0.1.0 release

.github/workflows/release.yaml

@@ -17,8 +17,16 @@ jobs:
       uses: actions/setup-python@v2
       with:
         python-version: 3.9
+    - name: Install apt dependencies
+      run: |
+        sudo apt-add-repository ppa:ubuntugis/ubuntugis-unstable
+        sudo apt-get update
+        sudo apt-get install gdal-bin libgdal-dev
     - name: Install pip dependencies
-      run: pip install .[tests]
+      run: |
+        pip install gdal tqdm  # TODO: these deps shouldn't be needed
+        pip install .[datasets,tests,train]
+        pip install -r docs/requirements.txt
     - name: Run notebook checks
       run: pytest --nbmake docs/tutorials
   integration:
@@ -32,6 +40,6 @@ jobs:
       with:
         python-version: 3.9
     - name: Install pip dependencies
-      run: pip install .[tests]
+      run: pip install .[datasets,tests,train]
     - name: Run integration checks
       run: pytest -m slow

README.md

@@ -23,7 +23,7 @@ Tests:
 The recommended way to install TorchGeo is with [pip](https://pip.pypa.io/):
 
 ```console
-$ pip install git+https://github.com/microsoft/torchgeo.git
+$ pip install torchgeo
 ```
 
 For [conda](https://docs.conda.io/) and [spack](https://spack.io/) installation instructions, see the [documentation](https://torchgeo.readthedocs.io/en/latest/user/installation.html).

conf/task_defaults/bigearthnet.yaml

@@ -9,8 +9,8 @@ experiment:
     in_channels: 14
     num_classes: 19
   datamodule:
-    num_classes: 19
-    batch_size: 128
-    num_workers: 6
+    root_dir: "tests/data/bigearthnet"
     bands: "all"
-    num_classes: 19
+    num_classes: ${experiment.module.num_classes}
+    batch_size: 128
+    num_workers: 0

conf/task_defaults/byol.yaml

@@ -9,11 +9,12 @@ experiment:
     learning_rate: 1e-3
     learning_rate_schedule_patience: 6
   datamodule:
-    batch_size: 64
-    num_workers: 6
+    root_dir: "tests/data/chesapeake/cvpr"
     train_splits:
-      - "de-train"
+      - "de-test"
     val_splits:
-      - "de-val"
+      - "de-test"
     test_splits:
       - "de-test"
+    batch_size: 64
+    num_workers: 0

conf/task_defaults/chesapeake_cvpr.yaml

@@ -12,9 +12,15 @@ experiment:
     num_classes: 7
     num_filters: 256
   datamodule:
-    train_state: "de"
+    root_dir: "tests/data/chesapeake/cvpr"
+    train_splits:
+    - "de-test"
+    val_splits:
+    - "de-test"
+    test_splits:
+    - "de-test"
     patches_per_tile: 200
     patch_size: 256
     batch_size: 64
-    num_workers: 4
-    num_classes: ${experiment.module.num_classes}
+    num_workers: 0
+    class_set: ${experiment.module.num_classes}

conf/task_defaults/cowc_counting.yaml

@@ -5,5 +5,6 @@ experiment:
     learning_rate: 1e-3
     learning_rate_schedule_patience: 2
   datamodule:
+    root_dir: "tests/data/cowc_counting"
     batch_size: 32
-    num_workers: 4
+    num_workers: 0

conf/task_defaults/cyclone.yaml

@@ -5,5 +5,6 @@ experiment:
     learning_rate: 1e-3
     learning_rate_schedule_patience: 2
   datamodule:
+    root_dir: "tests/data/cyclone"
     batch_size: 32
-    num_workers: 4
+    num_workers: 0

conf/task_defaults/landcoverai.yaml

@@ -12,5 +12,6 @@ experiment:
     num_classes: 6
     num_filters: 256
   datamodule:
+    root_dir: "tests/data/landcoverai"
     batch_size: 32
-    num_workers: 4
+    num_workers: 0

conf/task_defaults/naipchesapeake.yaml

@@ -12,5 +12,7 @@ experiment:
     num_classes: 13
     num_filters: 64
   datamodule:
+    naip_root_dir: "tests/data/naip"
+    chesapeake_root_dir: "tests/data/chesapeake/BAYWIDE"
     batch_size: 32
-    num_workers: 4
+    num_workers: 0

