#48 add FrameParameters class for processing frame config

samples/peoplenet_detector/module.yml

@@ -1,8 +1,9 @@
 name: ${oc.env:MODULE_NAME, 'regular-cam-human-detector-peoplenet'}
 
 parameters:
-  frame_width: 960
-  frame_height: 544
+  frame:
+    width: 960
+    height: 544
   output_frame: ${json:${oc.env:OUTPUT_FRAME, '{"codec":"jpeg"}'}}
 
 pipeline:

savant/config/default.yml

@@ -29,9 +29,10 @@ parameters:
         port: 2379
     timeout: 15
 
-  # pipeline processing frame width/height, default 720p
-  frame_width: ${oc.decode:${oc.env:FRAME_WIDTH, 1280}}
-  frame_height: ${oc.decode:${oc.env:FRAME_HEIGHT, 720}}
+  # pipeline processing frame parameters, default 720p
+  frame:
+    width: ${oc.decode:${oc.env:FRAME_WIDTH, 1280}}
+    height: ${oc.decode:${oc.env:FRAME_HEIGHT, 720}}
 
   # FPS measurement period
   fps_period: ${oc.decode:${oc.env:FPS_PERIOD, 10000}}

savant/config/initializer_resolver.py

@@ -23,7 +23,8 @@ def initializer_resolver(param_name: str, default_val: Any, _parent_, _root_) ->
             etcd: 10
 
         parameters:
-            frame_width: ${initializer:frame_width,1280}
+            frame:
+                width: ${initializer:frame_width,1280}
 
     where
 

savant/config/module_config.py

@@ -11,6 +11,7 @@
     ModelElement,
     get_element_name,
     DrawFunc,
+    FrameParameters,
 )
 from savant.deepstream.nvinfer.element_config import nvinfer_configure_element
 from savant.parameter_storage import init_param_storage
@@ -153,12 +154,17 @@ def setup_batch_size(config: Module) -> None:
     config.parameters['batch_size'] = batch_size
 
 
-def resolve_draw_func_parameter(config: DictConfig):
-    """Resolve draw_func parameter on module config.
+def resolve_parameters(config: DictConfig):
+    """Resolve parameters on module config ("frame", "draw_func", etc.).
 
     :param config: Module config.
     """
 
+    config.parameters['frame'] = OmegaConf.unsafe_merge(
+        OmegaConf.structured(FrameParameters),
+        config.parameters['frame'],
+    )
+
     draw_func_cfg = config.parameters.get('draw_func')
     if draw_func_cfg is not None:
         draw_func_schema = OmegaConf.structured(DrawFunc)
@@ -195,11 +201,11 @@ def load(self, config_file_path: Union[str, Path]) -> Module:
         module_cfg = OmegaConf.unsafe_merge(
             self._config_schema, self._default_cfg, module_cfg
         )
-        resolve_draw_func_parameter(module_cfg)
         logger.debug('Merged conf\n%s', module_cfg)
         init_param_storage(module_cfg)
 
         OmegaConf.resolve(module_cfg)  # to resolve parameters for pipeline elements
+        resolve_parameters(module_cfg)
         logger.debug('Resolved conf\n%s', module_cfg)
         logger.info('Configure pipeline elements...')
 

savant/config/schema.py

@@ -7,6 +7,17 @@
 from savant.base.pyfunc import PyFunc
 
 
+@dataclass
+class FrameParameters:
+    """Pipeline processing frame parameters"""
+
+    width: int
+    """Pipeline processing frame width"""
+
+    height: int
+    """Pipeline processing frame height"""
+
+
 @dataclass
 class DynamicGstProperty:
     """Allows configuring a gstreamer element property to be automatically
@@ -350,7 +361,8 @@ class Module:
     .. code-block:: yaml
 
         parameters:
-            frame_width: ${initializer:frame_width,1280}
+            frame:
+                width: ${initializer:frame_width,1280}
 
     Etcd storage will be polled for the current value first,
     in the event etcd is unavailable resolver will

savant/deepstream/buffer_processor.py

@@ -11,7 +11,7 @@
 from pysavantboost import ObjectsPreprocessing
 
 from savant.base.model import ObjectModel, ComplexModel
-from savant.config.schema import PipelineElement, ModelElement
+from savant.config.schema import PipelineElement, ModelElement, FrameParameters
 from savant.converter.scale import scale_rbbox
 from savant.deepstream.base_drawfunc import BaseNvDsDrawFunc
 from savant.deepstream.nvinfer.model import (
@@ -61,8 +61,7 @@ def __init__(
         sources: SourceInfoRegistry,
         model_object_registry: ModelObjectRegistry,
         objects_preprocessing: ObjectsPreprocessing,
-        frame_width: int,
-        frame_height: int,
+        frame_params: FrameParameters,
     ):
         """Buffer processor for DeepStream pipeline.
 
@@ -71,16 +70,14 @@ def __init__(
         :param sources: Source info registry.
         :param model_object_registry: Model.Object registry.
         :param objects_preprocessing: Objects processing registry.
-        :param frame_width: Processing frame width (after nvstreammux).
-        :param frame_height: Processing frame height (after nvstreammux).
+        :param frame_params: Processing frame parameters (after nvstreammux).
         """
 
         super().__init__(queue, fps_meter)
         self._sources = sources
         self._model_object_registry = model_object_registry
         self._objects_preprocessing = objects_preprocessing
-        self._frame_width = frame_width
-        self._frame_height = frame_height
+        self._frame_params = frame_params
         self._queue = queue
 
     def prepare_input(self, buffer: Gst.Buffer):
@@ -136,16 +133,16 @@ def prepare_input(self, buffer: Gst.Buffer):
                                     ]
                                 ]
                             ),
-                            scale_factor_x=self._frame_width,
-                            scale_factor_y=self._frame_height,
+                            scale_factor_x=self._frame_params.width,
+                            scale_factor_y=self._frame_params.height,
                         )[0]
                         selection_type = ObjectSelectionType.ROTATED_BBOX
                     else:
                         scaled_bbox = (
-                            obj_meta['bbox']['xc'] * self._frame_width,
-                            obj_meta['bbox']['yc'] * self._frame_height,
-                            obj_meta['bbox']['width'] * self._frame_width,
-                            obj_meta['bbox']['height'] * self._frame_height,
+                            obj_meta['bbox']['xc'] * self._frame_params.width,
+                            obj_meta['bbox']['yc'] * self._frame_params.height,
+                            obj_meta['bbox']['width'] * self._frame_params.width,
+                            obj_meta['bbox']['height'] * self._frame_params.height,
                             obj_meta['bbox']['angle'],
                         )
                         selection_type = ObjectSelectionType.REGULAR_BBOX
@@ -175,10 +172,10 @@ def prepare_input(self, buffer: Gst.Buffer):
                 gie_uid=model_uid,
                 # tuple(xc, yc, width, height, angle)
                 bbox=(
-                    self._frame_width / 2,
-                    self._frame_height / 2,
-                    self._frame_width,
-                    self._frame_height,
+                    self._frame_params.width / 2,
+                    self._frame_params.height / 2,
+                    self._frame_params.width,
+                    self._frame_params.height,
                     0,
                 ),
                 obj_label=obj_label,
@@ -267,8 +264,8 @@ def prepare_element_input(self, element: PipelineElement, buffer: Gst.Buffer):
                     else:
                         parent_bbox.left = 0
                         parent_bbox.top = 0
-                        parent_bbox.width = self._frame_width
-                        parent_bbox.height = self._frame_height
+                        parent_bbox.width = self._frame_params.width
+                        parent_bbox.height = self._frame_params.height
 
                     bbox = model.input.preprocess_object_meta(
                         bbox, parent_bbox=parent_bbox
@@ -376,11 +373,11 @@ def prepare_element_output(self, element: PipelineElement, buffer: Gst.Buffer):
                                 bbox_tensor[:, 2][bbox_tensor[:, 2] < 0.0] = 0.0
                                 bbox_tensor[:, 3][bbox_tensor[:, 3] < 0.0] = 0.0
                                 bbox_tensor[:, 4][
-                                    bbox_tensor[:, 4] > self._frame_width - 1.0
-                                ] = (self._frame_width - 1.0)
+                                    bbox_tensor[:, 4] > self._frame_params.width - 1.0
+                                ] = (self._frame_params.width - 1.0)
                                 bbox_tensor[:, 5][
-                                    bbox_tensor[:, 5] > self._frame_height - 1.0
-                                ] = (self._frame_height - 1.0)
+                                    bbox_tensor[:, 5] > self._frame_params.height - 1.0
+                                ] = (self._frame_params.height - 1.0)
 
                                 # right to width, bottom to height
                                 bbox_tensor[:, 4] -= bbox_tensor[:, 2]
@@ -540,8 +537,7 @@ def __init__(
         sources: SourceInfoRegistry,
         model_object_registry: ModelObjectRegistry,
         objects_preprocessing: ObjectsPreprocessing,
-        frame_width: int,
-        frame_height: int,
+        frame_params: FrameParameters,
         codec: CodecInfo,
     ):
         """Buffer processor for DeepStream pipeline.
@@ -551,8 +547,7 @@ def __init__(
         :param sources: Source info registry.
         :param model_object_registry: Model.Object registry.
         :param objects_preprocessing: Objects processing registry.
-        :param frame_width: Processing frame width (after nvstreammux).
-        :param frame_height: Processing frame height (after nvstreammux).
+        :param frame_params: Processing frame parameters (after nvstreammux).
         :param codec: Codec of the output frames.
         """
 
@@ -563,8 +558,7 @@ def __init__(
             sources=sources,
             model_object_registry=model_object_registry,
             objects_preprocessing=objects_preprocessing,
-            frame_width=frame_width,
-            frame_height=frame_height,
+            frame_params=frame_params,
         )
 
     def _iterate_output_frames(self, buffer: Gst.Buffer) -> Iterator[_OutputFrame]:
@@ -593,8 +587,7 @@ def __init__(
         sources: SourceInfoRegistry,
         model_object_registry: ModelObjectRegistry,
         objects_preprocessing: ObjectsPreprocessing,
-        frame_width: int,
-        frame_height: int,
+        frame_params: FrameParameters,
         output_frame: bool,
         draw_func: Optional[BaseNvDsDrawFunc],
     ):
@@ -605,8 +598,7 @@ def __init__(
         :param sources: Source info registry.
         :param model_object_registry: Model.Object registry.
         :param objects_preprocessing: Objects processing registry.
-        :param frame_width: Processing frame width (after nvstreammux).
-        :param frame_height: Processing frame height (after nvstreammux).
+        :param frame_params: Processing frame parameters (after nvstreammux).
         :param output_frame: Whether to output frame or not.
         :param draw_func: PyFunc for drawing on frames.
         """
@@ -620,8 +612,7 @@ def __init__(
             sources=sources,
             model_object_registry=model_object_registry,
             objects_preprocessing=objects_preprocessing,
-            frame_width=frame_width,
-            frame_height=frame_height,
+            frame_params=frame_params,
         )
 
     def _iterate_output_frames(self, buffer: Gst.Buffer) -> Iterator[_OutputFrame]:

savant/deepstream/metadata.py

@@ -3,6 +3,7 @@
 import numpy as np
 import pyds
 
+from savant.config.schema import FrameParameters
 from savant.converter.scale import scale_rbbox
 from savant.deepstream.utils import nvds_get_rbbox
 from savant.meta.attribute import AttributeMeta
@@ -11,14 +12,12 @@
 
 def nvds_obj_meta_output_converter(
     nvds_obj_meta: pyds.NvDsObjectMeta,
-    frame_width: int,
-    frame_height: int,
+    frame_params: FrameParameters,
 ) -> Dict[str, Any]:
     """Convert object meta to output format.
 
