{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "LYKNvTdSQzAo" }, "source": [ "https://www.tensorflow.org/lite/inference_with_metadata/task_library/audio_classifier?hl=zh-cn&authuser=1\n", "\n", "用 Python 运行推断\n", "\n", "第 1 步:安装 pip 软件包\n", "\n", "\n", "pip install tflite-support\n", "\n", "注:Task Library 的 Audio API依靠 PortAudio 来录制来自设备麦克风的音频。如果您打算使用 Task Library 的 AudioRecord 进行音频录制,则需要在您的系统上安装 PortAudio。\n", "\n", "Linux:运行 sudo apt-get update && apt-get install libportaudio2\n", "Mac 和 Windows:安装 tflite-support pip 软件包时会自动安装 PortAudio。\n", "第 2 步:使用模型\n", "\n", "\n", "\n", "请参阅源代码,了解有关配置 AudioClassifier 的更多选项。" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "0hQPjUA6RLgz", "outputId": "e2080672-4938-4cac-a361-71d047fdc17c" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Looking in indexes: https://mirrors.aliyun.com/pypi/simple\n", "Collecting tflite-support\n", " Downloading https://mirrors.aliyun.com/pypi/packages/3e/84/0a17a606f6d1560ba8f45186730d29cd917c2a55260fd6f4a13c121eee31/tflite_support-0.4.3-cp38-cp38-macosx_10_11_x86_64.whl (53.0 MB)\n", "\u001b[K |████████████████████████████████| 53.0 MB 284 kB/s eta 0:00:01 |██████████████ | 23.3 MB 285 kB/s eta 0:01:45 |███████████████████████▍ | 38.6 MB 274 kB/s eta 0:00:53\n", "\u001b[?25hCollecting sounddevice>=0.4.4\n", " Downloading https://mirrors.aliyun.com/pypi/packages/24/5a/c0b9066fcaf783054b3f35254938dcba2d8cf02576ebdc56b6b4e85661f2/sounddevice-0.4.6-py3-none-macosx_10_6_x86_64.macosx_10_6_universal2.whl (107 kB)\n", "\u001b[K |████████████████████████████████| 107 kB 676 kB/s eta 0:00:01\n", "\u001b[?25hCollecting numpy>=1.20.0\n", " Downloading https://mirrors.aliyun.com/pypi/packages/11/10/943cfb579f1a02909ff96464c69893b1d25be3731b5d3652c2e0cf1281ea/numpy-1.24.4-cp38-cp38-macosx_10_9_x86_64.whl (19.8 MB)\n", "\u001b[K |████████████████████████████████| 19.8 MB 278 kB/s eta 0:00:01\n", "\u001b[?25hCollecting flatbuffers>=2.0\n", " Downloading https://mirrors.aliyun.com/pypi/packages/6f/12/d5c79ee252793ffe845d58a913197bfa02ae9a0b5c9bc3dc4b58d477b9e7/flatbuffers-23.5.26-py2.py3-none-any.whl (26 kB)\n", "Requirement already satisfied: absl-py>=0.7.0 in /Users/luis/miniconda3/lib/python3.8/site-packages (from tflite-support) (0.13.0)\n", "Collecting pybind11>=2.6.0\n", " Downloading https://mirrors.aliyun.com/pypi/packages/06/55/9f73c32dda93fa4f539fafa268f9504e83c489f460c380371d94296126cd/pybind11-2.11.1-py3-none-any.whl (227 kB)\n", "\u001b[K |████████████████████████████████| 227 kB 46.0 MB/s eta 0:00:01\n", "\u001b[?25hCollecting protobuf<4,>=3.18.0\n", " Downloading https://mirrors.aliyun.com/pypi/packages/9f/1a/6848ed1669a6c70bf947d25d64ce6dcc65ccec06e917072df516944fa17e/protobuf-3.20.3-cp38-cp38-macosx_10_9_x86_64.whl (982 kB)\n", "\u001b[K |████████████████████████████████| 982 kB 260 kB/s eta 0:00:01\n", "\u001b[?25hRequirement already satisfied: CFFI>=1.0 in /Users/luis/miniconda3/lib/python3.8/site-packages (from sounddevice>=0.4.4->tflite-support) (1.14.3)\n", "Requirement already satisfied: six in /Users/luis/miniconda3/lib/python3.8/site-packages (from absl-py>=0.7.0->tflite-support) (1.15.0)\n", "Requirement already satisfied: pycparser in /Users/luis/miniconda3/lib/python3.8/site-packages (from CFFI>=1.0->sounddevice>=0.4.4->tflite-support) (2.20)\n", "Installing collected packages: sounddevice, numpy, flatbuffers, pybind11, protobuf, tflite-support\n", " Attempting uninstall: numpy\n", " Found existing installation: numpy 1.19.5\n", " Uninstalling numpy-1.19.5:\n", " Successfully uninstalled numpy-1.19.5\n", " Attempting uninstall: flatbuffers\n", " Found existing installation: flatbuffers 1.12\n", " Uninstalling flatbuffers-1.12:\n", " Successfully uninstalled flatbuffers-1.12\n", " Attempting uninstall: protobuf\n", " Found existing installation: protobuf 3.17.3\n", " Uninstalling protobuf-3.17.3:\n", " Successfully uninstalled protobuf-3.17.3\n", "\u001b[31mERROR: After October 2020 you may experience errors when installing or updating packages. This is because pip will change the way that it resolves dependency conflicts.