Blurred_landmarks Open-source Image Classification Model - Free Deployment for High-accuracy Landmark Recognition

Blurred Landmarks

Developed by petrznel

An image classification model fine-tuned based on ResNet-50, achieving 96.45% accuracy in landmark recognition tasks

Downloads 35

Release Time : 7/29/2023

Model Overview

This model is a fine-tuned version of microsoft/resnet-50 on an image folder dataset, specifically designed for landmark image classification tasks.

High Accuracy

Achieves 96.45% classification accuracy on the validation set

Based on ResNet-50

Fine-tuned using the mature ResNet-50 architecture

Efficient Training

Utilizes linear learning rate scheduling and Adam optimizer, completing training within 20 epochs

Image Classification

Landmark Recognition

Travel Applications

Automatic Landmark Recognition

Identify famous landmark buildings in photos

96.45% recognition accuracy

Content Management

Automatic Image Classification

Automatically classify and organize images containing landmarks

Property	Details
Model Type	Fine - tuned version of [microsoft/resnet - 50](https://huggingface.co/microsoft/resnet - 50)
Training Data	imagefolder dataset
Metrics	Accuracy: 0.9645, Loss: 0.1152

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6588	1.0	357	0.6460	0.7707
0.3752	2.0	714	0.2969	0.8933
0.3275	3.0	1071	0.1912	0.9319
0.2183	4.0	1429	0.1794	0.9305
0.2133	5.0	1786	0.1638	0.9414
0.1984	6.0	2143	0.1322	0.9484
0.1409	7.0	2500	0.1304	0.9529
0.1864	8.0	2858	0.1212	0.9572
0.1778	9.0	3215	0.1216	0.9540
0.1734	10.0	3572	0.1129	0.9593
0.1349	11.0	3929	0.1127	0.9614
0.1057	12.0	4287	0.1177	0.9582
0.1434	13.0	4644	0.1153	0.9603
0.0832	14.0	5001	0.1264	0.9593
0.0963	15.0	5358	0.1146	0.9607
0.0642	16.0	5716	0.1135	0.9635
0.0763	17.0	6073	0.1210	0.9614
0.0432	18.0	6430	0.1162	0.9645
0.0618	19.0	6787	0.1269	0.9600
0.049	19.99	7140	0.1152	0.9645

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