| 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 | |
| ```python | |
| 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() | |