{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Predict\n", "Similar to training, prediction can be done via three interfaces:\n", "- via python, `das.predict.predict`\n", "- via the command line, `das predict`, with audio data from a wav file.\n", "- the GUI - see the [GUI tutorial](/tutorials_gui/predict)\n", "\n", "Prediction will:\n", "\n", "- load the audio data and the network\n", "- run inference to produce confidence scores (`class_probabilties`)\n", "- post-process the confidence score to extract the times of events and label segments.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prediction using python" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on function predict in module das.predict:\n", "\n", "predict(x: numpy.ndarray, model_save_name: str = None, verbose: int = 1, batch_size: int = None, model: keras.engine.training.Model = None, params: dict = None, event_thres: float = 0.5, event_dist: float = 0.01, event_dist_min: float = 0, event_dist_max: float = None, segment_thres: float = 0.5, segment_use_optimized: bool = True, segment_minlen: float = None, segment_fillgap: float = None, pad: bool = True, prepend_data_padding: bool = True)\n", " [summary]\n", " \n", " Usage:\n", " Calling predict with the path to the model will load the model and the\n", " associated params and run inference:\n", " `das.predict.predict(x=data, model_save_name='tata')`\n", " \n", " To re-use the same model with multiple recordings, load the modal and params\n", " once and pass them to `predict`\n", " ```my_model, my_params = das.utils.load_model_and_params(model_save_name)\n", " for data in data_list:\n", " das.predict.predict(x=data, model=my_model, params=my_params)\n", " ```\n", " \n", " Args:\n", " x (np.array): Audio data [samples, channels]\n", " model_save_name (str): path with the trunk name of the model. Defaults to None.\n", " model (keras.model.Models): Defaults to None.\n", " params (dict): Defaults to None.\n", " \n", " verbose (int): display progress bar during prediction. Defaults to 1.\n", " batch_size (int): number of chunks processed at once . Defaults to None (the default used during training).\n", " Larger batches lead to faster inference. Limited by memory size, in particular for GPUs which typically have 8GB.\n", " Large batch sizes lead to loss of samples since only complete batches are used.\n", " pad (bool): Append zeros to fill up batch. Otherwise the end can be cut.\n", " Defaults to False\n", " \n", " event_thres (float): Confidence threshold for detecting peaks. Range 0..1. Defaults to 0.5.\n", " event_dist (float): Minimal distance between adjacent events during thresholding.\n", " Prevents detecting duplicate events when the confidence trace is a little noisy.\n", " Defaults to 0.01.\n", " event_dist_min (float): MINimal inter-event interval for the event filter run during post processing.\n", " Defaults to 0.\n", " event_dist_max (float): MAXimal inter-event interval for the event filter run during post processing.\n", " Defaults to None (no upper limit).\n", " \n", " segment_thres (float): Confidence threshold for detecting segments. Range 0..1. Defaults to 0.5.\n", " segment_use_optimized (bool): Use minlen and fillgap values from param file if they exist.\n", " If segment_minlen and segment_fillgap are provided,\n", " then they will override the values from the param file.\n", " Defaults to True.\n", " segment_minlen (float): Minimal duration in seconds of a segment used for filtering out spurious detections. Defaults to None.\n", " segment_fillgap (float): Gap in seconds between adjacent segments to be filled. Useful for correcting brief lapses. Defaults to None.\n", " \n", " pad (bool): prepend values (repeat last sample value) to fill the last batch. Otherwise, the end of the data will not be annotated because\n", " the last, non-full batch will be skipped.\n", " prepend_data_padding (bool, optional): Restores samples that are ignored\n", " in the beginning of the first and the end of the last chunk\n", " because of \"ignore_boundaries\". Defaults to True.\n", " Raises:\n", " ValueError: [description]\n", " \n", " Returns:\n", " events: [description]\n", " segments: [description]\n", " class_probabilities (np.array): [T, nb_classes]\n", " class_names (List[str]): [nb_classes]\n", "\n" ] } ], "source": [ "import numpy as np\n", "from pprint import pprint\n", "import scipy.io.wavfile\n", "import das.predict\n", "help(das.predict.predict)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DAS requires [T, channels], but single-channel wave files are loaded with shape [T,] (data shape is (35000,)).\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/Users/clemens10/miniconda3/lib/python3.9/site-packages/keras/layers/core.py:1043: UserWarning: dss.tcn.tcn is not loaded, but a Lambda layer uses it. It may cause errors.