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+ "grid_column": null,
+ "grid_gap": null,
+ "grid_row": null,
+ "grid_template_areas": null,
+ "grid_template_columns": null,
+ "grid_template_rows": null,
+ "height": null,
+ "justify_content": null,
+ "justify_items": null,
+ "left": null,
+ "margin": null,
+ "max_height": null,
+ "max_width": null,
+ "min_height": null,
+ "min_width": null,
+ "object_fit": null,
+ "object_position": null,
+ "order": null,
+ "overflow": null,
+ "overflow_x": null,
+ "overflow_y": null,
+ "padding": null,
+ "right": null,
+ "top": null,
+ "visibility": null,
+ "width": null
+ }
+ },
+ "97ff4b48bbae4fee976690efadb08f42": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_name": "DescriptionStyleModel",
+ "model_module_version": "1.5.0",
+ "state": {
+ "_model_module": "@jupyter-widgets/controls",
+ "_model_module_version": "1.5.0",
+ "_model_name": "DescriptionStyleModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/base",
+ "_view_module_version": "1.2.0",
+ "_view_name": "StyleView",
+ "description_width": ""
+ }
+ }
+ }
+ }
+ },
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Imports and Hugging Face Login"
+ ],
+ "metadata": {
+ "id": "JmycREmYnMXc"
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "s3FAMHfAkCC5",
+ "outputId": "d10e358c-3171-4b64-f396-99c516a2061f"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (0.26.5)\n",
+ "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub) (3.16.1)\n",
+ "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub) (2024.10.0)\n",
+ "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub) (24.2)\n",
+ "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub) (6.0.2)\n",
+ "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub) (2.32.3)\n",
+ "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub) (4.66.6)\n",
+ "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub) (4.12.2)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub) (3.4.0)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub) (3.10)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub) (2.2.3)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub) (2024.8.30)\n",
+ "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+ "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\u001b[0m\u001b[31m\n",
+ "\u001b[0m"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install huggingface-hub\n",
+ "!pip install datasets > delete.txt"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "import torch\n",
+ "import pickle\n",
+ "from huggingface_hub import hf_hub_download\n",
+ "from datasets import load_dataset, Image\n",
+ "import torch\n",
+ "from torch import nn, optim\n",
+ "from torch.utils.data import DataLoader, Dataset\n",
+ "import numpy as np\n",
+ "from geopy.distance import geodesic\n",
+ "import matplotlib.pyplot as plt\n",
+ "from torchvision import models\n",
+ "from timm import create_model"
+ ],
+ "metadata": {
+ "id": "ljUC6nnqkPw5"
+ },
+ "execution_count": 8,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
+ "print(device)"
+ ],
+ "metadata": {
+ "id": "Qw8TzYuYkRJl",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "dd88e51a-490e-4963-88b0-157c9096e18b"
+ },
+ "execution_count": 3,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "cuda\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!huggingface-cli login\n",
+ "# use appropiate token"
+ ],
+ "metadata": {
+ "id": "rl8Lo-LPkSZq",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "85a4dc60-7f08-4f32-b1df-c1abeeaf8d97"
+ },
+ "execution_count": 4,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ " _| _| _| _| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _|_|_|_| _|_| _|_|_| _|_|_|_|\n",
+ " _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|\n",
+ " _|_|_|_| _| _| _| _|_| _| _|_| _| _| _| _| _| _|_| _|_|_| _|_|_|_| _| _|_|_|\n",
+ " _| _| _| _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|\n",
+ " _| _| _|_| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _| _| _| _|_|_| _|_|_|_|\n",
+ "\n",
+ " To log in, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n",
+ "Enter your token (input will not be visible): \n",
+ "Add token as git credential? (Y/n) y\n",
+ "Token is valid (permission: fineGrained).\n",
+ "The token `CIS 5190 Project 3` has been saved to /root/.cache/huggingface/stored_tokens\n",
