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Hotel Image Classifier
H
Hotel Image Classifier
Developed by faisalabidi
A hotel image classification model based on PyTorch and HuggingPics, capable of recognizing different scenes and facilities in hotel environments.
Downloads 43
Release Time : 12/25/2022
Model Overview
This model is specifically designed for classifying images in hotel environments, capable of identifying various scenes such as bathrooms, beaches, fitness centers, dining areas, lobbies, meeting rooms, pools, restaurants, guest rooms, spas, and suites.
Model Features
Multi-scene Classification
Accurately identifies multiple scenes and facilities in hotel environments, covering various images from guest rooms to public areas.
High Accuracy
Achieves an accuracy of 80.21% on test datasets, demonstrating stable and reliable performance.
Easy Integration
Built on the PyTorch framework, making it easy to integrate with other deep learning projects.
Model Capabilities
Image Classification
Scene Recognition
Hotel Facility Recognition
Use Cases
Hotel Management
Automatic Hotel Photo Classification
Used on hotel websites or booking platforms to automatically categorize uploaded photos into the correct categories.
Improves photo management efficiency and reduces manual classification workload.
Customer Experience Analysis
Analyzes photos taken by customers to identify the most popular facilities.
Provides data support for hotel facility improvements.
Travel Platforms
Hotel Search Optimization
Automatically recommends photos of specific types of hotel facilities based on user preferences.
Enhances user experience and conversion rates.
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