Add instance segmentation and keypoint detection to flash zero

CHANGELOG.md

@@ -48,6 +48,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Added Torch ORT support to Transformer based tasks ([#667](https://github.com/PyTorchLightning/lightning-flash/pull/667))
 
+- Added support for flash zero with the `InstanceSegmentation` and `KeypointDetector` tasks ([#672](https://github.com/PyTorchLightning/lightning-flash/pull/672))
+
 ### Changed
 
 - Changed how pretrained flag works for loading weights for ImageClassifier task ([#560](https://github.com/PyTorchLightning/lightning-flash/pull/560))

docs/source/reference/instance_segmentation.rst

@@ -29,3 +29,22 @@ Here's the full example:
 .. literalinclude:: ../../../flash_examples/instance_segmentation.py
     :language: python
     :lines: 14-
+
+------
+
+**********
+Flash Zero
+**********
+
+The instance segmentation task can be used directly from the command line with zero code using :ref:`flash_zero`.
+You can run the above example with:
+
+.. code-block:: bash
+
+    flash instance_segmentation
+
+To view configuration options and options for running the instance segmentation task with your own data, use:
+
+.. code-block:: bash
+
+    flash instance_segmentation --help

docs/source/reference/keypoint_detection.rst

@@ -29,3 +29,22 @@ Here's the full example:
 .. literalinclude:: ../../../flash_examples/keypoint_detection.py
     :language: python
     :lines: 14-
+
+------
+
+**********
+Flash Zero
+**********
+
+The keypoint detector can be used directly from the command line with zero code using :ref:`flash_zero`.
+You can run the above example with:
+
+.. code-block:: bash
+
+    flash keypoint_detection
+
+To view configuration options and options for running the keypoint detector with your own data, use:
+
+.. code-block:: bash
+
+    flash keypoint_detection --help

flash/__main__.py

@@ -44,6 +44,8 @@ def wrapper(cli_args):
     "flash.graph.classification",
     "flash.image.classification",
     "flash.image.detection",
+    "flash.image.instance_segmentation",
+    "flash.image.keypoint_detection",
     "flash.image.segmentation",
     "flash.image.style_transfer",
     "flash.pointcloud.detection",

flash/core/utilities/imports.py

@@ -96,6 +96,7 @@ def _compare_version(package: str, op, version) -> bool:
 _SENTENCEPIECE_AVAILABLE = _module_available("sentencepiece")
 _DATASETS_AVAILABLE = _module_available("datasets")
 _ICEVISION_AVAILABLE = _module_available("icevision")
+_ICEDATA_AVAILABLE = _module_available("icedata")
 _TORCH_ORT_AVAILABLE = _module_available("torch_ort")
 
 if Version:
@@ -120,6 +121,7 @@ def _compare_version(package: str, op, version) -> bool:
         _PYSTICHE_AVAILABLE,
         _SEGMENTATION_MODELS_AVAILABLE,
         _ICEVISION_AVAILABLE,
+        _ICEDATA_AVAILABLE,
     ]
 )
 _SERVE_AVAILABLE = _FASTAPI_AVAILABLE and _PYDANTIC_AVAILABLE and _CYTOOLZ_AVAILABLE and _UVICORN_AVAILABLE

flash/image/instance_segmentation/cli.py

@@ -0,0 +1,62 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from functools import partial
+from typing import Optional
+
+from flash.core.utilities.flash_cli import FlashCLI
+from flash.core.utilities.imports import _ICEDATA_AVAILABLE, requires_extras
+from flash.image import InstanceSegmentation, InstanceSegmentationData
+
+if _ICEDATA_AVAILABLE:
+    import icedata
+
+__all__ = ["instance_segmentation"]
+
+
+@requires_extras("image")
+def from_pets(
+    val_split: float = 0.1,
+    batch_size: int = 4,
+    num_workers: Optional[int] = None,
+    **preprocess_kwargs,
+) -> InstanceSegmentationData:
+    """Downloads and loads the pets data set from icedata."""
+    data_dir = icedata.pets.load_data()
+
+    return InstanceSegmentationData.from_folders(
+        train_folder=data_dir,
+        val_split=val_split,
+        batch_size=batch_size,
+        num_workers=num_workers,
+        parser=partial(icedata.pets.parser, mask=True),
+        **preprocess_kwargs,
+    )
+
+
+def instance_segmentation():
+    """Segment object instances in images."""
+    cli = FlashCLI(
+        InstanceSegmentation,
+        InstanceSegmentationData,
+        default_datamodule_builder=from_pets,
+        default_arguments={
+            "trainer.max_epochs": 3,
+        },
+    )
+
+    cli.trainer.save_checkpoint("instance_segmentation_model.pt")
+
+
+if __name__ == "__main__":
+    instance_segmentation()

