chore: add pre-commit

.pre-commit-config.yaml

@@ -0,0 +1,50 @@
+# To use:
+#
+#     pre-commit run -a
+#
+# Or:
+#
+#     pre-commit install  # (runs every time you commit in git)
+#
+# To update this file:
+#
+#     pre-commit autoupdate
+#
+# See https://github.com/pre-commit/pre-commit
+
+repos:
+  # Standard hooks
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.1.0
+    hooks:
+      - id: check-added-large-files
+      - id: check-ast
+      - id: check-case-conflict
+      - id: check-docstring-first
+      - id: check-merge-conflict
+      - id: check-symlinks
+      - id: check-xml
+      - id: check-yaml
+      - id: debug-statements
+      - id: mixed-line-ending
+      - id: trailing-whitespace
+      - id: fix-byte-order-marker
+
+  # Python hooks
+  - repo: https://github.com/asottile/pyupgrade
+    rev: v2.31.0
+    hooks:
+    -   id: pyupgrade
+        args: [--py36-plus]
+
+  - repo: https://github.com/psf/black
+    rev: 22.3.0
+    hooks:
+      - id: black
+        args: ["--line-length=99"]
+
+  - repo: https://github.com/pycqa/flake8
+    rev: 4.0.1
+    hooks:
+    - id: flake8
+      args: ["--ignore=E203, E266, E501, W503, F403, F401 --max-line-length = 99"]

README.md

@@ -18,7 +18,7 @@ nuctl deploy --project-name cvat \
 
 ### Get started
 
-In order to develop you'll want a nuclio instance running on your local machine... 
+In order to develop you'll want a nuclio instance running on your local machine...
 
 * `docker-compose up` to start nuclio.
 * `./scripts/build.sh` to build `ghcr.io/greenroom-robotics/nuclio_lighting_flash:latest`
@@ -30,6 +30,10 @@ nuctl deploy --project-name cvat \
   --platform local
 ```
 
+### Run tests
+
+* `./scripts/build.sh && docker run ghcr.io/greenroom-robotics/nuclio_lighting_flash:latest` to build and run pytests
+
 ### Release a version
 
 * Run the [Release](./.github/workflows/release.yml) workflow on github

nuclio_lighting_flash/flash_model_handler.py

@@ -36,4 +36,4 @@ def infer(self, image: Image, threshold: float = 0.0):
         )
         if predictions is None:
             return []
-        return predictions[0][0]
+        return predictions[0][0]

nuclio_lighting_flash/flash_model_handler_in_memory.py

@@ -5,7 +5,6 @@
 from flash.core.data.io.output import Output
 from flash.core.data.io.input import DataKeys
 from flash.core.data.data_module import DataModule
-from flash.core.data.io.input import DataKeys
 from flash.core.data.io.output_transform import OutputTransform
 from flash.core.trainer import Trainer
 from flash.core.utilities.stages import RunningStage

nuclio_lighting_flash/nuclio_detection_labels_output.py

@@ -34,9 +34,7 @@ def transform(self, sample: Dict[str, Any]) -> List[Dict[str, Any]]:
 
         preds = sample[DataKeys.PREDS]
 
-        for bbox, label, score in zip(
-            preds["bboxes"], preds["labels"], preds["scores"]
-        ):
+        for bbox, label, score in zip(preds["bboxes"], preds["labels"], preds["scores"]):
             confidence = score.tolist()
 
             if self.threshold is not None and confidence < self.threshold: