{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "22GigzghEU1t"
   },
   "source": [
    "# **GeoMAPCLIP Demo:** Worldwide Map Image Geo-localization 🌎📍"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "Over the past two decades, anthropology and archaeology have shifted from paper-based data collection to digital workflows, leveraging innovations like tablet computing, web GIS, remote sensing, LiDAR, and open-access repositories.\n",
    "However, traditional analog data in archaeological reports, field notes, and sketch maps remain underutilized due to the challenges of digitization and integration.\n",
    "These legacy datasets contain valuable historical and spatial information. However, extracting geospatial details—such as site locations described textually or in hand-drawn maps—is labor-intensive and limits scalability.\n",
    "\n",
    "This project aims to develop a vision system capable of interpreting map images and extracting bounding box coordinates to describe map content.\n",
    "By fine-tuning models such as CLIP and applying image retrieval techniques, the system will learn to recognize legends, scales, symbols, and coordinate grids within geospatial maps, enabling automated extraction of structured spatial information.\n",
    "This advancement will significantly enhance the geospatial reasoning capabilities of large language models, supporting researchers in efficiently querying and leveraging legacy geospatial datasets.\n",
    "\n",
    "Initial development will focus on fine-tuning GeoCLIP (Contrastive Language-Image Pretraining) for map-specific tasks. The vision system will produce a list of coordinates corresponding to visual elements in map figures."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## For more information about GeoCLIP, please check out their [paper](https://arxiv.org/abs/2309.16020v2) and [GitHub repository](https://github.com/VicenteVivan/geo-clip)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notebook Comparison: GeoCLIP vs. GeoMapCLIP\n",
    "\n",
    "This notebook evaluates how coordinate inference results differ between GeoCLIP and GeoMapCLIP:\n",
    "\n",
    "1. GeoCLIP was pre-trained on natural images, such as those from Twitter.\n",
    "\n",
    "2. GeoMapCLIP was fine-tuned on map tiles using GeoCLIP as a base.\n",
    "\n",
    "3. By comparing their predictions, we assess how map-specific fine-tuning improves coordinate inference for geospatial imagery."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "erKH1uiNHoC1",
    "outputId": "cda92c52-f983-4802-f2f4-4da0095baef9"
   },
   "outputs": [],
   "source": [
    "import sys, os\n",
    "import torch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "euBTZdAtEtMU"
   },
   "source": [
    "## Installation 📦"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "UR4_OFerE1JP"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: geoclip in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (1.2.0)\n",
      "Requirement already satisfied: torch in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from geoclip) (2.5.1)\n",
      "Requirement already satisfied: torchvision in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from geoclip) (0.20.1)\n",
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      "Requirement already satisfied: transformers in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from geoclip) (4.49.0)\n",
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      "Requirement already satisfied: packaging>=20.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from transformers->geoclip) (24.2)\n",
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      "Requirement already satisfied: MarkupSafe>=2.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from jinja2->torch->geoclip) (2.1.1)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->transformers->geoclip) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->transformers->geoclip) (3.4)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->transformers->geoclip) (2.0.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->transformers->geoclip) (2025.1.31)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install geoclip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: geomapclip in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (0.0.1)\n",
      "Collecting geomapclip\n",
      "  Downloading geomapclip-0.0.2-py3-none-any.whl.metadata (5.2 kB)\n",
      "Requirement already satisfied: torch in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from geomapclip) (2.5.1)\n",
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      "Requirement already satisfied: packaging>=20.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from transformers->geomapclip) (24.2)\n",
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      "Requirement already satisfied: tqdm>=4.27 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from transformers->geomapclip) (4.67.1)\n",
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      "Requirement already satisfied: idna<4,>=2.5 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->transformers->geomapclip) (3.4)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->transformers->geomapclip) (2.0.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->transformers->geomapclip) (2025.1.31)\n",
      "Downloading geomapclip-0.0.2-py3-none-any.whl (42.9 MB)\n",
      "\u001b[2K   \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.9/42.9 MB\u001b[0m \u001b[31m23.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0mm eta \u001b[36m0:00:01\u001b[0m0:01\u001b[0m:01\u001b[0m\n",
      "\u001b[?25hInstalling collected packages: geomapclip\n",
      "  Attempting uninstall: geomapclip\n",
      "    Found existing installation: geomapclip 0.0.1\n",
      "    Uninstalling geomapclip-0.0.1:\n",
      "      Successfully uninstalled geomapclip-0.0.1\n",
      "Successfully installed geomapclip-0.0.2\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install -U geomapclip"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nJXZE1NcE8WM"
   },
   "source": [
    "## Importing Libraries and Model Initialization 🛠️"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## import libraries and GeoMapCLIP model Initialization "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===========================\n",
      "GeoMapCLIP has been loaded! 🎉\n",
      "===========================\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geomapclip/model/location_encoder.py:57: 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",
      "  self.load_state_dict(torch.load(f\"{file_dir}/weights/location_encoder_weights.pth\"))\n",
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geomapclip/model/GeoMapCLIP.py:38: 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",
      "  self.image_encoder.mlp.load_state_dict(torch.load(f\"{self.weights_folder}/image_encoder_mlp_weights.pth\"))\n",
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geomapclip/model/GeoMapCLIP.py:39: 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",
      "  self.location_encoder.load_state_dict(torch.load(f\"{self.weights_folder}/location_encoder_weights.pth\"))\n",
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geomapclip/model/GeoMapCLIP.py:40: 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",
      "  self.logit_scale = nn.Parameter(torch.load(f\"{self.weights_folder}/logit_scale_weights.pth\"))\n"
     ]
    }
   ],
   "source": [
    "from geomapclip import GeoMapCLIP\n",
    "\n",
    "gmc_device = \"cpu\"\n",
    "\n",
    "gmc_model = GeoMapCLIP().to(gmc_device)\n",
    "print(\"===========================\")\n",
    "print(\"GeoMapCLIP has been loaded! 🎉\")\n",
    "print(\"===========================\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "gsE9h_3Ticp9",
    "outputId": "498ce15c-72ed-4d7e-9249-7d2e01447cc7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===========================\n",
      "GeoCLIP has been loaded! 🎉\n",
      "===========================\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geoclip/model/location_encoder.py:57: 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",
      "  self.load_state_dict(torch.load(f\"{file_dir}/weights/location_encoder_weights.pth\"))\n",
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geoclip/model/GeoCLIP.py:37: 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",
      "  self.image_encoder.mlp.load_state_dict(torch.load(f\"{self.weights_folder}/image_encoder_mlp_weights.pth\"))\n",
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geoclip/model/GeoCLIP.py:38: 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",
      "  self.location_encoder.load_state_dict(torch.load(f\"{self.weights_folder}/location_encoder_weights.pth\"))\n",
      "/Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages/geoclip/model/GeoCLIP.py:39: 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",
      "  self.logit_scale = nn.Parameter(torch.load(f\"{self.weights_folder}/logit_scale_weights.pth\"))\n"
     ]
    }
   ],
   "source": [
    "from geoclip import GeoCLIP\n",
    "\n",
    "gc_model = GeoCLIP().to(\"cpu\")\n",
    "print(\"===========================\")\n",
    "print(\"GeoCLIP has been loaded! 🎉\")\n",
    "print(\"===========================\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: matplotlib in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (3.8.0)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (1.2.0)\n",
      "Requirement already satisfied: cycler>=0.10 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (4.25.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (1.4.4)\n",
      "Requirement already satisfied: numpy<2,>=1.21 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (1.26.2)\n",
      "Requirement already satisfied: packaging>=20.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (24.2)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (10.0.1)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (3.0.9)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from matplotlib) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: folium in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (0.19.5)\n",
      "Requirement already satisfied: branca>=0.6.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from folium) (0.8.1)\n",
      "Requirement already satisfied: jinja2>=2.9 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from folium) (3.1.2)\n",
      "Requirement already satisfied: numpy in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from folium) (1.26.2)\n",
      "Requirement already satisfied: requests in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from folium) (2.31.0)\n",
      "Requirement already satisfied: xyzservices in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from folium) (2025.1.0)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from jinja2>=2.9->folium) (2.1.1)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->folium) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->folium) (3.4)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->folium) (2.0.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/junghawoo/anaconda3/envs/tensorflow_m3/lib/python3.11/site-packages (from requests->folium) (2025.1.31)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# if the kernel does not have them, install these packages\n",
    "%pip install matplotlib\n",
    "%pip install folium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "qYW_iE8PE7uG"
   },
   "outputs": [],
   "source": [
    "# Image Upload & Display\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Heatmap\n",
    "import folium\n",
    "from folium.plugins import HeatMap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Cjb12z4HFEx5"
   },
   "source": [
    "## Uploading an Image 🌃"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## If you want to upload your own image, please upload one to the file explorer, and update the image_path accordingly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 361
    },
    "id": "wGBr-gp6FMvU",
    "outputId": "732e4554-ad16-44b0-e4b9-fbb938d8a546"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#upload your image and put the path here\n",
    "from PIL import Image\n",
    "#image_path = \"./img_uploads/10_301_384.png\"  # Update with the path to your file\n",
    "image_path = \"./img_uploads/10_301_385.png\"  # Update with the path to your file\n",
    "\n",
    "\n",
    "# Open the image file (replace with your local path)\n",
    "image = Image.open(image_path)\n",
    "\n",
    "# Show Image\n",
    "image = Image.open(image_path)\n",
    "plt.figure(figsize=(5, 5))\n",
    "plt.imshow(image)\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Nl5e-uzjFUF3"
   },
   "source": [
    "## Making Predictions 🗺️📍"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GeoMapCLIP predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "eRYZEgCEFm3d",
    "outputId": "9175924d-4322-4e18-97de-40ee49cc6a71"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 5 GPS Predictions by GeoMapCLIP 📍\n",
      "========================\n",
      "Prediction 1: (40.847061, -74.003906) - Probability: 0.096377\n",
      "Prediction 2: (40.847061, -72.597656) - Probability: 0.077176\n",
      "Prediction 3: (40.847061, -73.652344) - Probability: 0.042105\n",
      "Prediction 4: (40.847061, -72.949219) - Probability: 0.041165\n",
      "Prediction 5: (41.112469, -73.300781) - Probability: 0.017862\n"
     ]
    }
   ],
   "source": [
    "#Make predictions for GeoMapClip  TODO: replace model with our GeoMapClip\n",
