[MO] remove deprecated mean_file option (#14137)

Signed-off-by: andrei.kochin <andrei.kochin@intel.com>

Signed-off-by: andrei.kochin <andrei.kochin@intel.com>

docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Caffe.md

@@ -17,19 +17,6 @@ Caffe-specific parameters:
                         Path to python Caffe parser generated from caffe.proto
   -k K                  Path to CustomLayersMapping.xml to register custom
                         layers
-  --mean_file MEAN_FILE, -mf MEAN_FILE
-                        [DEPRECATED] Mean image to be used for the input. Should be a
-                        binaryproto file
-  --mean_file_offsets MEAN_FILE_OFFSETS, -mo MEAN_FILE_OFFSETS
-                        [DEPRECATED] Mean image offsets to be used for the input
-                        binaryproto file. When the mean image is bigger than
-                        the expected input, it is cropped. By default, centers
-                        of the input image and the mean image are the same and
-                        the mean image is cropped by dimensions of the input
-                        image. The format to pass this option is the
-                        following: "-mo (x,y)". In this case, the mean file is
-                        cropped by dimensions of the input image with offset
-                        (x,y) from the upper left corner of the mean image
   --disable_omitting_optional
                         Disable omitting optional attributes to be used for
                         custom layers. Use this option if you want to transfer

tools/mo/openvino/tools/mo/convert_impl.py

@@ -237,18 +237,6 @@ def arguments_post_parsing(argv: argparse.Namespace):
     if is_tf and argv.tensorflow_use_custom_operations_config is not None:
         argv.transformations_config = argv.tensorflow_use_custom_operations_config
 
-    if is_caffe and argv.mean_file and argv.mean_values:
-        raise Error('Both --mean_file and mean_values are specified. Specify either mean file or mean values. ' +
-                    refer_to_faq_msg(17))
-    elif is_caffe and argv.mean_file and argv.mean_file_offsets:
-        values = get_tuple_values(argv.mean_file_offsets, t=int, num_exp_values=2)
-        mean_file_offsets = mo_array([int(x) for x in values[0].split(',')])
-        if not all([offset >= 0 for offset in mean_file_offsets]):
-            raise Error("Negative value specified for --mean_file_offsets option. "
-                        "Please specify positive integer values in format '(x,y)'. " +
-                        refer_to_faq_msg(18))
-        argv.mean_file_offsets = mean_file_offsets
-
     if argv.scale and argv.scale_values:
         raise Error(
             'Both --scale and --scale_values are defined. Specify either scale factor or scale values per input ' +

tools/mo/openvino/tools/mo/front/caffe/loader.py

@@ -26,59 +26,6 @@ def import_caffe_pb2(caffe_parser_path: str):
 
     return caffe_pb2
 
-
-def parse_mean(file_path: str, in_shape: np.ndarray, mean_file_offsets: [tuple, None], caffe_pb2):
-    blob = caffe_pb2.BlobProto()
-    with open(file_path, 'rb') as file:
-        data = file.read()
-
-    if not data:
-        raise Error('Mean file "{}" is empty.' + refer_to_faq_msg(5),
-                    file_path)
-
-    try:
-        blob.ParseFromString(data)
-        data = mo_array(blob.data)  # pylint: disable=no-member
-
-        if blob.HasField('channels') or blob.HasField('height') or blob.HasField('width'):
-            data = data.reshape(blob.channels, blob.height, blob.width)  # pylint: disable=no-member
-        else:
-            data = data.reshape(blob.shape.dim)  # pylint: disable=no-member
-        # crop mean image according to input size
-        if in_shape[2] > data.shape[1] or in_shape[3] > data.shape[2]:
-            raise Error(
-                'Input image of shape {} is larger than mean image {} from file "{}". ' +
-                refer_to_faq_msg(4),
-                in_shape,
-                data.shape,
-                file_path
-            )
-
-        if mean_file_offsets is not None and len(mean_file_offsets) == 2:
-            offset_x = mean_file_offsets[0]
-            offset_y = mean_file_offsets[1]
-        else:
-            offset_x = int((data.shape[1] - in_shape[2]) / 2)
-            offset_y = int((data.shape[2] - in_shape[3]) / 2)
-
-        mean = []
-        for i in range(in_shape[1]):
-            data_channel = np.zeros(in_shape[2] * in_shape[3], dtype=np.float32)
-            for x in range(in_shape[2]):
-                for y in range(in_shape[3]):
-                    data_channel[x * in_shape[3] + y] = data[i, x + offset_x, y + offset_y]
-            mean.append(data_channel)
-
-        return mean
-
-    except Exception as err:
-        raise Error(
-            'While processing mean file "{}": {}. Probably mean file has incorrect format. ' +
-            refer_to_faq_msg(6),
-            file_path,
-            str(err)) from err
-
-
 def load_caffe_proto_model(caffe_pb2, proto_path: str, model_path: [str, None] = None):
     # 1. python protobuf is used
     if api_implementation._implementation_type == 'python':

