https://github.com/samuelfolledo/custom_ai_in_ios
Object detection iOS app that scores rock paper scissor game for you
https://github.com/samuelfolledo/custom_ai_in_ios
machine-learning object-detection python swift swiftui tutorial
Last synced: 29 days ago
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Object detection iOS app that scores rock paper scissor game for you
- Host: GitHub
- URL: https://github.com/samuelfolledo/custom_ai_in_ios
- Owner: SamuelFolledo
- Created: 2021-03-25T07:10:36.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2022-08-28T21:57:06.000Z (almost 4 years ago)
- Last Synced: 2025-04-13T13:49:11.087Z (about 1 year ago)
- Topics: machine-learning, object-detection, python, swift, swiftui, tutorial
- Language: Swift
- Homepage:
- Size: 215 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# How to Create an Machine Learning Model from scratch and use it in an iOS app
This is a tutorial on how to create your own Machine Learning model from scratch and how to use it in your iOS app.
## ML Model Type
This tutorial will be a YOLO (You Only Look Once) type of machine learning model as speed is a huge requirement for mobile devices. YOLO is one of the **single stage detectors** that runs the classifier once on the input image and do all of the work in a single pass.
## Tools and Tech Stacks
### Machine Learning Tools
- **[IBM Cloud Annotation](https://cloud.annotations.ai/)** - for labeling our dataset
- **Jupyter Notebook** - run our Python codes as well as creating, training, and saving our machine learning model
- **Libraries** - TuriCreate, Pandas
### iOS Development Tools
- **Xcode** - best IDE for iOS development
- **Libraries** - CoreML, UIKit
## Initial Setup for ML
**Note:** Only follow these instructions once. For updating or reopening, refer to the instructions under *How to Update Machine Learning Model*
1. With this repo downloaded, open Terminal and change directory to the project's directory
2. In Terminal, enter `$ cd ML`
3. If needed, install Python's [virtualenv](https://docs.python.org/3/tutorial/venv.html) to have an isolated Python environment.
`$ pip install virtualenv`
- *For a cheat sheet for virtualenv, click [here](https://zetcode.com/python/venv/)*
4. In Terminal, enter `$ python3 -m venv ML_Model_Env` to create a Python virtual environment on the ML_Model_Env
5. In Terminal, enter `$ cd ML_Model_Env` to go inside that directory
6. In Terminal, enter `$ source bin/activate` to activate Python environment. It should look like below
7. Install these libraries and its dependencies by running:
- `(ML_Model_Env) ➜ ML_Model_Env $ pip3 install turicreate`
- `(ML_Model_Env) ➜ ML_Model_Env $ pip3 install jupyter`
8. In Terminal, enter `(ML_Model_Env) ➜ ML_Model_Env $ python3 -m notebook` to launch Jupyter Notebook in your browser and then open **Model Creator.ipnyb**
9. Once you are done, enter in Terminal `(ML_Model_Env) ➜ ML_Model_Env $ deactivate` to clean state and remove all installed packages
## How to Update Machine Learning Model
1. With this repo downloaded, open Terminal and change directory to the project's directory
2. In Terminal, enter `$ cd ML/ML_Model_Env` to go to ML_Model_Env directory
3. In Terminal, enter `$ source bin/activate` to activate Python environment. It should look like below
4. In Terminal, enter `(ML_Model_Env) ➜ ML_Model_Env $ jupyter notebook` to launch Jupyter Notebook in your browser and then open **Model Creator.ipnyb**
## External Links
- [IBM Cloud Annotations Introduction](https://cloud.annotations.ai/workshops/object-detection/index.html)
- [IBM Cloud Annotations Documentation](https://cloud.annotations.ai/docs)
## For questions or opportunities, contact me at:
- [LinkedIn](https://linkedin.com/in/samuelfolledo)
- Email: samuelfolled@gmail.com
- [MakeSchool portfolio](https://www.makeschool.com/portfolio/samuelfolledo) - Expected gradutation date August 2021