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raj999 commited on Jun 2, 2024

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33b9a81

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predictJB (2).ipynb +640 -0
test_json.py +54 -0

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	@@ -0,0 +1,640 @@

+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HAyy6GyLGXcB"
+      },
+      "source": [
+        "# Performing landscape level predictions"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "bZPXVnSG8UZ6"
+      },
+      "source": [
+        "Mount drive, install package\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [],
+      "metadata": {
+        "id": "vR4HxtPIneU3"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import sys\n",
+        "print(\"Python version\")\n",
+        "print(sys.version)"
+      ],
+      "metadata": {
+        "id": "xoNfSu7hWryz",
+        "outputId": "368b44fc-279a-450e-ce95-9b15b28f2b55",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Python version\n",
+            "3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "CBxnNgct8T84",
+        "outputId": "2c910ebf-3efe-4776-d2bd-02f0c23083a0"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting git+https://github.com/PatBall1/detectree2.git\n",
+            "  Cloning https://github.com/PatBall1/detectree2.git to /tmp/pip-req-build-vztr3c29\n",
+            "  Running command git clone --filter=blob:none --quiet https://github.com/PatBall1/detectree2.git /tmp/pip-req-build-vztr3c29\n",
+            "  Resolved https://github.com/PatBall1/detectree2.git to commit 2f29886bafcb63743a7f3ab596c5c3796ca4a243\n",
+            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Collecting detectron2@ git+https://github.com/facebookresearch/detectron2.git (from detectree2==1.0.8)\n",
+            "  Cloning https://github.com/facebookresearch/detectron2.git to /tmp/pip-install-3kcq93pe/detectron2_814ab9c3956248cf876dae13021793d0\n",
+            "  Running command git clone --filter=blob:none --quiet https://github.com/facebookresearch/detectron2.git /tmp/pip-install-3kcq93pe/detectron2_814ab9c3956248cf876dae13021793d0\n",
+            "  Resolved https://github.com/facebookresearch/detectron2.git to commit 0df2d73d0013db7de629602c23cc120219b4f2b8\n",
+            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (6.0.1)\n",
+            "Requirement already satisfied: GDAL>=1.11 in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (3.6.4)\n",
+            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (1.25.2)\n",
+            "Requirement already satisfied: rtree in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (1.2.0)\n",
+            "Requirement already satisfied: proj in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (0.2.0)\n",
+            "Requirement already satisfied: geos in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (0.2.3)\n",
+            "Requirement already satisfied: pypng in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (0.20220715.0)\n",
+            "Requirement already satisfied: pygeos in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (0.14)\n",
+            "Requirement already satisfied: shapely in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (2.0.4)\n",
+            "Requirement already satisfied: geopandas in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (0.13.2)\n",
+            "Requirement already satisfied: rasterio==1.3a3 in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (1.3a3)\n",
+            "Requirement already satisfied: fiona in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (1.9.6)\n",
+            "Requirement already satisfied: pycrs in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (1.0.2)\n",
+            "Requirement already satisfied: descartes in /usr/local/lib/python3.10/dist-packages (from detectree2==1.0.8) (1.1.0)\n",
+            "Requirement already satisfied: affine in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (2.4.0)\n",
+            "Requirement already satisfied: attrs in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (23.2.0)\n",
+            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (2024.2.2)\n",
+            "Requirement already satisfied: click>=4.0 in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (8.1.7)\n",
+            "Requirement already satisfied: cligj>=0.5 in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (0.7.2)\n",
+            "Requirement already satisfied: snuggs>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (1.4.7)\n",
+            "Requirement already satisfied: click-plugins in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (1.1.1)\n",
+            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from rasterio==1.3a3->detectree2==1.0.8) (67.7.2)\n",
