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')