Support the offset member in Core ML crop layer parameter. (#119)

* Support the offset member in Core ML crop layer parameter.

* fix the order.

* correct the border value.

* add a docs string.

Author: wenbingl

onnxmltools/convert/coreml/operator_converters/neural_network/Crop.py

@@ -14,12 +14,22 @@ def convert_crop(scope, operator, container):
     op_type = 'Crop'
     attrs = {'name': operator.full_name}
     border = operator.raw_operator.crop.cropAmounts.borderAmounts
-    left = border[1].startEdgeSize
-    top = border[0].startEdgeSize
-    right = border[1].endEdgeSize
-    bottom = border[0].endEdgeSize
-
-    attrs['border'] = [left, top, right, bottom]
+    left_border, top_border, right_border, bottom_border = (None,) * 4
+    if len(border):
+        left_border = border[1].startEdgeSize
+        top_border = border[0].startEdgeSize
+        right_border = border[1].endEdgeSize
+        bottom_border = border[0].endEdgeSize
+    else:
+        offset = operator.raw_operator.crop.offset
+        in_shape = operator.inputs[0].type.shape
+        out_shape = operator.outputs[0].type.shape
+        left_border = offset[1]
+        top_border = offset[0]
+        right_border = in_shape[3] - left_border - out_shape[3]
+        bottom_border = in_shape[2] - top_border - out_shape[2]
+
+    attrs['border'] = [left_border, top_border, right_border, bottom_border]
 
     container.add_node(op_type, operator.input_full_names, operator.output_full_names, **attrs)
 

onnxmltools/convert/coreml/shape_calculators/neural_network/Crop.py

@@ -14,6 +14,7 @@ def calculate_crop_output_shapes(operator):
     '''
     Allowed input/output patterns are
         1. [N, C, H, W] ---> [N, C, H', W']
+        2. [N, C, H, W],  shape-ref [N', C', H', W'] ---> [N, C, H', W']
     '''
     check_input_and_output_numbers(operator, input_count_range=[1, 2], output_count_range=1)
     check_input_and_output_types(operator, good_input_types=[FloatTensorType])
@@ -28,8 +29,8 @@ def calculate_crop_output_shapes(operator):
             output_shape[3] -= params.cropAmounts.borderAmounts[1].startEdgeSize
             output_shape[3] -= params.cropAmounts.borderAmounts[1].endEdgeSize
     elif len(operator.inputs) == 2:
-        output_shape[2] = operator.raw_operator.inputs[1].type.shape[2]
-        output_shape[3] = operator.raw_operator.inputs[1].type.shape[3]
+        output_shape[2] = operator.inputs[1].type.shape[2]
+        output_shape[3] = operator.inputs[1].type.shape[3]
     else:
         raise RuntimeError('Too many inputs for Crop operator')