+            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from descartes->detectree2==1.0.8) (3.7.1)\n",
+            "Requirement already satisfied: Pillow>=7.1 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (9.4.0)\n",
+            "Requirement already satisfied: pycocotools>=2.0.2 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.0.7)\n",
+            "Requirement already satisfied: termcolor>=1.1 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.4.0)\n",
+            "Requirement already satisfied: yacs>=0.1.8 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.1.8)\n",
+            "Requirement already satisfied: tabulate in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.9.0)\n",
+            "Requirement already satisfied: cloudpickle in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.2.1)\n",
+            "Requirement already satisfied: tqdm>4.29.0 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (4.66.4)\n",
+            "Requirement already satisfied: tensorboard in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.15.2)\n",
+            "Requirement already satisfied: fvcore<0.1.6,>=0.1.5 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.1.5.post20221221)\n",
+            "Requirement already satisfied: iopath<0.1.10,>=0.1.7 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.1.9)\n",
+            "Requirement already satisfied: omegaconf<2.4,>=2.1 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.3.0)\n",
+            "Requirement already satisfied: hydra-core>=1.1 in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (1.3.2)\n",
+            "Requirement already satisfied: black in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (24.4.2)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (24.0)\n",
+            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from fiona->detectree2==1.0.8) (1.16.0)\n",
+            "Requirement already satisfied: pandas>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from geopandas->detectree2==1.0.8) (2.0.3)\n",
+            "Requirement already satisfied: pyproj>=3.0.1 in /usr/local/lib/python3.10/dist-packages (from geopandas->detectree2==1.0.8) (3.6.1)\n",
+            "Requirement already satisfied: flask in /usr/local/lib/python3.10/dist-packages (from geos->detectree2==1.0.8) (2.2.5)\n",
+            "Requirement already satisfied: lxml in /usr/local/lib/python3.10/dist-packages (from geos->detectree2==1.0.8) (4.9.4)\n",
+            "Requirement already satisfied: arrow>=0.15.6 in /usr/local/lib/python3.10/dist-packages (from proj->detectree2==1.0.8) (1.3.0)\n",
+            "Requirement already satisfied: python-dateutil>=2.7.0 in /usr/local/lib/python3.10/dist-packages (from arrow>=0.15.6->proj->detectree2==1.0.8) (2.8.2)\n",
+            "Requirement already satisfied: types-python-dateutil>=2.8.10 in /usr/local/lib/python3.10/dist-packages (from arrow>=0.15.6->proj->detectree2==1.0.8) (2.9.0.20240316)\n",
+            "Requirement already satisfied: antlr4-python3-runtime==4.9.* in /usr/local/lib/python3.10/dist-packages (from hydra-core>=1.1->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (4.9.3)\n",
+            "Requirement already satisfied: portalocker in /usr/local/lib/python3.10/dist-packages (from iopath<0.1.10,>=0.1.7->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.0->geopandas->detectree2==1.0.8) (2023.4)\n",
+            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.0->geopandas->detectree2==1.0.8) (2024.1)\n",
+            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->descartes->detectree2==1.0.8) (1.2.1)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->descartes->detectree2==1.0.8) (0.12.1)\n",
+            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->descartes->detectree2==1.0.8) (4.51.0)\n",
+            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->descartes->detectree2==1.0.8) (1.4.5)\n",
+            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->descartes->detectree2==1.0.8) (3.1.2)\n",
+            "Requirement already satisfied: mypy-extensions>=0.4.3 in /usr/local/lib/python3.10/dist-packages (from black->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (1.0.0)\n",
+            "Requirement already satisfied: pathspec>=0.9.0 in /usr/local/lib/python3.10/dist-packages (from black->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.12.1)\n",
+            "Requirement already satisfied: platformdirs>=2 in /usr/local/lib/python3.10/dist-packages (from black->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (4.2.2)\n",
+            "Requirement already satisfied: tomli>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from black->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.0.1)\n",