\n", " warnings.warn('{} is not loaded, but a Lambda layer uses it. '\n", "2022-07-25 13:02:25.335763: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA\n", "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "2022-07-25 13:02:25.918851: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "20/20 - 2s\n", "CPU times: user 5.92 s, sys: 895 ms, total: 6.82 s\n", "Wall time: 2.62 s\n" ] } ], "source": [ "%%time\n", "samplerate, x = scipy.io.wavfile.read('dat/dmel_song_rt.wav')\n", "print(f\"DAS requires [T, channels], but single-channel wave files are loaded with shape [T,] (data shape is {x.shape}).\")\n", "x = np.atleast_2d(x).T\n", "events, segments, class_probabilities, class_names = das.predict.predict(x, \n", " model_save_name='models/dmel_single_rt/20200430_201821',\n", " verbose=2,\n", " segment_minlen=0.02,\n", " segment_fillgap=0.02)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Outputs of `predict`\n", "- `class_probabilties`: `[T, nb_classes]` including noise.\n", "- `segments`: Labelled segments\n", " - `samplerate_Hz`: \n", " - `names`: names of all segment types\n", " - `index`: indices of all segments types into class_probabiltiies\n", " - `probabilities = class_probabilites[:, index]`\n", " - `sequence`: sequence of segment names (one entry per detected segment). Excludes noise\n", " - `samples`: labelled sample trace (label of the sequence occupying each sample)\n", " - `onsets_seconds`, `offsets_seconds`, `durations_seconds`: Onsets, offsets, and duration of individual segmeents\n", "- `events`: Detected events\n", " - `samplerate_Hz`: \n", " - `index`: indices of all events types into class_probabiltiies\n", " - `names`: names of all event types\n", " - `probabilities`: probabilities (confidence scores) for detected events. Value of `class_probabilities` for the detected event index at each event time.\n", " - `seconds`: times (seconds) of detected events\n", " - `sequence`: sequence of event names (one per detected event)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "plt.style.use('ncb.mplstyle')\n", "\n", "t0 = 0\n", "t1 = 30_000 \n", "fs =segments['samplerate_Hz']\n", "time = np.arange(t0, t1) / fs\n", "nb_classes = class_probabilities.shape[1]\n", "\n", "plt.figure(figsize=(30, 10))\n", "plt.subplot(411)\n", "plt.plot(time, x[t0:t1], 'k', linewidth=0.5)\n", "plt.title('Song')\n", "plt.xticks([])\n", "plt.ylim(-0.25, 0.25)\n", "\n", "plt.subplot(412)\n", "plt.imshow(class_probabilities[t0:t1].T, cmap='Greys')\n", "plt.yticks(np.arange(nb_classes), labels=class_names)\n", "plt.title('Raw confidence scores')\n", "plt.xticks([])\n", "\n", "ax = plt.subplot(413)\n", "plt.plot(time, x[t0:t1],'k', linewidth=0.5)\n", "plt.ylim(-0.25, 0.25)\n", "plt.title('Annotations')\n", "plt.xlabel('Time [seconds]')\n", "for onset, offset, segment_name in zip(segments['onsets_seconds'], segments['offsets_seconds'], segments['sequence']):\n", " if onset >= t0 /fs and offset <= t1 / fs:\n", " plt.plot([onset, offset], [0.1, 0.1], c='b')\n", " ax.annotate(segment_name, xy=(onset, 0.11), c='b')\n", "\n", "for pulse_time, pulse_name in zip(events['seconds'], events['sequence']):\n", " if pulse_time >= t0 /fs and pulse_time <= t1 / fs:\n", " plt.axvline(pulse_time, c='r')\n", " ax.annotate(pulse_name, xy=(pulse_time, 0.1), c='r', rotation=-90)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prediction using command-line scripts\n", "Will save the output of `das.predict.predict` to a h5 file ending in `_das.h5` or specified via the `--save-filename` argument.\n", "\n", "See [cli](/technical/cli) for a full list of arguments." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:root:Loading model from models/dmel_single_rt/20200430_201821.\n", "2022-07-25 13:02:37.243085: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA\n", "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "INFO:root: Loading data from dat/dmel_song_rt.wav.\n", "INFO:root: Annotating using model at models/dmel_single_rt/20200430_201821.\n", "2022-07-25 13:02:37.763758: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n", "20/20 [==============================] - 2s 68ms/step\n", "INFO:root: found 29 instances of events '['pulse']'.\n", "INFO:root: found 15 instances of segments '['sine']'.\n", "INFO:root: Saving results to dat/dmel_song_rt_annotations.csv.\n", "INFO:root:Done.\n", "\u001b[0m" ] } ], "source": [ "!das predict dat/dmel_song_rt.wav models/dmel_single_rt/20200430_201821" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['class_names', 'class_probabilities', 'events', 'segments']\n" ] } ], "source": [ "import h5py\n", "with h5py.File('dat/dmel_song_rt_das.h5', mode='r') as f:\n", " print(list(f.keys()))" ] } ], "metadata": { "file_extension": ".py", "kernelspec": { "display_name": "Python 3.9.9 ('base')", "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": "3.9.9" }, "mimetype": "text/x-python", "name": "python", "npconvert_exporter": "python", "pygments_lexer": "ipython3", "version": 3, "vscode": { "interpreter": { "hash": "7ea0ec616133ead53c1908c8f6539f5c0cb9b2f78368e2bb6ab3f847e89ca400" } } }, "nbformat": 4, "nbformat_minor": 4 }