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)
2. Run python3 scraper.py
3. The data are now saved under /data
4. 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.
5. The model is saved under /models
6. Place the images whose likes you want to predict under Analyze/to_predict
7. Go to predictor.py and add the number of followers of each image's user (line 12)
8. Run python3 predictor.py

License

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