+            "Requirement already satisfied: typing-extensions>=4.0.1 in /usr/local/lib/python3.10/dist-packages (from black->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (4.11.0)\n",
+            "Requirement already satisfied: Werkzeug>=2.2.2 in /usr/local/lib/python3.10/dist-packages (from flask->geos->detectree2==1.0.8) (3.0.3)\n",
+            "Requirement already satisfied: Jinja2>=3.0 in /usr/local/lib/python3.10/dist-packages (from flask->geos->detectree2==1.0.8) (3.1.4)\n",
+            "Requirement already satisfied: itsdangerous>=2.0 in /usr/local/lib/python3.10/dist-packages (from flask->geos->detectree2==1.0.8) (2.2.0)\n",
+            "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (1.4.0)\n",
+            "Requirement already satisfied: grpcio>=1.48.2 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (1.64.0)\n",
+            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.27.0)\n",
+            "Requirement already satisfied: google-auth-oauthlib<2,>=0.5 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (1.2.0)\n",
+            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (3.6)\n",
+            "Requirement already satisfied: protobuf!=4.24.0,>=3.19.6 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (3.20.3)\n",
+            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.31.0)\n",
+            "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.7.2)\n",
+            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (5.3.3)\n",
+            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.4.0)\n",
+            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (4.9)\n",
+            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<2,>=0.5->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (1.3.1)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from Jinja2>=3.0->flask->geos->detectree2==1.0.8) (2.1.5)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (3.7)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (2.0.7)\n",
+            "Requirement already satisfied: pyasn1<0.7.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (0.6.0)\n",
+            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard->detectron2@ git+https://github.com/facebookresearch/detectron2.git->detectree2==1.0.8) (3.2.2)\n"
+          ]
+        }
+      ],
+      "source": [
+        "from google.colab import drive\n",
+        "# drive.mount('/content/drive')\n",
+        "!pip install git+https://github.com/PatBall1/detectree2.git"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "cZfxTuOxnXKQ"
+      },
+      "source": [
+        "## Tiling\n",
+        "Tile up the entire orthomosaic to make predictions"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "hvKTOryJQR0v"
+      },
+      "source": [
+        "## Create full site predictions\n",
+        "\n",
+        "### Access pre-trained model"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Download pre-trained model"
+      ],
+      "metadata": {
+        "id": "4CnWRxJB9eA3"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "There might be a cleaner way to do it with `pkg_resources` but I haven't figured this out yet"
+      ],
+      "metadata": {
+        "id": "cpHMH39aELgb"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "JeT66YPmreRv"
+      },
+      "source": [
+        "Combine predictions into full output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import cv2\n",
+        "from PIL import Image\n",
+        "import os\n",
+        "import numpy as np\n",
+        "import urllib.request\n",
+        "import glob\n",
+        "\n",
+        "# intake library and plugin\n",
+        "# import intake\n",
+        "# from intake_zenodo_fetcher import download_zenodo_files_for_entry\n",
+        "\n",
+        "# geospatial libraries\n",
+        "import geopandas as gpd\n",
+        "\n",
+        "from rasterio.transform import from_origin\n",
+        "import rasterio.features\n",
+        "\n",
+        "import fiona\n",
+        "\n",
+        "from shapely.geometry import shape, mapping, box\n",
+        "from shapely.geometry.multipolygon import MultiPolygon\n",
+        "\n",
+        "# machine learning libraries\n",
+        "from detectron2 import model_zoo\n",
+        "from detectron2.engine import DefaultPredictor\n",
+        "from detectron2.utils.visualizer import Visualizer, ColorMode\n",
+        "from detectron2.config import get_cfg\n",
+        "from detectron2.engine import DefaultTrainer\n",
+        "\n",
+        "# visualisation\n",
+        "import holoviews as hv\n",
+        "from IPython.display import display\n",
+        "# import geoviews.tile_sources as gts\n",
+        "\n",
+        "# import hvplot.pandas\n",
+        "# import hvplot.xarray\n",
+        "\n",
+        "# hv.extension('bokeh', width=100)"