    "GM_top_pred_gps, GM_top_pred_prob = gmc_model.predict(image_path, top_k=50)\n",
    "\n",
    "# Display the top 5 GPS predictions\n",
    "print(\"Top 5 GPS Predictions by GeoMapCLIP 📍\")\n",
    "print(\"========================\")\n",
    "for i in range(5):\n",
    "    lat, lon = GM_top_pred_gps[i]\n",
    "    print(f\"Prediction {i+1}: ({lat:.6f}, {lon:.6f}) - Probability: {GM_top_pred_prob[i]:.6f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "eRYZEgCEFm3d",
    "outputId": "9175924d-4322-4e18-97de-40ee49cc6a71"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 5 GPS Predictions by GeoCLIP 📍\n",
      "========================\n",
      "Prediction 1: (40.628880, -74.068146) - Probability: 0.024057\n",
      "Prediction 2: (40.646652, -74.064331) - Probability: 0.020160\n",
      "Prediction 3: (40.642452, -74.072311) - Probability: 0.017864\n",
      "Prediction 4: (40.648705, -74.064911) - Probability: 0.017332\n",
      "Prediction 5: (40.619293, -73.832069) - Probability: 0.014185\n"
     ]
    }
   ],
   "source": [
    "# Make predictions\n",
    "top_pred_gps, top_pred_prob = gc_model.predict(image_path, top_k=50)\n",
    "\n",
    "# Display the top 5 GPS predictions\n",
    "print(\"Top 5 GPS Predictions by GeoCLIP 📍\")\n",
    "print(\"========================\")\n",
    "for i in range(5):\n",
    "    lat, lon = top_pred_gps[i]\n",
    "    print(f\"Prediction {i+1}: ({lat:.6f}, {lon:.6f}) - Probability: {top_pred_prob[i]:.6f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_y3qwMv_jXxy"
   },
   "source": [
    "## Visualize Heatmap 🌎 🔍"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 850
    },
    "id": "ZKlgt5xEXw3s",
    "outputId": "ef809c09-e7b0-4ccf-e05c-55cde850ce8e",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-3.7.1.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap-glyphicons.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_e1e3becc079d983b89540064117ce911 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium@main/folium/templates/leaflet_heat.min.js&quot;&gt;&lt;/script&gt;\n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_e1e3becc079d983b89540064117ce911&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_e1e3becc079d983b89540064117ce911 = L.map(\n",
       "                &quot;map_e1e3becc079d983b89540064117ce911&quot;,\n",
       "                {\n",
       "                    center: [40.658192825317386, -73.99867401123046],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    ...{\n",
       "  &quot;zoom&quot;: 2.2,\n",
       "  &quot;zoomControl&quot;: true,\n",
       "  &quot;preferCanvas&quot;: false,\n",
       "}\n",
       "\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_6a36184184b22d56b33b69952627f639 = L.tileLayer(\n",
       "                &quot;https://tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {\n",
       "  &quot;minZoom&quot;: 0,\n",
       "  &quot;maxZoom&quot;: 19,\n",
       "  &quot;maxNativeZoom&quot;: 19,\n",
       "  &quot;noWrap&quot;: false,\n",
       "  &quot;attribution&quot;: &quot;\\u0026copy; \\u003ca href=\\&quot;https://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors&quot;,\n",
       "  &quot;subdomains&quot;: &quot;abc&quot;,\n",
       "  &quot;detectRetina&quot;: false,\n",
       "  &quot;tms&quot;: false,\n",
       "  &quot;opacity&quot;: 1,\n",
       "}\n",
       "\n",
       "            );\n",
       "        \n",
       "    \n",
       "            tile_layer_6a36184184b22d56b33b69952627f639.addTo(map_e1e3becc079d983b89540064117ce911);\n",
       "        \n",
       "    \n",
       "            var heat_map_0264a1d87517566b0c13ea0aef460ed8 = L.heatLayer(\n",
       "                [[40.62887954711914, -74.06814575195312, 0.15064031951482557], [40.64665222167969, -74.0643310546875, 0.12624023704472837], [40.642452239990234, -74.07231140136719, 0.1118587644650268], [40.648704528808594, -74.06491088867188, 0.10853081355313961], [40.619293212890625, -73.83206939697266, 0.08882144238389854], [40.79285430908203, -73.83903503417969, 0.08751806074484605], [40.64809036254883, -73.87178039550781, 0.08636656087389658], [40.65739440917969, -74.05316925048828, 0.08126621667659248], [40.644832611083984, -74.07416534423828, 0.08039767853464488], [40.652774810791016, -74.04682159423828, 0.07835990620840112]],\n",
       "                {\n",
       "  &quot;minOpacity&quot;: 0.5,\n",
       "  &quot;maxZoom&quot;: 18,\n",
       "  &quot;radius&quot;: 25,\n",
       "  &quot;blur&quot;: 15,\n",
       "  &quot;gradient&quot;: {\n",
