https://github.com/drkostas/insta-likes-predict

First attempt on predicting the likes a photo will get on Instagram.
https://github.com/drkostas/insta-likes-predict

cnn instagram keras-tensorflow python scraper

Last synced: about 2 months ago
JSON representation

First attempt on predicting the likes a photo will get on Instagram.

• Host: GitHub
• URL: https://github.com/drkostas/insta-likes-predict
• Owner: drkostas
• License: gpl-3.0
• Created: 2018-11-23T20:37:54.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2023-03-25T01:29:47.000Z (almost 2 years ago)
• Last Synced: 2024-10-12T08:32:37.092Z (2 months ago)
• Topics: cnn, instagram, keras-tensorflow, python, scraper
• Language: Python
• Homepage:
• Size: 45.9 KB
• Stars: 66
• Watchers: 7
• Forks: 5
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Instagram Predict: First attempt

First attempt on predicting the likes a photo will get on Instagram.

Given a list of Instagram users, it downloads their latest photos with their corresponding likes and the number of their followers. Then, it creates a CNN model with **Keras** on **Tensorflow** that predicts the number of likes an image will get.

## Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

### Prerequisites

Python 3.x

### Installing

Installing the requirements

```

pip install -r requirements.txt

```

## Running

1. In the *usernames.txt* write the usernames of the Instagram users you want to scrape (One per line)

1. Run `python3 scraper.py`

1. The data are now saved under */data*

1. Run `python3 Analyze/analyzer.py` to download the images under *data/download* and a create a CNN model that predicts the number of likes based on the image and the number of followers.

1. The model is saved under */models*

1. Place the images whose likes you want to predict under *Analyze/to_predict*

1. Go to *predictor.py* and add the number of followers of each image's user (line *12*)

1. Run `python3 predictor.py`

## License

This project is licensed under the GNU General Public License v3.0 License