\n", "\n", "We recommend you use --use-feature=2020-resolver to test your packages with the new resolver before it becomes the default.\n", "\n", "tensorflow 2.5.0 requires flatbuffers~=1.12.0, but you'll have flatbuffers 23.5.26 which is incompatible.\n", "tensorflow 2.5.0 requires numpy~=1.19.2, but you'll have numpy 1.24.4 which is incompatible.\n", "pytorch-lightning 2.0.6 requires tqdm>=4.57.0, but you'll have tqdm 4.51.0 which is incompatible.\n", "pytorch-lightning 2.0.6 requires typing-extensions>=4.0.0, but you'll have typing-extensions 3.7.4.3 which is incompatible.\n", "numba 0.56.0 requires numpy<1.23,>=1.18, but you'll have numpy 1.24.4 which is incompatible.\n", "lightning 2.0.6 requires tqdm<6.0,>=4.57.0, but you'll have tqdm 4.51.0 which is incompatible.\n", "lightning 2.0.6 requires typing-extensions<6.0,>=4.0.0, but you'll have typing-extensions 3.7.4.3 which is incompatible.\u001b[0m\n", "Successfully installed flatbuffers-23.5.26 numpy-1.24.4 protobuf-3.20.3 pybind11-2.11.1 sounddevice-0.4.6 tflite-support-0.4.3\n" ] } ], "source": [ "!pip install -i https://mirrors.aliyun.com/pypi/simple tflite-support" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 245.0 }, "id": "Kl6laUiQRBeT", "outputId": "68130993-d7ad-46cf-a189-c67e1843b62d" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/luis/miniconda3/lib/python3.8/site-packages/tensorflow/python/framework/dtypes.py:511: FutureWarning: In the future `np.object` will be defined as the corresponding NumPy scalar.\n", " np.object,\n" ] }, { "ename": "AttributeError", "evalue": "module 'numpy' has no attribute 'object'.\n`np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe. \nThe aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:\n https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/var/folders/8c/clfh0x3s6wg77ms0cdgcbt1w0000gn/T/ipykernel_64159/35834893.py\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Imports\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mtflite_support\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtask\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0maudio\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;32mfrom\u001b[0m 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To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe. \nThe aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:\n https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations" ], "output_type": "error" } ], "source": [ "# Imports\n", "from tflite_support.task import audio\n", "from tflite_support.task import core\n", "from tflite_support.task import processor\n", "\n", "model_path = 'model_v8.1.tflite'\n", "audio_path = 'res/snore/pro_snore 1f6d0dcf8499f3bc _7b23e49bc4f8d31fac175ac362ce34e76550914d.wav'\n", "\n", "# Initialization\n", "base_options = core.BaseOptions(file_name=model_path)\n", "classification_options = processor.ClassificationOptions(max_results=2)\n", "options = audio.AudioClassifierOptions(base_options=base_options, classification_options=classification_options)\n", "classifier = audio.AudioClassifier.create_from_options(options)\n", "\n", "# Alternatively, you can create an audio classifier in the following manner:\n", "# classifier = audio.AudioClassifier.create_from_file(model_path)\n", "\n", "# Run inference\n", "audio_file = audio.TensorAudio.create_from_wav_file(audio_path, classifier.required_input_buffer_size)\n", "audio_result = classifier.classify(audio_file)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "colab": { "provenance": [] }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 1 }