+ "\u001b[1m\u001b[31mCannot authenticate through git-credential as no helper is defined on your machine.\n",
+ "You might have to re-authenticate when pushing to the Hugging Face Hub.\n",
+ "Run the following command in your terminal in case you want to set the 'store' credential helper as default.\n",
+ "\n",
+ "git config --global credential.helper store\n",
+ "\n",
+ "Read https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage for more details.\u001b[0m\n",
+ "Token has not been saved to git credential helper.\n",
+ "Your token has been saved to /root/.cache/huggingface/token\n",
+ "Login successful.\n",
+ "The current active token is: `CIS 5190 Project 3`\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Models"
+ ],
+ "metadata": {
+ "id": "VZH-IAQOnfVK"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "class SwinGPSModel(nn.Module):\n",
+ " def __init__(self, pretrained=True):\n",
+ " super(SwinGPSModel, self).__init__()\n",
+ " # Load the pretrained Swin Transformer\n",
+ " self.backbone = create_model('swin_tiny_patch4_window7_224', pretrained=pretrained)\n",
+ "\n",
+ " # Get the number of features from the backbone\n",
+ " num_features = self.backbone.num_features\n",
+ " self.backbone.head = nn.Identity()\n",
+ "\n",
+ " # Define the regression head\n",
+ " self.regression_head = nn.Sequential(\n",
+ " nn.AdaptiveAvgPool2d((1, 1)),\n",
+ " nn.Flatten(),\n",
+ " nn.Linear(num_features, 256),\n",
+ " nn.ReLU(),\n",
+ " nn.Linear(256, 2)\n",
+ " )\n",
+ "\n",
+ " def forward(self, x):\n",
+ " # Forward pass through the backbone\n",
+ " features = self.backbone(x)\n",
+ " features = features.permute(0, 3, 1, 2)\n",
+ " return self.regression_head(features)"
+ ],
+ "metadata": {
+ "id": "jRLpNGGTkWE_"
+ },
+ "execution_count": 9,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Loading Test Dataset"
+ ],
+ "metadata": {
+ "id": "f1UUjumnnjKg"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from torch.utils.data import Dataset\n",
+ "class GPSImageDataset(Dataset):\n",
+ " def __init__(self, hf_dataset, transform, lat_mean=None, lat_std=None, lon_mean=None, lon_std=None):\n",
+ " self.hf_dataset = hf_dataset\n",
+ " self.transform = transform\n",
+ "\n",
+ " # Normalize the latitude and longitude\n",
+ " self.latitudes = np.array(hf_dataset['Latitude'])\n",
+ " self.longitudes = np.array(hf_dataset['Longitude'])\n",
+ " self.latitude_mean = lat_mean if lat_mean is not None else self.latitudes.mean()\n",
+ " self.latitude_std = lat_std if lat_std is not None else self.latitudes.std()\n",
+ " self.longitude_mean = lon_mean if lon_mean is not None else self.longitudes.mean()\n",
+ " self.longitude_std = lon_std if lon_std is not None else self.longitudes.std()\n",
+ "\n",
+ " self.normalized_latitudes = (self.latitudes - self.latitude_mean) / self.latitude_std\n",
+ " self.normalized_longitudes = (self.longitudes - self.longitude_mean) / self.longitude_std\n",
+ "\n",
+ " def __len__(self):\n",
+ " return len(self.hf_dataset)\n",
+ "\n",
+ " def __getitem__(self, idx):\n",
+ " image = self.hf_dataset[idx]['image']\n",
+ " latitude = self.normalized_latitudes[idx]\n",
+ " longitude = self.normalized_longitudes[idx]\n",
+ "\n",
+ " if self.transform:\n",
+ " image = self.transform(image)\n",
+ "\n",
+ " return image, torch.tensor([latitude, longitude], dtype=torch.float)"
+ ],
+ "metadata": {
+ "id": "qOJy6pFekcKm"
+ },
+ "execution_count": 10,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from torchvision import transforms, models\n",
+ "transform = transforms.Compose([\n",
+ " transforms.RandomResizedCrop(224),\n",
+ " transforms.RandomHorizontalFlip(),\n",
+ " transforms.ColorJitter(brightness=0.2, contrast=0.2, saturation=0.2, hue=0.1),\n",
+ " transforms.ToTensor(),\n",
+ " transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
+ "])\n",
+ "\n",
+ "inference_transform = transforms.Compose([\n",
+ " transforms.Resize((224, 224)),\n",
+ " transforms.ToTensor(),\n",
+ " transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
+ "])"
+ ],
+ "metadata": {
+ "id": "hQS6QcZHkb5K"
+ },
+ "execution_count": 11,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "dataset_test = load_dataset(\"gydou/released_img\")"
+ ],
+ "metadata": {
+ "id": "y-fJviwPkhGn",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 237,
+ "referenced_widgets": [
+ "b5514ebeac2043ed80851509501f5bc1",
+ "d5916e3238cb40c08176156ef260ae9f",
