README.md

lat_mean=39.951853021309034 lat_std=0.0005336591548786815 lon_mean=-75.19122782343982 lon_std=0.0004335530163099028

license: mit

#ResNet GPS Prediction Model This model predicts GPS coordinates (latitude and longitude) from input images using a custom ResNet-based architecture.

##How to Use

1. Download resnet_gps_model.pth and config.json from this repository.
2. Define the model architecture (as shown in the usage example below).
3. Load the model weights and configuration.

Example Usage

import torch
import json

# Load config
config = json.load(open("config.json", "r"))

# Define and load model
resnet = CustomResNetModel(model_name="microsoft/resnet-18", num_classes=config["num_classes"])
state_dict = torch.load("resnet_gps_model.pth")
resnet.load_state_dict(state_dict)
resnet.eval()