def coreml_parse(architecture_name, test_input_path):
from mmdnn.conversion.examples.coreml.extractor import coreml_extractor
from mmdnn.conversion.coreml.coreml_parser import CoremlParser
# download model
architecture_file = coreml_extractor.download(architecture_name,
TestModels.cachedir)
# get original model prediction result
original_predict = coreml_extractor.inference(architecture_name,
architecture_file,
test_input_path)
del coreml_extractor
# original to IR
IR_file = TestModels.tmpdir + 'coreml_' + architecture_name + "_converted"
parser = CoremlParser(architecture_file)
parser.run(IR_file)
del parser
del CoremlParser
return original_predict
def main():
loaded_model_ml = _MLModel('result/posenet257.mlmodel')
coremlParser = CoremlParser(loaded_model_ml)
coremlParser.run('result/posenet257_ir')