Welcome to our ClosetCoach, a Fashion Wardrobe Assistant project, designed to help you develop your Deep Learning based Computer Vision skills. In this project, we will guide you through the process of building a fashion wardrobe assistant from scratch, using cutting-edge Deep Learning techniques
This Pull Request (PR) aims to merge the 4-data-scraping-for-fashion-data branch into the main branch. The key features and updates introduced by this branch include data scraping and preprocessing tools for fashion data, which will help to enhance the ClosetCoach project. And this issue closes #4
Features
Below is a summary of the major features and updates included in this PR:
Data Scraping Tools: Implemented Scrapy based data scraping spiders to fetch fashion data from Myntra website.
Data Preprocessing: Added preprocessing functions to clean and preprocess the scraped data. These functions handle tasks such as removing special characters and converting text to lowercase. This will ensure that the data is in a suitable format for further analysis and modeling.
Data Storage: Implemented data storage solutions to save the scraped and preprocessed data in a unstructured data format using MongoDB. This will make it easy to access and manipulate the data during the development of the ClosetCoach project.
Error Handling and Logging: Implemented robust error handling and logging mechanisms to ensure that the data scraping process runs smoothly. This will help in detecting and troubleshooting any issues that may arise during the scraping process.
Impact
Merging this PR will significantly enhance the ClosetCoach project by providing a rich dataset of fashion-related information. This data will be instrumental in training and evaluating the machine learning models for various tasks, such as outfit recommendations and trend analysis.
How to Test
To test the changes introduced by this PR, follow these steps:
Description
This Pull Request (PR) aims to merge the 4-data-scraping-for-fashion-data branch into the main branch. The key features and updates introduced by this branch include data scraping and preprocessing tools for fashion data, which will help to enhance the ClosetCoach project. And this issue closes #4
Features
Below is a summary of the major features and updates included in this PR:
Data Scraping Tools: Implemented Scrapy based data scraping spiders to fetch fashion data from Myntra website.
Data Preprocessing: Added preprocessing functions to clean and preprocess the scraped data. These functions handle tasks such as removing special characters and converting text to lowercase. This will ensure that the data is in a suitable format for further analysis and modeling.
Data Storage: Implemented data storage solutions to save the scraped and preprocessed data in a unstructured data format using MongoDB. This will make it easy to access and manipulate the data during the development of the ClosetCoach project.
Error Handling and Logging: Implemented robust error handling and logging mechanisms to ensure that the data scraping process runs smoothly. This will help in detecting and troubleshooting any issues that may arise during the scraping process.
Impact
Merging this PR will significantly enhance the ClosetCoach project by providing a rich dataset of fashion-related information. This data will be instrumental in training and evaluating the machine learning models for various tasks, such as outfit recommendations and trend analysis.
How to Test
To test the changes introduced by this PR, follow these steps: