From 9fc713d3901c95eb927cb3a146a6e6c0e45ff616 Mon Sep 17 00:00:00 2001 From: mbsantiago Date: Tue, 22 Apr 2025 09:01:58 +0100 Subject: [PATCH] Temporary remove compat params module --- batdetect2/compat/params.py | 304 ++++++++++++++++++------------------ 1 file changed, 152 insertions(+), 152 deletions(-) diff --git a/batdetect2/compat/params.py b/batdetect2/compat/params.py index 14cfdbc..95d1c31 100644 --- a/batdetect2/compat/params.py +++ b/batdetect2/compat/params.py @@ -1,152 +1,152 @@ -from batdetect2.preprocess import ( - AmplitudeScaleConfig, - AudioConfig, - FrequencyConfig, - LogScaleConfig, - PcenConfig, - PreprocessingConfig, - ResampleConfig, - Scales, - SpecSizeConfig, - SpectrogramConfig, - STFTConfig, -) -from batdetect2.preprocess.spectrogram import get_spectrogram_resolution -from batdetect2.targets import ( - LabelConfig, - TagInfo, - TargetConfig, -) -from batdetect2.train.preprocess import ( - TrainPreprocessingConfig, -) - - -def get_spectrogram_scale(scale: str) -> Scales: - if scale == "pcen": - return PcenConfig() - if scale == "log": - return LogScaleConfig() - return AmplitudeScaleConfig() - - -def get_preprocessing_config(params: dict) -> PreprocessingConfig: - return PreprocessingConfig( - audio=AudioConfig( - resample=ResampleConfig( - samplerate=params["target_samp_rate"], - method="poly", - ), - scale=params["scale_raw_audio"], - center=params["scale_raw_audio"], - duration=None, - ), - spectrogram=SpectrogramConfig( - stft=STFTConfig( - window_duration=params["fft_win_length"], - window_overlap=params["fft_overlap"], - window_fn="hann", - ), - frequencies=FrequencyConfig( - min_freq=params["min_freq"], - max_freq=params["max_freq"], - ), - scale=get_spectrogram_scale(params["spec_scale"]), - spectral_mean_substraction=params["denoise_spec_avg"], - size=SpecSizeConfig( - height=params["spec_height"], - resize_factor=params["resize_factor"], - ), - peak_normalize=params["max_scale_spec"], - ), - ) - - -def get_training_preprocessing_config( - params: dict, -) -> TrainPreprocessingConfig: - generic = params["generic_class"][0] - preprocessing = get_preprocessing_config(params) - - freq_bin_width, time_bin_width = get_spectrogram_resolution( - preprocessing.spectrogram - ) - - return TrainPreprocessingConfig( - preprocessing=preprocessing, - target=TargetConfig( - classes=[ - TagInfo(key="class", value=class_name) - for class_name in params["class_names"] - ], - generic_class=TagInfo( - key="class", - value=generic, - ), - include=[ - TagInfo(key="event", value=event) - for event in params["events_of_interest"] - ], - exclude=[ - TagInfo(key="class", value=value) - for value in params["classes_to_ignore"] - ], - ), - labels=LabelConfig( - position="bottom-left", - time_scale=1 / time_bin_width, - frequency_scale=1 / freq_bin_width, - sigma=params["target_sigma"], - ), - ) - - -# 'standardize_classs_names_ip', -# 'convert_to_genus', -# 'genus_mapping', -# 'standardize_classs_names', -# 'genus_names', - -# ['data_dir', -# 'ann_dir', -# 'train_split', -# 'model_name', -# 'num_filters', -# 'experiment', -# 'model_file_name', -# 'op_im_dir', -# 'op_im_dir_test', -# 'notes', -# 'spec_divide_factor', -# 'detection_overlap', -# 'ignore_start_end', -# 'detection_threshold', -# 'nms_kernel_size', -# 'nms_top_k_per_sec', -# 'aug_prob', -# 'augment_at_train', -# 'augment_at_train_combine', -# 'echo_max_delay', -# 'stretch_squeeze_delta', -# 'mask_max_time_perc', -# 'mask_max_freq_perc', -# 'spec_amp_scaling', -# 'aug_sampling_rates', -# 'train_loss', -# 'det_loss_weight', -# 'size_loss_weight', -# 'class_loss_weight', -# 'individual_loss_weight', -# 'emb_dim', -# 'lr', -# 'batch_size', -# 'num_workers', -# 'num_epochs', -# 'num_eval_epochs', -# 