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Diffstat (limited to 'docs/use_cases/kws.md')
| -rw-r--r-- | docs/use_cases/kws.md | 71 |
1 files changed, 37 insertions, 34 deletions
diff --git a/docs/use_cases/kws.md b/docs/use_cases/kws.md index 84eddd6..0c50fe5 100644 --- a/docs/use_cases/kws.md +++ b/docs/use_cases/kws.md @@ -23,7 +23,7 @@ Use-case code could be found in the following directory: [source/use_case/kws](. ### Preprocessing and feature extraction -The `DS-CNN` keyword spotting model that is used with the Code Samples expects audio data to be preprocessed in a +The `MicroNet` keyword spotting model that is used with the Code Samples expects audio data to be preprocessed in a specific way before performing an inference. Therefore, this section aims to provide an overview of the feature extraction process used. @@ -62,7 +62,7 @@ used. ### Postprocessing After an inference is complete, the word with the highest detected probability is output to console. Providing that the -probability is larger than a threshold value. The default is set to `0.9`. +probability is larger than a threshold value. The default is set to `0.7`. If multiple inferences are performed for an audio clip, then multiple results are output. @@ -107,7 +107,7 @@ In addition to the already specified build option in the main documentation, the this number, then it is padded with zeros. The default value is `16000`. - `kws_MODEL_SCORE_THRESHOLD`: Threshold value that must be applied to the inference results for a label to be deemed - valid. Goes from 0.00 to 1.0. The default is `0.9`. + valid. Goes from 0.00 to 1.0. The default is `0.7`. - `kws_ACTIVATION_BUF_SZ`: The intermediate, or activation, buffer size reserved for the NN model. By default, it is set to 2MiB and is enough for most models @@ -247,7 +247,7 @@ For further information: [Optimize model with Vela compiler](../sections/buildin To run the application with a custom model, you must provide a `labels_<model_name>.txt` file of labels that are associated with the model. Each line of the file must correspond to one of the outputs in your model. Refer to the -provided `ds_cnn_labels.txt` file for an example. +provided `micronet_kws_labels.txt` file for an example. Then, you must set `kws_MODEL_TFLITE_PATH` to the location of the Vela processed model file and `kws_LABELS_TXT_FILE`to the location of the associated labels file. @@ -369,24 +369,24 @@ What the preceding choices do: INFO - Model INPUT tensors: INFO - tensor type is INT8 INFO - tensor occupies 490 bytes with dimensions - INFO - 0: 1 - INFO - 1: 1 - INFO - 2: 49 - INFO - 3: 10 + INFO - 0: 1 + INFO - 1: 49 + INFO - 2: 10 + INFO - 3: 1 INFO - Quant dimension: 0 - INFO - Scale[0] = 1.107164 - INFO - ZeroPoint[0] = 95 + INFO - Scale[0] = 0.201095 + INFO - ZeroPoint[0] = -5 INFO - Model OUTPUT tensors: - INFO - tensor type is INT8 - INFO - tensor occupies 12 bytes with dimensions - INFO - 0: 1 - INFO - 1: 12 + INFO - tensor type is INT8 + INFO - tensor occupies 12 bytes with dimensions + INFO - 0: 1 + INFO - 1: 12 INFO - Quant dimension: 0 - INFO - Scale[0] = 0.003906 - INFO - ZeroPoint[0] = -128 - INFO - Activation buffer (a.k.a tensor arena) size used: 72848 - INFO - Number of operators: 1 - INFO - Operator 0: ethos-u + INFO - Scale[0] = 0.056054 + INFO - ZeroPoint[0] = -54 + INFO - Activation buffer (a.k.a tensor arena) size used: 127068 + INFO - Number of operators: 0 + INFO - Operator 0: ethos-u ``` 5. List audio clips: Prints a list of pair ... indexes. The original filenames are embedded in the application, like so: @@ -405,18 +405,21 @@ Please select the first menu option to execute inference on the first file. The following example illustrates the output for classification: -```logINFO - Running inference on audio clip 0 => down.wav +```log + +INFO - Running inference on audio clip 0 => down.wav INFO - Inference 1/1 INFO - Final results: INFO - Total number of inferences: 1 -INFO - For timestamp: 0.000000 (inference #: 0); label: down, score: 0.996094; threshold: 0.900000 +INFO - For timestamp: 0.000000 (inference #: 0); label: down, score: 0.986182; threshold: 0.700000 INFO - Profile for Inference: -INFO - NPU AXI0_RD_DATA_BEAT_RECEIVED beats: 217385 -INFO - NPU AXI0_WR_DATA_BEAT_WRITTEN beats: 82607 -INFO - NPU AXI1_RD_DATA_BEAT_RECEIVED beats: 59608 -INFO - NPU ACTIVE cycles: 680611 -INFO - NPU IDLE cycles: 561 -INFO - NPU TOTAL cycles: 681172 +INFO - NPU AXI0_RD_DATA_BEAT_RECEIVED beats: 132130 +INFO - NPU AXI0_WR_DATA_BEAT_WRITTEN beats: 48252 +INFO - NPU AXI1_RD_DATA_BEAT_RECEIVED beats: 17544 +INFO - NPU ACTIVE cycles: 413814 +INFO - NPU IDLE cycles: 358 +INFO - NPU TOTAL cycles: 414172 + ``` On most systems running Fast Model, each inference takes under 30 seconds. @@ -425,22 +428,22 @@ The profiling section of the log shows that for this inference: - *Ethos-U* PMU report: - - 681,172 total cycle: The number of NPU cycles. + - 414,172 total cycle: The number of NPU cycles. - - 680,611 active cycles: The number of NPU cycles that were used for computation. + - 413,814 active cycles: The number of NPU cycles that were used for computation. - - 561 idle cycles: The number of cycles for which the NPU was idle. + - 358 idle cycles: The number of cycles for which the NPU was idle. - - 217,385 AXI0 read beats: The number of AXI beats with read transactions from the AXI0 bus. AXI0 is the bus where the + - 132,130 AXI0 read beats: The number of AXI beats with read transactions from the AXI0 bus. AXI0 is the bus where the *Ethos-U* NPU reads and writes to the computation buffers, activation buf, or tensor arenas. - - 82,607 write cycles: The number of AXI beats with write transactions to AXI0 bus. + - 48,252 write cycles: The number of AXI beats with write transactions to AXI0 bus. - - 59,608 AXI1 read beats: The number of AXI beats with read transactions from the AXI1 bus. AXI1 is the bus where the + - 17,544 AXI1 read beats: The number of AXI beats with read transactions from the AXI1 bus. AXI1 is the bus where the *Ethos-U* NPU reads the model. So, read-only. - For FPGA platforms, a CPU cycle count can also be enabled. However, do not use cycle counters for FVP, as the CPU model is not cycle-approximate or cycle-accurate. -> **Note:** The application prints the highest confidence score and the associated label from the `ds_cnn_labels.txt` +> **Note:** The application prints the highest confidence score and the associated label from the `micronet_kws_labels.txt` > file. |