Add plugin docs

datumaro/components/project.py

@@ -277,7 +277,8 @@ def categories(_):
 
         return self.transform(_DatasetFilter)
 
-    def export(self, save_dir: str, format, **kwargs):
+    def export(self, save_dir: str, format, \
+            **kwargs): #pylint: disable=redefined-builtin
         dataset = Dataset.from_extractors(self, env=self.env)
         dataset.export(save_dir, format, **kwargs)
 

docs/user_manual.md

@@ -24,6 +24,7 @@
   - [Run inference explanation](#explain-inference)
   - [Transform project](#transform-project)
 - [Extending](#extending)
+  - [Builtin plugins](#builtin-plugins)
 - [Links](#links)
 
 ## Installation
@@ -1030,6 +1031,43 @@ In general, a plugin is a Python code file. It must be put into a plugin directo
 - `<project_dir>/.datumaro/plugins` for project-specific plugins
 - `<datumaro_dir>/plugins` for global plugins
 
+### Built-in plugins
+
+Datumaro provides several builtin plugins. Plugins can have dependencies,
+which need to be installed separately.
+
+#### TensorFlow
+
+The plugin provides support of TensorFlow Detection API format, which includes
+boxes and masks. It depends on TensorFlow, which can be installed with `pip`:
+
+```bash
+pip install tensorflow
+# or
+pip install tensorflow-gpu
+# or
+pip install datumaro[tf]
+# or
+pip install datumaro[tf-gpu]
+```
+
+#### Accuracy Checker
+
+This plugin allows to use [Accuracy Checker](https://github.com/openvinotoolkit/open_model_zoo/tree/master/tools/accuracy_checker)
+to launch deep learning models from various frameworks
+(Caffe, MxNet, PyTorch, OpenVINO, ...) through Accuracy Checker's API.
+The plugin depends on Accuracy Checker, which can be installed with `pip`:
+
+```bash
+pip install 'git+https://github.com/openvinotoolkit/open_model_zoo.git#subdirectory=tools/accuracy_checker'
+```
+
+#### OpenVINO™
+
+This plugin provides support for model inference with [OpenVINO™](https://01.org/openvinotoolkit).
+The plugin depends on the OpenVINO™ Tookit, which can be installed by
+following [these instructions](https://docs.openvinotoolkit.org/latest/index.html#packaging_and_deployment)
+
 ### Dataset Formats
 
 Dataset reading is supported by Extractors and Importers.

tests/test_dataset.py

@@ -528,7 +528,7 @@ def __iter__(self):
                     DatasetItem(4),
                 ])
 
-            def get(self, id, subset=None):
+            def get(self, id, subset=None): #pylint: disable=redefined-builtin
                 nonlocal get_called
                 get_called += 1
                 return DatasetItem(id, subset=subset)