     :param nvds_obj_meta: NvDsObjectMeta
-    :param frame_width: Frame width, to scale to [0..1]
-    :param frame_height: Frame height
+    :param frame_params: Frame parameters (width/height, to scale to [0..1]
     :return: dict
     """
     model_name, label = ModelObjectRegistry.parse_model_object_key(
@@ -46,8 +45,8 @@ def nvds_obj_meta_output_converter(
                     ]
                 ]
             ),
-            scale_factor_x=1 / frame_width,
-            scale_factor_y=1 / frame_height,
+            scale_factor_x=1 / frame_params.width,
+            scale_factor_y=1 / frame_params.height,
         )[0]
         bbox = dict(
             xc=scaled_bbox[0],
@@ -57,11 +56,11 @@ def nvds_obj_meta_output_converter(
             angle=scaled_bbox[4],
         )
     else:
-        obj_width = rect_params.width / frame_width
-        obj_height = rect_params.height / frame_height
+        obj_width = rect_params.width / frame_params.width
+        obj_height = rect_params.height / frame_params.height
         bbox = dict(
-            xc=rect_params.left / frame_width + obj_width / 2,
-            yc=rect_params.top / frame_height + obj_height / 2,
+            xc=rect_params.left / frame_params.width + obj_width / 2,
+            yc=rect_params.top / frame_params.height + obj_height / 2,
             width=obj_width,
             height=obj_height,
         )

savant/deepstream/pipeline.py

@@ -51,7 +51,7 @@
 from savant.utils.model_registry import ModelObjectRegistry
 from savant.utils.source_info import SourceInfoRegistry, SourceInfo, Resolution
 from savant.utils.platform import is_aarch64
-from savant.config.schema import PipelineElement, ModelElement
+from savant.config.schema import PipelineElement, ModelElement, FrameParameters
 from savant.base.model import AttributeModel, ComplexModel
 from savant.utils.sink_factories import SinkEndOfStream
 
@@ -62,8 +62,7 @@ class NvDsPipeline(GstPipeline):
     :param name: Pipeline name
     :param source: Pipeline source element
     :param elements: Pipeline elements
-    :key frame_width: Processing frame width (after nvstreammux)
-    :key frame_height: Processing frame height (after nvstreammux)
+    :key frame_params: Processing frame parameters (after nvstreammux)
     :key batch_size: Primary batch size (nvstreammux batch-size)
     :key output_frame: Whether to include frame in module output, not just metadata
     """
@@ -76,8 +75,7 @@ def __init__(
         **kwargs,
     ):
         # pipeline internal processing frame size
-        self._frame_width = kwargs['frame_width']
-        self._frame_height = kwargs['frame_height']
+        self._frame_params: FrameParameters = kwargs['frame']
 
         self._batch_size = kwargs['batch_size']
         # Timeout in microseconds
@@ -162,8 +160,7 @@ def _build_buffer_processor(
                 sources=self._sources,
                 model_object_registry=model_object_registry,
                 objects_preprocessing=self._objects_preprocessing,
-                frame_width=self._frame_width,
-                frame_height=self._frame_height,
+                frame_params=self._frame_params,
                 output_frame=self._output_frame_codec is not None,
                 draw_func=self._draw_func,
             )
@@ -173,8 +170,7 @@ def _build_buffer_processor(
             sources=self._sources,
             model_object_registry=model_object_registry,
             objects_preprocessing=self._objects_preprocessing,
-            frame_width=self._frame_width,
-            frame_height=self._frame_height,
+            frame_params=self._frame_params,
             codec=self._output_frame_codec.value,
         )
 
@@ -503,7 +499,7 @@ def update_frame_meta(self, pad: Gst.Pad, info: Gst.PadProbeInfo):
                     continue
 
                 obj_meta = nvds_obj_meta_output_converter(
-                    nvds_obj_meta, self._frame_width, self._frame_height
+                    nvds_obj_meta, self._frame_params
                 )
                 for attr_meta_list in nvds_attr_meta_iterator(
                     frame_meta=nvds_frame_meta, obj_meta=nvds_obj_meta
@@ -531,8 +527,8 @@ def _create_muxer(self, live_source: bool) -> Gst.Element:
         """
 
         frame_processing_parameters = {
-            'width': self._frame_width,
-            'height': self._frame_height,
+            'width': self._frame_params.width,
+            'height': self._frame_params.height,
             'batch-size': self._batch_size,
             # Allowed range for batch-size: 1 - 1024
             # Allowed range for buffer-pool-size: 4 - 1024