'device', -# 'save_test_image_during_train', -# 'save_test_image_after_train', -# 'train_sets', -# 'test_sets', -# 'class_inv_freq', -# 'ip_height'] +# from batdetect2.preprocess import ( +# AmplitudeScaleConfig, +# AudioConfig, +# FrequencyConfig, +# LogScaleConfig, +# PcenConfig, +# PreprocessingConfig, +# ResampleConfig, +# Scales, +# SpecSizeConfig, +# SpectrogramConfig, +# STFTConfig, +# ) +# from batdetect2.preprocess.spectrogram import get_spectrogram_resolution +# from batdetect2.targets import ( +# LabelConfig, +# TagInfo, +# TargetConfig, +# ) +# from batdetect2.train.preprocess import ( +# TrainPreprocessingConfig, +# ) +# +# +# def get_spectrogram_scale(scale: str) -> Scales: +# if scale == "pcen": +# return PcenConfig() +# if scale == "log": +# return LogScaleConfig() +# return AmplitudeScaleConfig() +# +# +# def get_preprocessing_config(params: dict) -> PreprocessingConfig: +# return PreprocessingConfig( +# audio=AudioConfig( +# resample=ResampleConfig( +# samplerate=params["target_samp_rate"], +# method="poly", +# ), +# scale=params["scale_raw_audio"], +# center=params["scale_raw_audio"], +# duration=None, +# ), +# spectrogram=SpectrogramConfig( +# stft=STFTConfig( +# window_duration=params["fft_win_length"], +# window_overlap=params["fft_overlap"], +# window_fn="hann", +# ), +# frequencies=FrequencyConfig( +# min_freq=params["min_freq"], +# max_freq=params["max_freq"], +# ), +# scale=get_spectrogram_scale(params["spec_scale"]), +# spectral_mean_substraction=params["denoise_spec_avg"], +# size=SpecSizeConfig( +# height=params["spec_height"], +# resize_factor=params["resize_factor"], +# ), +# peak_normalize=params["max_scale_spec"], +# ), +# ) +# +# +# def get_training_preprocessing_config( +# params: dict, +# ) -> TrainPreprocessingConfig: +# generic = params["generic_class"][0] +# preprocessing = get_preprocessing_config(params) +# +# freq_bin_width, time_bin_width = get_spectrogram_resolution( +# preprocessing.spectrogram +# ) +# +# return TrainPreprocessingConfig( +# preprocessing=preprocessing, +# target=TargetConfig( +# classes=[ +# TagInfo(key="class", value=class_name) +# for class_name in params["class_names"] +# ], +# generic_class=TagInfo( +# key="class", +# value=generic, +# ), +# include=[ +# TagInfo(key="event", value=event) +# for event in params["events_of_interest"] +# ], +# exclude=[ +# TagInfo(key="class", value=value) +# for value in params["classes_to_ignore"] +# ], +# ), +# labels=LabelConfig( +# position="bottom-left", +# time_scale=1 / time_bin_width, +# frequency_scale=1 / freq_bin_width, +# sigma=params["target_sigma"], +# ), +# ) +# +# +# # 'standardize_classs_names_ip', +# # 'convert_to_genus', +# # 'genus_mapping', +# # 'standardize_classs_names', +# # 'genus_names', +# +# # ['data_dir', +# # 'ann_dir', +# # 'train_split', +# # 'model_name', +# # 'num_filters', +# # 'experiment', +# # 'model_file_name', +# # 'op_im_dir', +# # 'op_im_dir_test', +# # 'notes', +# # 'spec_divide_factor', +# # 'detection_overlap', +# # 'ignore_start_end', +# # 'detection_threshold', +# # 'nms_kernel_size', +# # 'nms_top_k_per_sec', +# # 'aug_prob', +# # 'augment_at_train', +# # 'augment_at_train_combine', +# # 'echo_max_delay', +# # 'stretch_squeeze_delta', +# # 'mask_max_time_perc', +# # 'mask_max_freq_perc', +# # 'spec_amp_scaling', +# # 'aug_sampling_rates', +# # 'train_loss', +# # 'det_loss_weight', +# # 'size_loss_weight', +# # 'class_loss_weight', +# # 'individual_loss_weight', +# # 'emb_dim', +# # 'lr', +# # 'batch_size', +# # 'num_workers', +# # 'num_epochs', +# # 'num_eval_epochs', +# # 'device', +# # 'save_test_image_during_train', +# # 'save_test_image_after_train', +# # 'train_sets', +# # 'test_sets', +# # 'class_inv_freq', +# # 'ip_height']