cleanX.image_work package¶
Submodules¶
- cleanX.image_work.image_functions module
Cv2Errorcv2_imread()crop_np()crop_np_white()find_outliers_sum_of_pixels_across_set()hist_sum_of_pixels_across_set()crop()subtle_sharpie_enhance()harsh_sharpie_enhance()salting()simple_rotate_no_pil()blur_out_edges()multi_rotation_augmentation_no_pill()show_major_lines_on_image()find_big_lines()separate_image_averager()dimensions_to_df()dimensions_to_histo()proportions_ht_wt_to_histo()find_very_hazy()find_by_sample_upper()find_sample_upper_greater_than_lower()find_outliers_by_total_mean()find_outliers_by_mean_to_df()create_matrix()find_tiny_image_differences()tesseract_specific()find_suspect_text()find_suspect_text_by_length()histogram_difference_for_inverts()inverts_by_sum_compare()histogram_difference_for_inverts_todf()find_duplicated_images()find_duplicated_images_todf()show_images_in_df()dataframe_up_my_pics()Rotatorsimple_spinning_template()make_contour_image()avg_image_maker()set_image_variability()avg_image_maker_by_label()zero_to_twofivefive_simplest_norming()rescale_range_from_histogram_low_end()make_histo_scaled_folder()give_size_count_df()give_size_counted_dfs()image_quality_by_size()find_close_images()show_close_images()image_to_histo()black_end_ratio()outline_segment_by_otsu()binarize_by_otsu()column_sum_folder()blind_quality_matrix()fourier_transf()pad_to_size()cut_to_size()cut_or_pad()rotated_with_max_clean_area()noise_sum_cv()noise_sum_median_blur()noise_sum_gaussian()noise_sum_bilateral()noise_sum_bilateralLO()noise_sum_5k()noise_sum_7k()blind_noise_matrix()segmented_blind_noise_matrix()make_inverted()cv2_phash_for_dupes()
- cleanX.image_work.journaling_pipeline module
- cleanX.image_work.pipeline module
- cleanX.image_work.steps module
get_known_steps()RegisteredStepStepAggregateMeanGroupHistoHtWtGroupHistoHtWt.__init__()GroupHistoHtWt.agg()GroupHistoHtWt.post()GroupHistoHtWt.__reduce__()GroupHistoHtWt.aggregate()GroupHistoHtWt.apply()GroupHistoHtWt.begin_transaction()GroupHistoHtWt.commit_transaction()GroupHistoHtWt.from_cmd_args()GroupHistoHtWt.pre()GroupHistoHtWt.read()GroupHistoHtWt.to_json()GroupHistoHtWt.write()
GroupHistoPorportionGroupHistoPorportion.__init__()GroupHistoPorportion.agg()GroupHistoPorportion.post()GroupHistoPorportion.__reduce__()GroupHistoPorportion.aggregate()GroupHistoPorportion.apply()GroupHistoPorportion.begin_transaction()GroupHistoPorportion.commit_transaction()GroupHistoPorportion.from_cmd_args()GroupHistoPorportion.pre()GroupHistoPorportion.read()GroupHistoPorportion.to_json()GroupHistoPorportion.write()
AcquireSaveFourierTransfContourImageProjectionHorizoVertProjectionHorizoVert.apply()ProjectionHorizoVert.__init__()ProjectionHorizoVert.__reduce__()ProjectionHorizoVert.begin_transaction()ProjectionHorizoVert.commit_transaction()ProjectionHorizoVert.from_cmd_args()ProjectionHorizoVert.read()ProjectionHorizoVert.to_json()ProjectionHorizoVert.write()
BlackEdgeCropWhiteEdgeCropSharpieBlurEdgesCleanRotateNormalizeHistogramNormalizeInvertImagesOtsuBinarizeOtsuLinesProjection
Module contents¶
- cleanX.image_work.create_pipeline(steps, batch_size=None, journal=None, keep_journal=False)¶
Create a pipeline that will execute the
steps. Ifjournalis not false, create a journaling pipeline, that can be pick up from the failed step.- Parameters:
steps (Sequence[Step]) – A sequence of
Stepto be executed in this pipeline.batch_size (int) – Controls how many steps are processed concurrently.
journal (Union[bool, str]) – If
Trueis passed, the pipeline code will use a preconfigured directory to store the journal. Otherwise, this must be the path to the directory to store the journal database.keep_journal (bool) – Controls whether the journal is kept after successful completion of the pipeline.
- Returns:
a
Pipelineobject or one of its descendants.- Return type:
- cleanX.image_work.restore_pipeline(journal_dir, skip=0, **overrides)¶
Restores previously interrupted pipeline. The pipeline should have been created with
journalset. If the creating code didn’t specify the directory to keep the journal, it may be obtained in this way:p = create_pipeline(steps=(...), journal=True) journal_dir = p.journal_dir # After pipeline failed p = restore_pipeline(journal_dir)
- Parameters:
journal_dir (Suitable for
os.path.join()) – The directory containing journal database to restore from.skip – Skip this many steps before attempting to resume the pipeline. This is useful if you know that the step that failed will fail again, but you want to execute the rest of the steps in the pipeline.
**overrides – Arguments to pass to the created pipeline instance that will override those restored from the journal.
- Returns:
Fresh
JournalingPipelineobject fast-forwarded to the last executed step +skip.- Return type: