Final Project [Notebook](/dog_app.ipynb)
## 1. Installation
Download Anaconda
| | Linux | Mac | Windows |
|--------|-------|-----|---------|
| 64-bit | [64-bit (bash installer)][lin64] | [64-bit (bash installer)][mac64] | [64-bit (exe installer)][win64]
| 32-bit | [32-bit (bash installer)][lin32] | | [32-bit (exe installer)][win32]
[win64]: https://repo.anaconda.com/archive/Anaconda3-2018.12-Windows-x86_64.exe
[win32]: https://repo.anaconda.com/archive/Anaconda3-2018.12-Windows-x86.exe
[mac64]: https://repo.anaconda.com/archive/Anaconda3-2018.12-MacOSX-x86_64.sh
[lin64]: https://repo.anaconda.com/archive/Anaconda3-2018.12-Linux-x86_64.sh
[lin32]: https://repo.anaconda.com/archive/Anaconda3-2018.12-Linux-x86.sh
**Install** [Anaconda](https://docs.anaconda.com/anaconda/install/) on your machine. Detailed instructions:
## 2. Create and Activate the Environment
Please go though this [doc](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) before you creating an environment.
After that create a environment using following command
```
conda create --name deep-learning
```
Then activate the environment using following command
```
activate deep-learning
```
#### Git and version control
These instructions also assume you have `git` installed for working with Github from a terminal window, but if you do not, you can download that first with the command:
```
conda install git
```
**Now, you can create a local version of the project**
1. Clone the repository, and navigate to the downloaded folder. This may take a minute or two to clone due to the included image data.
```
git clone https://github.com/koushik-elite/Dog-Identification-App.git
cd TV-Script-Generation
```
2. Install PyTorch and torchvision; this should install the latest version of PyTorch.
- __Linux__ or __Mac__:
```
conda install pytorch torchvision -c pytorch
```
- __Windows__:
```
conda install pytorch -c pytorch
pip install torchvision
```
3. Install a few required pip packages, which are specified in the requirements text file (including OpenCV).
```
pip install -r requirements.txt
```
4. That's it!, Now run the project using following command, check you default browser and open dog_app.ipynb file
```
jupyter notebook
```