AC: fix video background matting for ov2.0 (#3290)

Author: eaidova

tools/accuracy_checker/openvino/tools/accuracy_checker/evaluators/custom_evaluators/sequential_background_matting_evaluator.py

@@ -21,7 +21,7 @@
 from ...adapters import create_adapter
 from ...config import ConfigError
 from ...launcher.input_feeder import InputFeeder
-from ...utils import contains_all, extract_image_representations
+from ...utils import contains_all, extract_image_representations, postprocess_output_name
 
 
 class SequentialBackgroundMatting(BaseCustomEvaluator):
@@ -109,7 +109,10 @@ def reset_rnn_inputs(self, batch_size):
         for _ in range(batch_size):
             zeros_lstm_inputs = {}
             for lstm_input_name in self.launcher.lstm_inputs.keys():
-                shape = self.model.network.input_info[lstm_input_name].input_data.shape
+                if hasattr(self.model.network, 'input_info'):
+                    shape = self.model.network.input_info[lstm_input_name].input_data.shape
+                else:
+                    shape = self.model.inputs[lstm_input_name].shape
                 zeros_lstm_inputs[lstm_input_name] = np.zeros(shape, dtype=np.float32)
             output.append(zeros_lstm_inputs)
         return output
@@ -119,7 +122,7 @@ def set_rnn_inputs(self, outputs):
         for output in outputs:
             batch_rnn_inputs = {}
             for input_name, output_name in self.launcher.lstm_inputs.items():
-                batch_rnn_inputs[input_name] = output[output_name]
+                batch_rnn_inputs[input_name] = output[postprocess_output_name(output_name, output)]
             result.append(batch_rnn_inputs)
         return result
 
@@ -131,4 +134,4 @@ def predict(self, identifiers, input_data):
 
 class OpenVINOModelSequentialBackgroundMattingModel(BaseOpenVINOModel):
     def predict(self, identifiers, input_data):
-        return self.exec_network.infer(input_data)
+        return self.infer(input_data)

tools/accuracy_checker/openvino/tools/accuracy_checker/launcher/openvino_launcher.py

@@ -323,9 +323,8 @@ def async_mode(self, flag):
 
     def get_async_requests(self):
         self._set_nireq()
-        return [
-            AsyncInferRequestWrapper(ireq_id, self.exec_network.create_infer_request())
-            for ireq_id in range(self.num_requests)]
+        return [AsyncInferRequestWrapper(ireq_id, self.exec_network.create_infer_request())
+                for ireq_id in range(self.num_requests)]
 
     def _reshape_input(self, shapes, make_dynamic=False):
         if hasattr(self, 'exec_network'):
@@ -350,8 +349,7 @@ def reshape_network(network, shapes):
         partial_shapes = {}
         for name, shape in shapes.items():
             p_shape = PartialShape(
-                [Dimension(d) if not isinstance(d, tuple) else Dimension(d[0], d[1]) for d in shape]
-            )
+                [Dimension(d) if not isinstance(d, tuple) else Dimension(d[0], d[1]) for d in shape])
             partial_shapes[name] = p_shape
         network.reshape(partial_shapes)
         return network
@@ -493,8 +491,7 @@ def _set_device_config(self, device_config):
                         ov_set_config(self.ie_core, dict(value), device=key)
                     else:
                         warnings.warn(
-                            f'Configuration for {key} will be skipped as device is not listed in evaluation device'
-                        )
+                            f'Configuration for {key} will be skipped as device is not listed in evaluation device')
                 else:
                     warnings.warn('Option {key}: {value} will be skipped because device to which it should be '
                                   'applied is not specified or option is not a dict-like'.format(key=key, value=value))
@@ -725,8 +722,11 @@ def inputs_info_for_meta(self, inputs=None):
             return {layer_name: np.shape(data) for layer_name, data in inputs.items()}
         return {
             layer_name: parse_partial_shape(layer.get_partial_shape()) for layer_name, layer in self.inputs.items()
-            if layer_name not in self.const_inputs + self.image_info_inputs
-        }
+            if layer_name not in self.const_inputs + self.image_info_inputs}
+
+    @property
+    def lstm_inputs(self):
+        return self._lstm_inputs
 
     def initialize_undefined_shapes(self, input_data, template_shapes=None):
         if self.dynamic_shapes_policy in ['default', 'dynamic']:

tools/accuracy_checker/openvino/tools/accuracy_checker/metrics/background_matting.py

@@ -33,7 +33,6 @@
     convolve = UnsupportedPackage('scipy', err.msg)
 
 
-
 class BaseBackgroundMattingMetrics(PerImageEvaluationMetric):
     annotation_types = (BackgroundMattingAnnotation,)
     prediction_types = (BackgroundMattingPrediction,)
@@ -86,7 +85,7 @@ def configure(self):
 
     @classmethod
     def get_common_meta(cls):
-        return {'target': 'higher-worse'}
+        return {'target': 'higher-worse', 'scale': 1, 'postfix': ' '}
 
 
 class MeanOfAbsoluteDifference(BaseBackgroundMattingMetrics):