       "  &quot;0.0&quot;: &quot;#932667&quot;,\n",
       "  &quot;0.2&quot;: &quot;#b5367a&quot;,\n",
       "  &quot;0.4&quot;: &quot;#d3466b&quot;,\n",
       "  &quot;0.6&quot;: &quot;#f1605d&quot;,\n",
       "  &quot;0.8&quot;: &quot;#fd9668&quot;,\n",
       "  &quot;1.0&quot;: &quot;#fcfdbf&quot;,\n",
       "},\n",
       "}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            heat_map_0264a1d87517566b0c13ea0aef460ed8.addTo(map_e1e3becc079d983b89540064117ce911);\n",
       "        \n",
       "    \n",
       "            var marker_0cca07ef0d4410c54419597ca19d3fe7 = L.marker(\n",
       "                [40.62887954711914, -74.06814575195312],\n",
       "                {\n",
       "}\n",
       "            ).addTo(map_e1e3becc079d983b89540064117ce911);\n",
       "        \n",
       "    \n",
       "            var icon_0f92489ddb1e2bcb9a80aba9649952bc = L.AwesomeMarkers.icon(\n",
       "                {\n",
       "  &quot;markerColor&quot;: &quot;orange&quot;,\n",
       "  &quot;iconColor&quot;: &quot;white&quot;,\n",
       "  &quot;icon&quot;: &quot;star&quot;,\n",
       "  &quot;prefix&quot;: &quot;glyphicon&quot;,\n",
       "  &quot;extraClasses&quot;: &quot;fa-rotate-0&quot;,\n",
       "}\n",
       "            );\n",
       "        \n",
       "    \n",
       "        var popup_764529da3bfe2edd0bb975baa362e674 = L.popup({\n",
       "  &quot;maxWidth&quot;: &quot;100%&quot;,\n",
       "});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_ff0103a3c47d1f3b76428b29b086694e = $(`&lt;div id=&quot;html_ff0103a3c47d1f3b76428b29b086694e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Top Prediction: [40.62887954711914, -74.06814575195312] with probability 0.1506&lt;/div&gt;`)[0];\n",
       "                popup_764529da3bfe2edd0bb975baa362e674.setContent(html_ff0103a3c47d1f3b76428b29b086694e);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_0cca07ef0d4410c54419597ca19d3fe7.bindPopup(popup_764529da3bfe2edd0bb975baa362e674)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "                marker_0cca07ef0d4410c54419597ca19d3fe7.setIcon(icon_0f92489ddb1e2bcb9a80aba9649952bc);\n",
       "            \n",
       "    \n",
       "            var heat_map_b10c0c356820d8c7f06f83df559f013a = L.heatLayer(\n",
       "                [[40.84706115722656, -74.00390625, 0.27686381533371474], [40.84706115722656, -72.59765625, 0.22170640568684266], [40.84706115722656, -73.65234375, 0.12095515018516419], [40.84706115722656, -72.94921875, 0.1182553559500852], [41.11246871948242, -73.30078125, 0.05131145282607714], [40.84706115722656, -73.30078125, 0.049965756144715746], [40.31304168701172, -74.00390625, 0.04943467118732769], [51.50874328613281, 0.52734375, 0.03823182697942137], [39.23225402832031, -74.70703125, 0.03795485503362359], [32.990234375, -79.62890625, 0.035320710673027673]],\n",
       "                {\n",
       "  &quot;minOpacity&quot;: 0.5,\n",
       "  &quot;maxZoom&quot;: 18,\n",
       "  &quot;radius&quot;: 25,\n",
       "  &quot;blur&quot;: 15,\n",
       "  &quot;gradient&quot;: {\n",
       "  &quot;0.0&quot;: &quot;#003366&quot;,\n",
       "  &quot;0.2&quot;: &quot;#336699&quot;,\n",
       "  &quot;0.4&quot;: &quot;#66ccff&quot;,\n",
       "  &quot;0.6&quot;: &quot;#99ccff&quot;,\n",
       "  &quot;0.8&quot;: &quot;#cce6ff&quot;,\n",
       "  &quot;1.0&quot;: &quot;#e6f7ff&quot;,\n",
       "},\n",
       "}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            heat_map_b10c0c356820d8c7f06f83df559f013a.addTo(map_e1e3becc079d983b89540064117ce911);\n",
       "        \n",
       "    \n",
       "            var marker_b66d426915413d1d69395b2fa065a6fd = L.marker(\n",
       "                [40.84706115722656, -74.00390625],\n",
       "                {\n",
       "}\n",
       "            ).addTo(map_e1e3becc079d983b89540064117ce911);\n",
       "        \n",
       "    \n",
       "            var icon_21ca9917403128649624096e3d29bd0c = L.AwesomeMarkers.icon(\n",
       "                {\n",
       "  &quot;markerColor&quot;: &quot;blue&quot;,\n",
       "  &quot;iconColor&quot;: &quot;white&quot;,\n",
       "  &quot;icon&quot;: &quot;star&quot;,\n",
       "  &quot;prefix&quot;: &quot;glyphicon&quot;,\n",
       "  &quot;extraClasses&quot;: &quot;fa-rotate-0&quot;,\n",
       "}\n",
       "            );\n",
       "        \n",
       "    \n",
       "        var popup_c9dfd512252dc7c787a89740fbe1541c = L.popup({\n",
       "  &quot;maxWidth&quot;: &quot;100%&quot;,\n",