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+ "11afc23eb5bc4f21b3fdde2be2d71047",
+ "8fd986d43ff245d28903dea981d5539c",
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+ "c143b711299a4991b1de2e92b70dec1a",
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+ "68e86e9414034d498b468f7b5356fd83",
+ "314ff6c39e7f40d1ae81152f345cb13f"
+ ]
+ },
+ "outputId": "c1b4a304-e368-409b-ee9c-7145281105df"
+ },
+ "execution_count": 12,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
+ "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+ "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+ "You will be able to reuse this secret in all of your notebooks.\n",
+ "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+ " warnings.warn(\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "README.md: 0%| | 0.00/360 [00:00<?, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "b5514ebeac2043ed80851509501f5bc1"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "train-00000-of-00001.parquet: 0%| | 0.00/307M [00:00<?, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "f761608901f243b69484791f7eadebc3"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Generating train split: 0%| | 0/100 [00:00<?, ? examples/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "8a58df07452448cea77377b46b3808bc"
+ }
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "lat_mean = 39.9517411499467\n",
+ "lat_std = 0.0006914493505038013\n",
+ "lon_mean = -75.19143213125122\n",
+ "lon_std = 0.0006539239061573955\n",
+ "\n",
+ "test_dataset = GPSImageDataset(\n",
+ " hf_dataset=dataset_test['train'],\n",
+ " transform=inference_transform,\n",
+ " lat_mean=lat_mean,\n",
+ " lat_std=lat_std,\n",
+ " lon_mean=lon_mean,\n",
+ " lon_std=lon_std\n",
+ ")\n",
+ "\n",
+ "test_dataloader = DataLoader(\n",
+ " test_dataset,\n",
+ " batch_size=32,\n",
+ " shuffle=False,\n",
+ " num_workers=4\n",
+ ")"
+ ],
+ "metadata": {
+ "id": "4uUIOOIkkpQ8",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "58c1bc50-5e40-4d57-bec5-f2018f366ed9"
+ },
+ "execution_count": 13,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:617: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
+ " warnings.warn(\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Loading the Model"
+ ],
+ "metadata": {
+ "id": "5dr6mhyDno5p"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "pth_file_path = hf_hub_download(repo_id= \"CIS-5190-CIA/SWIN_Model\", filename=\"best_swin_gps_model.pth\")"
+ ],
+ "metadata": {
+ "id": "c4-DMMjxlh-A",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "355f647049a14da69403c2ec8bd37259",
+ "6d50051473d8403892a0de076bcbf598",
+ "1cd513bd8cba479897d87f420c5b392e",
+ "6483ec93244d41c1bb6e25938d6a0335",
+ "92d7357e289f4d7893755d4e6f9011fa",
+ "3a6e3fb21cb74d9f8fc180c306bb5df4",
+ "87714bc600524b538b09971f217366e3",
+ "06320303c9e14b51beb814c9988524af",
+ "4c8825bdc5e94b3cbaf949ba8c59dca6",
+ "06b6c047edf441b4b4f179cd828374b3",
+ "97ff4b48bbae4fee976690efadb08f42"
+ ]
+ },
+ "outputId": "87a7ae37-5df1-4f93-dd49-92e4d6b700ec"
+ },
+ "execution_count": 14,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "best_swin_gps_model.pth: 0%| | 0.00/111M [00:00<?, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "355f647049a14da69403c2ec8bd37259"
+ }
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Instantiate the model\n",
+ "model = SwinGPSModel(pretrained=False)\n",
+ "\n",
+ "# Load the weights from the downloaded .pth file\n",
+ "model.load_state_dict(torch.load(pth_file_path, map_location=torch.device(\"cpu\")))\n",
+ "\n",
+ "# Move the model to the appropriate device\n",
+ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
+ "model = model.to(device)\n",
+ "\n",
+ "# Set the model to evaluation mode\n",
+ "model.eval()\n",
+ "\n",
+ "print(\"Model loaded successfully!\")"
+ ],
+ "metadata": {
+ "id": "Foo4o2Xllhh4",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "6288586f-dba8-478a-93b2-4df0748c957a"
+ },
+ "execution_count": 15,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "<ipython-input-15-85f55b19993d>:5: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+ " model.load_state_dict(torch.load(pth_file_path, map_location=torch.device(\"cpu\")))\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Model loaded successfully!\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Prediction"
+ ],
+ "metadata": {
