This project features an Image Extractor that deals with apartment images, extracts them from MongoDB, and compresses them in order to store them in a new directory based on the apartment's condition.
The building blocks of this project were built using the following software:
- Python 3.8.
- Pandas 1.4.0, Numpy 1.22.1 for tabular data manipulation.
- Pillow 8.4.0, Opencv 4.5.5.62 for Image Processing.
- Pymongo 4.2.0 for working with MongoDB.
The database was stored in Mongodb, which has two collections, one for Morizon and one for Otodom. Each document in these collections has the following schema:
_id: string(unique)
address: string
area: string
condition: enumeration of Polish words
description: string
m2price: string
offer_number: string
price: string
rooms: string
url: string
year_of_build: string
images: list of strings
date_scrapped: string (datatime)
The second database is a csv file containing the words used to describe the apartment's condition along with its appropriate standard (1 for good condition, 0 for bad condition).
Create secret.py in the root directory and add MONGODB_CONNECTION_URL variable
pip install -r requirments.txt
python main.py