diff options
Diffstat (limited to 'python/pyarmnn/examples/keyword_spotting/run_audio_classification.py')
| -rw-r--r-- | python/pyarmnn/examples/keyword_spotting/run_audio_classification.py | 11 |
1 files changed, 7 insertions, 4 deletions
diff --git a/python/pyarmnn/examples/keyword_spotting/run_audio_classification.py b/python/pyarmnn/examples/keyword_spotting/run_audio_classification.py index 6dfa4cc806..50ad1a8a2e 100644 --- a/python/pyarmnn/examples/keyword_spotting/run_audio_classification.py +++ b/python/pyarmnn/examples/keyword_spotting/run_audio_classification.py @@ -14,7 +14,7 @@ script_dir = os.path.dirname(__file__) sys.path.insert(1, os.path.join(script_dir, '..', 'common')) from network_executor import ArmnnNetworkExecutor -from utils import prepare_input_tensors, dequantize_output +from utils import prepare_input_data, dequantize_output from mfcc import AudioPreprocessor, MFCC, MFCCParams from audio_utils import decode, display_text from audio_capture import AudioCaptureParams, CaptureAudioStream, capture_audio @@ -69,13 +69,16 @@ def parse_args(): def recognise_speech(audio_data, network, preprocessor, threshold): # Prepare the input Tensors - input_tensors = prepare_input_tensors(audio_data, network.input_binding_info, preprocessor) + input_data = prepare_input_data(audio_data, network.get_data_type(), network.get_input_quantization_scale(0), + network.get_input_quantization_offset(0), preprocessor) # Run inference - output_result = network.run(input_tensors) + output_result = network.run([input_data]) dequantized_result = [] for index, ofm in enumerate(output_result): - dequantized_result.append(dequantize_output(ofm, network.output_binding_info[index])) + dequantized_result.append(dequantize_output(ofm, network.is_output_quantized(index), + network.get_output_quantization_scale(index), + network.get_output_quantization_offset(index))) # Decode the text and display result if above threshold decoded_result = decode(dequantized_result, labels) |