+      ],
+      "metadata": {
+        "id": "lftCpCayrPR5"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "%matplotlib inline"
+      ],
+      "metadata": {
+        "id": "fpHuk_s3uAXz"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "filepath = '/content/DJI_20240504221329_0168_D.JPG'\n",
+        "im = cv2.imread(filepath)\n",
+        "display(Image.fromarray(im))"
+      ],
+      "metadata": {
+        "id": "g0YQ1U2trbI5",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 297
+        },
+        "outputId": "c766edda-6deb-4eae-e5bf-8c55104316f1"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "error",
+          "ename": "AttributeError",
+          "evalue": "'NoneType' object has no attribute '__array_interface__'",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-11-0d695c62c78d>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mfilepath\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'/content/DJI_20240504221329_0168_D.JPG'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mdisplay\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mImage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfromarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/PIL/Image.py\u001b[0m in \u001b[0;36mfromarray\u001b[0;34m(obj, mode)\u001b[0m\n\u001b[1;32m   3067\u001b[0m     \u001b[0;34m.\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mversionadded\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m1.1\u001b[0m\u001b[0;36m.6\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3068\u001b[0m     \"\"\"\n\u001b[0;32m-> 3069\u001b[0;31m     \u001b[0marr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__array_interface__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3070\u001b[0m     \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"shape\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3071\u001b[0m     \u001b[0mndim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute '__array_interface__'"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import matplotlib.pyplot as plt\n"
+      ],
+      "metadata": {
+        "id": "D8YtfLmluG3e"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plt.imshow(im)"
+      ],
+      "metadata": {
+        "id": "fqHOtxxvuDnl"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Define the project main folder\n",
+        "data_folder = './forest-modelling-detectree'\n",
+        "\n",
+        "# Set the folder structure\n",
+        "config = {\n",
+        "    'in_geotiff': os.path.join(data_folder, 'input','tiff'),\n",
+        "    'in_png': os.path.join(data_folder, 'input','png'),\n",
+        "    'model': os.path.join(data_folder, 'model'),\n",
+        "    'out_geotiff': os.path.join(data_folder, 'output','raster'),\n",
+        "    'out_shapefile': os.path.join(data_folder, 'output','vector'),\n",
+        "}\n",
+        "\n",
+        "# List comprehension for the folder structure code\n",
+        "[os.makedirs(val) for key, val in config.items() if not os.path.exists(val)]"
+      ],
+      "metadata": {
+        "id": "_cPnLA53sNWi"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# define the URL to retrieve the model\n",
+        "fn = 'model_final.pth'\n",
+        "url = f'https://zenodo.org/record/5515408/files/{fn}?download=1'\n",
+        "\n",
+        "urllib.request.urlretrieve(url, config['model'] + '/' + fn)"
+      ],
+      "metadata": {
+        "id": "SazYGXJWr6rW"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "Yu6ixAMoObsv"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cfg = get_cfg()\n",
+        "\n",
+        "# if you want to make predictions using a CPU, run the following line. If using GPU, hash it out.\n",
+        "cfg.MODEL.DEVICE='cuda'\n",
+        "\n",
+        "# model and hyperparameter selection\n",
+        "cfg.merge_from_file(model_zoo.get_config_file(\"COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml\"))\n",
+        "cfg.DATALOADER.NUM_WORKERS = 2\n",
+        "cfg.SOLVER.IMS_PER_BATCH = 2\n",
+        "cfg.MODEL.ROI_HEADS.NUM_CLASSES = 1\n",
+        "\n",
+        "### path to the saved pre-trained model weights\n",
+        "cfg.MODEL.WEIGHTS = config['model'] + '/model_final.pth'\n",
+        "\n",
+        "# set confidence threshold at which we predict\n",
+        "cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.15\n",
+        "\n",
+        "#### Settings for predictions using detectron config\n",
+        "\n",
+        "predictor = DefaultPredictor(cfg)"
+      ],
+      "metadata": {
+        "id": "ibJGEKdmsZmq"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "outputs = predictor(im)\n",
+        "v = Visualizer(im[:, :, ::-1], scale=1.5, instance_mode=ColorMode.IMAGE_BW)   # remove the colors of unsegmented pixels\n",
+        "v = v.draw_instance_predictions(outputs[\"instances\"].to(\"cpu\"))\n",