conf/task_defaults/resisc45.yaml

@@ -9,9 +9,6 @@ experiment:
     in_channels: 3
     num_classes: 45
   datamodule:
+    root_dir: "tests/data/resisc45"
     batch_size: 128
-    num_workers: 6
-    weights: ${experiment.module.weights}
-    unsupervised_mode: false
-    val_split_pct: 0.2
-    test_split_pct: 0.2
+    num_workers: 0

conf/task_defaults/sen12ms.yaml

@@ -11,5 +11,6 @@ experiment:
     in_channels: 15
     num_classes: 11
   datamodule:
+    root_dir: "tests/data/sen12ms"
     batch_size: 32
-    num_workers: 4
+    num_workers: 0

conf/task_defaults/so2sat.yaml

@@ -9,6 +9,7 @@ experiment:
     in_channels: 3
     num_classes: 17
   datamodule:
+    root_dir: "tests/data/so2sat"
     batch_size: 128
-    num_workers: 6
+    num_workers: 0
     bands: "rgb"

conf/task_defaults/ucmerced.yaml

@@ -9,8 +9,6 @@ experiment:
     in_channels: 3
     num_classes: 21
   datamodule:
+    root_dir: "tests/data/ucmerced"
     batch_size: 128
-    num_workers: 6
-    unsupervised_mode: false
-    val_split_pct: 0.1
-    test_split_pct: 0.1
+    num_workers: 0

docs/tutorials/benchmarking.ipynb

@@ -37,7 +37,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install git+https://github.com/microsoft/torchgeo.git"
+    "%pip install torchgeo"
    ]
   },
   {

docs/tutorials/getting_started.ipynb

@@ -43,7 +43,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install git+https://github.com/microsoft/torchgeo.git"
+    "%pip install torchgeo"
    ]
   },
   {

docs/tutorials/indices.ipynb

@@ -23,7 +23,6 @@
       "mimetype": "text/x-python",
       "name": "python",
       "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
       "version": "3.8.11"
     }
   },
@@ -86,7 +85,7 @@
         "id": "wOwsb8KT_uXR"
       },
       "source": [
-        "%pip install git+https://github.com/microsoft/torchgeo.git"
+        "%pip install torchgeo"
       ],
       "execution_count": null,
       "outputs": []
@@ -117,7 +116,6 @@
         "import rasterio\n",
         "import rasterio.features\n",
         "import shapely\n",
-        "import tifffile\n",
         "import torch\n",
         "import torch.nn as nn\n",
         "import torchvision.transforms as T\n",

docs/tutorials/trainers.ipynb

@@ -43,7 +43,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install git+https://github.com/microsoft/torchgeo.git"
+    "%pip install torchgeo"
    ]
   },
   {
@@ -226,7 +226,6 @@
    ],
    "source": [
     "trainer = pl.Trainer(\n",
-    "    gpus=1,\n",
     "    callbacks=[checkpoint_callback, early_stopping_callback],\n",
     "    logger=[csv_logger],\n",
     "    default_root_dir=experiment_dir,\n",

docs/tutorials/transforms.ipynb

@@ -23,7 +23,6 @@
       "mimetype": "text/x-python",
       "name": "python",
       "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
       "version": "3.8.11"
     },
     "accelerator": "GPU"
@@ -84,7 +83,7 @@
         "id": "wOwsb8KT_uXR"
       },
       "source": [
-        "%pip install git+https://github.com/microsoft/torchgeo.git"
+        "%pip install torchgeo"
       ],
       "execution_count": null,
       "outputs": []
@@ -538,7 +537,7 @@
         "outputId": "fa0443da-8b4d-47f7-e713-93e1e4976e87"
       },
       "source": [
-        "!nvidia-smi"
+        "%nvidia-smi"
       ],
       "execution_count": 8,
       "outputs": [
@@ -724,4 +723,4 @@
       "outputs": []
     }
   ]
-}
+}

docs/user/installation.rst

@@ -1,17 +1,16 @@
 Installation
 ============
 
-TorchGeo is simple and easy to install. We support installation using the `pip <https://pip.pypa.io/>`_, `conda <https://docs.conda.io/>`_, and `spack <https://spack.io/>`_ package managers, although you can also install from source if you want to.
+TorchGeo is simple and easy to install. We support installation using the `pip <https://pip.pypa.io/>`_, `conda <https://docs.conda.io/>`_, and `spack <https://spack.io/>`_ package managers.
 