+ "id": "Ut26z0oDnHey"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "def evaluate_final_rmse(ensemble_model, data_loader, lat_mean, lon_mean, lat_std, lon_std):\n",
+ " \"\"\"\n",
+ " Evaluate the ensemble model on a given dataset and compute final RMSE in meters.\n",
+ " \"\"\"\n",
+ " ensemble_model.eval()\n",
+ " total_loss = 0.0\n",
+ " total_samples = 0\n",
+ "\n",
+ " with torch.no_grad():\n",
+ " for images, targets in data_loader:\n",
+ " images, targets = images.to(device), targets.to(device)\n",
+ " outputs = ensemble_model(images)\n",
+ " preds_denorm = outputs.cpu().numpy() * np.array([lat_std, lon_std]) + np.array([lat_mean, lon_mean])\n",
+ " actuals_denorm = targets.cpu().numpy() * np.array([lat_std, lon_std]) + np.array([lat_mean, lon_mean])\n",
+ "\n",
+ " for pred, actual in zip(preds_denorm, actuals_denorm):\n",
+ " distance = geodesic((actual[0], actual[1]), (pred[0], pred[1])).meters\n",
+ " total_loss += distance ** 2\n",
+ " total_samples += targets.size(0)\n",
+ "\n",
+ " final_loss = total_loss / total_samples\n",
+ " final_rmse = np.sqrt(final_loss)\n",
+ "\n",
+ " return final_loss, final_rmse"
+ ],
+ "metadata": {
+ "id": "cRrEV4aQltTk"
+ },
+ "execution_count": 16,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "final_test_loss, final_test_rmse = evaluate_final_rmse(\n",
+ " ensemble_model=model,\n",
+ " data_loader=test_dataloader,\n",
+ " lat_mean=lat_mean,\n",
+ " lon_mean=lon_mean,\n",
+ " lat_std=lat_std,\n",
+ " lon_std=lon_std\n",
+ ")\n",
+ "\n",
+ "print(f\"Test Loss (meters^2): {final_test_loss:.2f}\")\n",
+ "print(f\"Test RMSE (meters): {final_test_rmse:.2f}\")"
+ ],
+ "metadata": {
+ "id": "fE9kcYcJl1Yv",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "dd9ee75d-8889-4d4a-e904-0b89e6f1841b"
+ },
+ "execution_count": 17,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Test Loss (meters^2): 6863.43\n",
+ "Test RMSE (meters): 82.85\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Visualization"
+ ],
+ "metadata": {
+ "id": "R4F9rg9Em-Wg"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "def visualize_predictions(all_preds, all_actuals, lat_mean, lon_mean, lat_std, lon_std):\n",
+ " \"\"\"\n",
+ " Visualizes actual and predicted GPS coordinates on a scatter plot,\n",
+ " including error lines connecting each prediction to its corresponding actual point.\n",
+ " \"\"\"\n",
+ "\n",
+ " all_preds_denorm = all_preds * np.array([lat_std, lon_std]) + np.array([lat_mean, lon_mean])\n",
+ " all_actuals_denorm = all_actuals * np.array([lat_std, lon_std]) + np.array([lat_mean, lon_mean])\n",
+ "\n",
+ " plt.figure(figsize=(10, 5))\n",
+ "\n",
+ " plt.scatter(all_actuals_denorm[:, 1], all_actuals_denorm[:, 0], label='Actual', color='blue', alpha=0.6)\n",
+ " plt.scatter(all_preds_denorm[:, 1], all_preds_denorm[:, 0], label='Predicted', color='red', alpha=0.6)\n",
+ " for i in range(len(all_actuals_denorm)):\n",
+ " plt.plot(\n",
+ " [all_actuals_denorm[i, 1], all_preds_denorm[i, 1]],\n",
+ " [all_actuals_denorm[i, 0], all_preds_denorm[i, 0]],\n",
+ " color='gray', linewidth=0.5\n",
+ " )\n",
+ "\n",
+ " plt.legend()\n",
+ " plt.xlabel('Longitude')\n",
+ " plt.ylabel('Latitude')\n",
+ " plt.title('Actual vs. Predicted GPS Coordinates with Error Lines')\n",
+ " plt.grid(True)\n",
+ " plt.show()"
+ ],
+ "metadata": {
+ "id": "ouC_5PjdnAkk"
+ },
+ "execution_count": 18,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "all_preds = []\n",
+ "all_actuals = []\n",
+ "\n",
+ "with torch.no_grad():\n",
+ " for images, targets in test_dataloader:\n",
+ " images = images.to(\"cuda\")\n",
+ " targets = targets.to(\"cuda\")\n",
+ "\n",
+ " preds = model(images)\n",
+ "\n",
+ " all_preds.append(preds.cpu().numpy())\n",
+ " all_actuals.append(targets.cpu().numpy())\n",
+ "\n",
+ "all_preds = np.concatenate(all_preds, axis=0)\n",
+ "all_actuals = np.concatenate(all_actuals, axis=0)\n",
+ "\n",
+ "visualize_predictions(\n",
+ " all_preds=all_preds,\n",
+ " all_actuals=all_actuals,\n",
+ " lat_mean=lat_mean,\n",
+ " lon_mean=lon_mean,\n",
+ " lat_std=lat_std,\n",
+ " lon_std=lon_std\n",
+ ")"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 487
+ },
+ "id": "rmS-K3ZinElW",
+ "outputId": "8ca1723d-8b2e-4336-97b3-0d1ed84100bc"
+ },
+ "execution_count": 19,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1000x500 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ }
+ ]
+}
\ No newline at end of file