+        "image = cv2.cvtColor(v.get_image()[:, :, :], cv2.COLOR_BGR2RGB)\n",
+        "display(Image.fromarray(image))"
+      ],
+      "metadata": {
+        "id": "zH-Okks_sVBF"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "plt.imshow(image)"
+      ],
+      "metadata": {
+        "id": "ZH3jAypEsqdG"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "mask_array = outputs['instances'].pred_masks.cpu().numpy()\n",
+        "\n",
+        "# get confidence scores too\n",
+        "mask_array_scores = outputs['instances'].scores.cpu().numpy()"
+      ],
+      "metadata": {
+        "id": "ewUypuTCSYSL"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "num_instances = mask_array.shape[0]\n",
+        "mask_array_instance = []\n",
+        "output = np.zeros_like(mask_array)\n",
+        "\n",
+        "mask_array_instance.append(mask_array)\n",
+        "output = np.where(mask_array_instance[0] == True, 255, output)\n",
+        "fresh_output = output.astype(np.float)\n",
+        "x_scaling = 140/fresh_output.shape[1]\n",
+        "y_scaling = 140/fresh_output.shape[2]\n",
+        "# this is an affine transform. This needs to be altered significantly.\n",
+        "transform = from_origin(int(filepath[-17:-11])-20, int(filepath[-10:-4])+120, y_scaling, x_scaling)"
+      ],
+      "metadata": {
+        "id": "i_25LDd9ShHj"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "mask_array = outputs['instances'].pred_masks.numpy()\n",
+        "\n",
+        "# get confidence scores too\n",
+        "mask_array_scores = outputs['instances'].scores.numpy()\n",
+        "\n",
+        "num_instances = mask_array.shape[0]\n",
+        "mask_array_instance = []\n",
+        "output = np.zeros_like(mask_array)\n",
+        "\n",
+        "mask_array_instance.append(mask_array)\n",
+        "output = np.where(mask_array_instance[0] == True, 255, output)\n",
+        "fresh_output = output.astype(np.float)\n",
+        "x_scaling = 140/fresh_output.shape[1]\n",
+        "y_scaling = 140/fresh_output.shape[2]\n",
+        "# this is an affine transform. This needs to be altered significantly.\n",
+        "transform = from_origin(int(filepath[-17:-11])-20, int(filepath[-10:-4])+120, y_scaling, x_scaling)\n",
+        "\n",
+        "output_raster = config['out_geotiff'] + '/' + 'predicted_rasters_' + filepath[-17:-4]+ '.tif'\n",
+        "\n",
+        "new_dataset = rasterio.open(output_raster, 'w', driver='GTiff',\n",
+        "                                height = fresh_output.shape[1], width = fresh_output.shape[2], count = fresh_output.shape[0],\n",
+        "                                dtype=str(fresh_output.dtype),\n",
+        "                                crs='+proj=utm +zone=50 +datum=WGS84 +units=m +no_defs',\n",
+        "                                transform=transform)\n",
+        "\n",
+        "new_dataset.write(fresh_output)\n",
+        "new_dataset.close()"
+      ],
+      "metadata": {
+        "id": "juM3wDRLvZ4m"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(outputs)"
+      ],
+      "metadata": {
+        "id": "u0hdjykMSNX8"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "mask_array = outputs['instances'].pred_masks.cpu.numpy()\n",
+        "\n",
+        "# get confidence scores too\n",
+        "mask_array_scores = outputs['instances'].scores.cpu.numpy()\n",
+        "\n",
+        "num_instances = mask_array.shape[0]\n",
+        "mask_array_instance = []\n",
+        "output = np.zeros_like(mask_array)\n",
+        "\n",
+        "mask_array_instance.append(mask_array)\n",
+        "output = np.where(mask_array_instance[0] == True, 255, output)\n",
+        "fresh_output = output.astype(np.float)"
+      ],
+      "metadata": {
+        "id": "Jg0r8IgQD_W8"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# # Read input band with Rasterio\n",
+        "\n",
+        "# with rasterio.open(output_raster) as src:\n",
+        "#     shp_schema = {'geometry': 'MultiPolygon','properties': {'pixelvalue': 'int', 'score': 'float'}}\n",
+        "\n",
+        "#     crs = src.crs\n",
+        "#     for i in range(src.count):\n",
+        "#         src_band = src.read(i+1)\n",
+        "#         src_band = np.float32(src_band)\n",
+        "#         conf = mask_array_scores[i]\n",
+        "#         # Keep track of unique pixel values in the input band\n",
+        "#         unique_values = np.unique(src_band)\n",
+        "#         # Polygonize with Rasterio. `shapes()` returns an iterable\n",
+        "#         # of (geom, value) as tuples\n",
+        "#         shapes = list(rasterio.features.shapes(src_band, transform=src.transform))\n",
+        "\n",
+        "#         if i == 0:\n",