tools/mo/openvino/tools/mo/middle/preprocessing.py

@@ -28,17 +28,4 @@ class CaffeMeanFileProcessing(MiddleReplacementPattern):
         caffe_pb2 = graph.graph['caffe_pb2']
         del graph.graph['caffe_pb2']
         input_names = find_inputs(graph)
-        mf = []
-        try:
-            if argv.mean_file and len(original_shapes) == 1:
-                mf = loader.parse_mean(argv.mean_file, original_shapes[input_names[0]],
-                                       argv.mean_file_offsets, caffe_pb2)
-            elif argv.mean_file:
-                raise Error('Mean file for topologies with multiple inputs is not supported. ' +
-                            refer_to_faq_msg(9))
-        except ValueError as e:
-            raise Error('Cannot load or process mean file: value error {}. ' +
-                        refer_to_faq_msg(10), str(e)) from e
-
-        graph.graph['mf'] = mf
         graph.graph['input_names'] = input_names

tools/mo/openvino/tools/mo/utils/cli_parser.py

@@ -823,8 +823,6 @@ class DeprecatedCanonicalizePathCheckExistenceAction(CanonicalizePathCheckExiste
             option_string)
         if 'tensorflow_use_custom_operations_config' in option_string:
             dep_msg += 'Please use --transformations_config cli option instead'
-        if 'mean_file' in option_string or 'mean_offset' in option_string:
-            dep_msg += 'Please use --mean_values cli option instead.'
         log.error(dep_msg, extra={'is_warning': True})
         super().__call__(parser, namespace, values, option_string)
 
@@ -1127,8 +1125,6 @@ def get_caffe_cli_options():
     d = {
         'input_proto': ['- Path to the Input prototxt', lambda x: x],
         'caffe_parser_path': ['- Path to Python Caffe* parser generated from caffe.proto', lambda x: x],
-        'mean_file': ['- Path to a mean file', lambda x: x if x else 'Not specified'],
-        'mean_file_offsets': ['- Offsets for a mean file', lambda x: x if x else 'Not specified'],
         'k': '- Path to CustomLayersMapping.xml',
         'disable_resnet_optimization': ['- Enable resnet optimization', lambda x: not x],
     }
@@ -1181,8 +1177,8 @@ def get_onnx_cli_options():
 
 def get_params_with_paths_list():
     return ['input_model', 'output_dir', 'caffe_parser_path', 'extensions', 'k', 'output_dir',
-            'input_checkpoint', 'input_meta_graph', 'input_proto', 'input_symbol', 'mean_file',
+            'input_checkpoint', 'input_meta_graph', 'input_proto', 'input_symbol',
-            'mean_file_offsets', 'pretrained_model_name', 'saved_model_dir', 'tensorboard_logdir',
+            'pretrained_model_name', 'saved_model_dir', 'tensorboard_logdir',
             'tensorflow_custom_layer_libraries', 'tensorflow_custom_operations_config_update',
             'tensorflow_object_detection_api_pipeline_config', 'tensorflow_use_custom_operations_config',
             'transformations_config']
@@ -1219,20 +1215,6 @@ def get_caffe_cli_parser(parser: argparse.ArgumentParser = None):
                                                   'front', 'caffe',
                                                   'CustomLayersMapping.xml'),
                              action=CanonicalizePathCheckExistenceAction)
-    caffe_group.add_argument('--mean_file', '-mf',
-                             help='[DEPRECATED] ' +
-                                  'Mean image to be used for the input. Should be a binaryproto file',
-                             default=None,
-                             action=DeprecatedCanonicalizePathCheckExistenceAction)
-    caffe_group.add_argument('--mean_file_offsets', '-mo',
-                             help='[DEPRECATED] ' +
-                                  'Mean image offsets to be used for the input binaryproto file. ' +
-                                  'When the mean image is bigger than the expected input, it is cropped. By default, centers ' +
-                                  'of the input image and the mean image are the same and the mean image is cropped by ' +
-                                  'dimensions of the input image. The format to pass this option is the following: "-mo (x,y)". In this ' +
-                                  'case, the mean file is cropped by dimensions of the input image with offset (x,y) ' +
-                                  'from the upper left corner of the mean image',
-                             default=None)
     caffe_group.add_argument('--disable_omitting_optional',
                              help=mo_convert_params_caffe['disable_omitting_optional'].description,
                              action='store_true',