 pip
 ---
 
-..
-   Since TorchGeo is written in pure-Python, the easiest way to install it is using pip:
+Since TorchGeo is written in pure-Python, the easiest way to install it is using pip:
 
-   .. code-block:: console
+.. code-block:: console
 
-      $ pip install torchgeo
+   $ pip install torchgeo
 
 
 If you want to install a development version, you can use a VCS project URL:
@@ -32,16 +31,10 @@ or a local git checkout:
 
 By default, only required dependencies are installed. TorchGeo has a number of optional dependencies for specific datasets or development. These can be installed with a comma-separated list:
 
-..
-   .. code-block:: console
-
-      $ pip install torchgeo[datasets]
-      $ pip install torchgeo[style,tests]
-
 .. code-block:: console
 
-   $ pip install .[datasets]
-   $ pip install .[style,tests]
+   $ pip install torchgeo[datasets]
+   $ pip install torchgeo[style,tests]
 
 
 See the ``setup.cfg`` for a complete list of options. See the `pip documentation <https://pip.pypa.io/>`_ for more details.
@@ -57,12 +50,11 @@ If you need to install non-Python dependencies like PyTorch, it's better to use
    $ conda config --set channel_priority strict
 
 
-..
-   Now, you can install the latest stable release using:
+Now, you can install the latest stable release using:
 
-   .. code-block:: console
+.. code-block:: console
 
-      $ conda install torchgeo
+   $ conda install torchgeo
 
 
 Conda does not directly support installing development versions, but you can use conda to install our dependencies, then use pip to install TorchGeo itself.
@@ -110,15 +102,3 @@ Optional dependencies can be installed by enabling build variants:
 Run ``spack info py-torchgeo`` for a complete list of variants.
 
 See the `spack documentation <https://spack.readthedocs.io/>`_ for more details.
-
-source
-------
-
-TorchGeo can also be installed from source using the ``setup.py`` file and setuptools.
-
-.. code-block:: console
-
-   $ git clone https://github.com/microsoft/torchgeo.git
-   $ cd torchgeo
-   $ python setup.py build
-   $ python setup.py install

setup.cfg

@@ -9,7 +9,7 @@ long_description = file: README.md
 long_description_content_type = text/markdown
 url = https://github.com/microsoft/torchgeo
 classifiers =
-    Development Status :: 1 - Planning
+    Development Status :: 3 - Alpha
     Intended Audience :: Science/Research
     Programming Language :: Python :: 3
     Programming Language :: Python :: 3.6
@@ -20,7 +20,7 @@ classifiers =
     Operating System :: OS Independent
     Topic :: Scientific/Engineering :: Artificial Intelligence
     Topic :: Scientific/Engineering :: GIS
-keywords = pytorch, deep learning, machine learning
+keywords = pytorch, deep learning, machine learning, remote sensing, satellite imagery, geospatial
 
 [options]
 setup_requires =

tests/test_train.py

@@ -134,20 +134,34 @@ def test_config_file(tmp_path: Path) -> None:
     subprocess.run(args, check=True)
 
 
-@pytest.mark.parametrize("task", ["cowc_counting", "cyclone", "sen12ms", "landcoverai"])
+@pytest.mark.parametrize(
+    "task",
+    [
+        "bigearthnet",
+        "byol",
+        "chesapeake_cvpr",
+        "cowc_counting",
+        "cyclone",
+        "landcoverai",
+        "naipchesapeake",
+        "resisc45",
+        "sen12ms",
+        "so2sat",
+        "ucmerced",
+    ],
+)
 def test_tasks(task: str, tmp_path: Path) -> None:
     output_dir = tmp_path / "output"
-    data_dir = os.path.join("tests", "data", task)
     log_dir = tmp_path / "logs"
     args = [
         sys.executable,
         "train.py",
         "experiment.name=test",
         "program.output_dir=" + str(output_dir),
-        "program.data_dir=" + data_dir,
         "program.log_dir=" + str(log_dir),
         "trainer.fast_dev_run=1",
         "experiment.task=" + task,
         "program.overwrite=True",
+        "config_file=" + os.path.join("conf", "task_defaults", task + ".yaml"),
     ]
     subprocess.run(args, check=True)