flash/image/keypoint_detection/cli.py

@@ -0,0 +1,61 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from typing import Optional
+
+from flash.core.utilities.flash_cli import FlashCLI
+from flash.core.utilities.imports import _ICEDATA_AVAILABLE, requires_extras
+from flash.image import KeypointDetectionData, KeypointDetector
+
+if _ICEDATA_AVAILABLE:
+    import icedata
+
+__all__ = ["keypoint_detection"]
+
+
+@requires_extras("image")
+def from_biwi(
+    val_split: float = 0.1,
+    batch_size: int = 4,
+    num_workers: Optional[int] = None,
+    **preprocess_kwargs,
+) -> KeypointDetectionData:
+    """Downloads and loads the BIWI data set from icedata."""
+    data_dir = icedata.biwi.load_data()
+
+    return KeypointDetectionData.from_folders(
+        train_folder=data_dir,
+        val_split=val_split,
+        batch_size=batch_size,
+        num_workers=num_workers,
+        parser=icedata.biwi.parser,
+        **preprocess_kwargs,
+    )
+
+
+def keypoint_detection():
+    """Detect keypoints in images."""
+    cli = FlashCLI(
+        KeypointDetector,
+        KeypointDetectionData,
+        default_datamodule_builder=from_biwi,
+        default_arguments={
+            "trainer.max_epochs": 3,
+        },
+    )
+
+    cli.trainer.save_checkpoint("keypoint_detection_model.pt")
+
+
+if __name__ == "__main__":
+    keypoint_detection()

flash_examples/instance_segmentation.py

@@ -27,7 +27,6 @@
 datamodule = InstanceSegmentationData.from_folders(
     train_folder=data_dir,
     val_split=0.1,
-    image_size=128,
     parser=partial(icedata.pets.parser, mask=True),
 )
 

flash_examples/keypoint_detection.py

@@ -25,7 +25,6 @@
 datamodule = KeypointDetectionData.from_folders(
     train_folder=data_dir,
     val_split=0.1,
-    image_size=128,
     parser=icedata.biwi.parser,
 )
 
@@ -52,4 +51,4 @@
 print(predictions)
 
 # 5. Save the model!
-trainer.save_checkpoint("object_detection_model.pt")
+trainer.save_checkpoint("keypoint_detection_model.pt")

tests/image/detection/test_model.py

@@ -124,8 +124,7 @@ def test_load_from_checkpoint_dependency_error():
         ObjectDetector.load_from_checkpoint("not_a_real_checkpoint.pt")
 
 
-@pytest.mark.skipif(not _IMAGE_AVAILABLE, reason="image libraries aren't installed.")
-@pytest.mark.skipif(not _ICEVISION_AVAILABLE, reason="icevision is not installed.")
+@pytest.mark.skipif(not _IMAGE_TESTING, reason="image libraries aren't installed.")
 def test_cli():
     cli_args = ["flash", "object_detection", "--trainer.fast_dev_run", "True"]
     with mock.patch("sys.argv", cli_args):

tests/image/instance_segmentation/test_model.py

@@ -0,0 +1,29 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from unittest import mock
+
+import pytest
+
+from flash.__main__ import main
+from tests.helpers.utils import _IMAGE_TESTING
+
+
+@pytest.mark.skipif(not _IMAGE_TESTING, reason="image libraries aren't installed.")
+def test_cli():
+    cli_args = ["flash", "instance_segmentation", "--trainer.fast_dev_run", "True"]
+    with mock.patch("sys.argv", cli_args):
+        try:
+            main()
+        except SystemExit:
+            pass

tests/image/keypoint_detection/test_model.py

@@ -0,0 +1,29 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from unittest import mock
+
+import pytest
+
+from flash.__main__ import main
+from tests.helpers.utils import _IMAGE_TESTING
+
+
+@pytest.mark.skipif(not _IMAGE_TESTING, reason="image libraries aren't installed.")
+def test_cli():
+    cli_args = ["flash", "keypoint_detection", "--trainer.fast_dev_run", "True"]
+    with mock.patch("sys.argv", cli_args):
+        try:
+            main()
+        except SystemExit:
+            pass