+        "#             with fiona.open(config['out_shapefile'] + '/predicted_polygons_' + filepath[-17:-4] + '_' + str(0) + '.shp', 'w', 'ESRI Shapefile',\n",
+        "#                             shp_schema) as shp:\n",
+        "#                 polygons = [shape(geom) for geom, value in shapes if value == 255.0]\n",
+        "#                 multipolygon = MultiPolygon(polygons)\n",
+        "#                         # simplify not needed here\n",
+        "#                         #multipolygon = multipolygon_a.simplify(0.1, preserve_topology=False)\n",
+        "#                 shp.write({\n",
+        "#                           'geometry': mapping(multipolygon),\n",
+        "#                           'properties': {'pixelvalue': int(unique_values[1]), 'score': float(conf)}\n",
+        "#                            })\n",
+        "#         else:\n",
+        "#             with fiona.open(config['out_shapefile'] + '/predicted_polygons_' + filepath[-17:-4] + '_' + str(0)+'.shp', 'a', 'ESRI Shapefile',\n",
+        "#                             shp_schema) as shp:\n",
+        "#                 polygons = [shape(geom) for geom, value in shapes if value == 255.0]\n",
+        "#                 multipolygon = MultiPolygon(polygons)\n",
+        "#                         # simplify not needed here\n",
+        "#                         #multipolygon = multipolygon_a.simplify(0.1, preserve_topology=False)\n",
+        "#                 shp.write({\n",
+        "#                           'geometry': mapping(multipolygon),\n",
+        "#                           'properties': {'pixelvalue': int(unique_values[1]), 'score': float(conf)}\n",
+        "#                            })"
+      ],
+      "metadata": {
+        "id": "-Enr0Hg7vbtr"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# load and plot polygons\n",
+        "in_shp = glob.glob(config['out_shapefile'] + '/*.shp')\n",
+        "\n",
+        "poly_df = gpd.read_file(in_shp[0])\n",
+        "\n",
+        "plot_vector = poly_df.hvplot(hover_cols=['score'], legend=False).opts(fill_color=None,line_color=None,alpha=0.5, width=800, height=600)\n",
+        "\n",
+        "plot_vector"
+      ],
+      "metadata": {
+        "id": "DWve5Kc8vI5s"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "KW3j29mJGjO5"
+      },
+      "source": [
+        "Remove invalid geometries before cleaning. Might be a way to fix them rather than remove all together but I think the ones with invalid geometries tend to be bad crowns anyway."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zF0qy7vpGmem"
+      },
+      "source": [
+        "Clean overlapping crowns. For significant overlaps, the most confident crown is selected. IoU can be varied based on how strict you want the filtering to be."
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "provenance": [],
+      "gpuType": "T4"
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

test_json.py ADDED Viewed

	@@ -0,0 +1,54 @@

+import json
+import pandas
+with open(r'E:\Backup_K20pro\Download\treesat_benchmark\coco-panoptic\export_coco-panoptic_r_drone-panoramic_drone-panoramic.v01.json') as f:
+    data = json.load(f)
+# Extracting general information
+info = data['info']
+categories = data['categories']
+images = data['images']
+annotations = data['annotations']
+print("Dataset description:", info['description'])
+print("Dataset version:", info['version'])
+print("\nCategories:")
+for category in categories:
+    print(f"ID: {category['id']}, Name: {category['name']}, Color: {category['color']}")
+print("\nImages:")
+for image in images:
+    print(f"ID: {image['id']}, File Name: {image['file_name']}, Width: {image['width']}, Height: {image['height']}")
+print("\nAnnotations:")
+for annotation in annotations:
+    print(f"Image ID: {annotation['image_id']}, File Name: {annotation['file_name']}")
+    for segment_info in annotation['segments_info']:
+        print(f"  Segment ID: {segment_info['id']}, Category ID: {segment_info['category_id']}, BBox: {segment_info['bbox']}, Area: {segment_info['area']}")
+def get_images_by_category(category_name, data):
+    category_id = None
+    for category in data['categories']:
+        if category['name'] == category_name:
+            category_id = category['id']
+            break
+    if category_id is None:
+        print(f"Category '{category_name}' not found.")
+        return []
+    images_with_category = []
+    for annotation in data['annotations']:
+        for segment_info in annotation['segments_info']:
+            if segment_info['category_id'] == category_id:
+                images_with_category.append(annotation['image_id'])
+                break
+    return images_with_category
+# Example usage
+category_name = "Attalea Maripa"
+print("ATTALIA MARIPAAAAAAA")
+image_ids = get_images_by_category(category_name, data)
+print(image_ids)