       "});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_a250a85cfdcc74d96651af98de034d8b = $(`&lt;div id=&quot;html_a250a85cfdcc74d96651af98de034d8b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Top Prediction: [40.84706115722656, -74.00390625] with probability 0.2769&lt;/div&gt;`)[0];\n",
       "                popup_c9dfd512252dc7c787a89740fbe1541c.setContent(html_a250a85cfdcc74d96651af98de034d8b);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_b66d426915413d1d69395b2fa065a6fd.bindPopup(popup_c9dfd512252dc7c787a89740fbe1541c)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "                marker_b66d426915413d1d69395b2fa065a6fd.setIcon(icon_21ca9917403128649624096e3d29bd0c);\n",
       "            \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x32165ad50>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set top coordinates to plot the heatmap (<= top_k)\n",
    "top_n_coordinates = 10\n",
    "\n",
    "gps_coordinates = top_pred_gps.tolist()[:top_n_coordinates]\n",
    "probabilities = top_pred_prob.tolist()[:top_n_coordinates]\n",
    "\n",
    "total_prob = sum(probabilities)\n",
    "normalized_probs = [prob / total_prob for prob in probabilities]\n",
    "\n",
    "# Combine coordinates with normalized probabilities\n",
    "weighted_coordinates = [(lat, lon, weight) for (lat, lon), weight in zip(gps_coordinates, normalized_probs)]\n",
    "\n",
    "# Calculate the average location to center the map\n",
    "avg_lat = sum(lat for lat, lon, weight in weighted_coordinates) / len(weighted_coordinates)\n",
    "avg_lon = sum(lon for lat, lon, weight in weighted_coordinates) / len(weighted_coordinates)\n",
    "\n",
    "# Create a map centered around the average coordinates\n",
    "m = folium.Map(location=[avg_lat, avg_lon], zoom_start=2.2)\n",
    "\n",
    "# Define the color gradient\n",
    "magma = {\n",
    "    0.0: '#932667',\n",
    "    0.2: '#b5367a',\n",
    "    0.4: '#d3466b',\n",
    "    0.6: '#f1605d',\n",
    "    0.8: '#fd9668',\n",
    "    1.0: '#fcfdbf'\n",
    "}\n",
    "\n",
    "\n",
    "gradient = {str(k): v for k, v in magma.items()}\n",
    "\n",
    "HeatMap(weighted_coordinates, gradient=gradient).add_to(m)\n",
    "\n",
    "# Mark top coordinate\n",
    "top_coordinate = gps_coordinates[0]\n",
    "top_probability = normalized_probs[0]\n",
    "\n",
    "folium.Marker(\n",
    "    location=top_coordinate,\n",
    "    popup=f\"Top Prediction: {top_coordinate} with probability {top_probability:.4f}\",\n",
    "    icon=folium.Icon(color='orange', icon='star')\n",
    ").add_to(m)\n",
    "\n",
    "\n",
    "############################################ Draw result for GeoMapClip################################\n",
    "GM_gps_coordinates = GM_top_pred_gps.tolist()[:top_n_coordinates]\n",
    "probabilities = GM_top_pred_prob.tolist()[:top_n_coordinates]\n",
    "\n",
    "total_prob = sum(probabilities)\n",
    "normalized_probs = [prob / total_prob for prob in probabilities]\n",
    "\n",
    "# Combine coordinates with normalized probabilities\n",
    "weighted_coordinates = [(lat, lon, weight) for (lat, lon), weight in zip(GM_gps_coordinates, normalized_probs)]\n",
    "\n",
    "# Define the bluish color gradient\n",
    "bluish = {\n",
    "    0.0: '#003366',  # Dark blue\n",
    "    0.2: '#336699',  # Light blue\n",
    "    0.4: '#66ccff',  # Lighter blue\n",
    "    0.6: '#99ccff',  # Very light blue\n",
    "    0.8: '#cce6ff',  # Soft blue\n",
    "    1.0: '#e6f7ff'   # Very pale blue\n",
    "}\n",
    "gradient = {str(k): v for k, v in bluish.items()}\n",
    "\n",
    "HeatMap(weighted_coordinates, gradient=gradient).add_to(m)\n",
    "\n",
    "# Mark top coordinate\n",
    "top_coordinate = GM_gps_coordinates[0]\n",
    "top_probability = normalized_probs[0]\n",
    "\n",
    "folium.Marker(\n",
    "    location=top_coordinate,\n",
    "    popup=f\"Top Prediction: {top_coordinate} with probability {top_probability:.4f}\",\n",
    "    icon=folium.Icon(color='blue', icon='star')\n",
    ").add_to(m)\n",
    "\n",
    "# Display the map\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_pS0gtZBFvpe"
   },
   "source": [
    "## Want to learn more? 📚\n",
    "\n",
    "Check out our [GitHub repository](https://github.com/junghawoo/geomap-clip) for more details!\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
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   "gpuType": "T4",
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   "language": "python",
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