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Introductory python tutorials for image processing

https://www.youtube.com/playlist?list=PLHae9ggVvqPgyRQQOtENr6hK0m1UquGaG

These video tutorials are designed to train absolute beginners on Python coding with a special emphasis on image analysis.

Coding enables researchers to ...

extend the capability of scientific software packages
customize applications for specific jobs to be done
automate rudimentary tasks freeing up valuable research time
improve reproducibility of experiments via automation
add an important skill to their portfolio making them well adjusted to the digital world

It is recommended to follow the videos as a course as we've structured them to progressively cover topics from basics of python to advanced libraries for image analysis.

Relevant links:To download Anaconda:https://www.anaconda.com/distribution/

To download ZEN Lite:https://www.zeiss.com/microscopy/us/products/microscope-software/zen-lite.html(If you're from outside US, please Google search for 'ZEN Lite' to find your local download link)

To sign up for APEER account:www.apeer.com

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Introductory python tutorials for image processing

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Name		Name	Last commit message	Last commit date
Latest commit History 47 Commits
generating_labeled_data_for_deep_learning		generating_labeled_data_for_deep_learning
README.md		README.md
YR1_hough_transform.py		YR1_hough_transform.py
YR2_batch_processing_multiple_images_in_python.py		YR2_batch_processing_multiple_images_in_python.py
tutorial04_appreciating the simplicity of python.py		tutorial04_appreciating the simplicity of python.py
tutorial09_top5_libraries.py		tutorial09_top5_libraries.py
tutorial101_DL_terminology_training_and_valid_curves.ipynb		tutorial101_DL_terminology_training_and_valid_curves.ipynb
tutorial102_DL_terminology_training_testing_validation_data.ipynb		tutorial102_DL_terminology_training_testing_validation_data.ipynb
tutorial103_DL_terminology_data_augmentation1.ipynb		tutorial103_DL_terminology_data_augmentation1.ipynb
tutorial103_DL_terminology_data_augmentation2.ipynb		tutorial103_DL_terminology_data_augmentation2.ipynb
tutorial104_DL_terminology_callbacks_checkpoints_earlystopping.ipynb		tutorial104_DL_terminology_callbacks_checkpoints_earlystopping.ipynb
tutorial105_DL_terminology_Learning_rate_scheduling.ipynb		tutorial105_DL_terminology_Learning_rate_scheduling.ipynb
tutorial107_7_steps_to_DL.ipynb		tutorial107_7_steps_to_DL.ipynb
tutorial109_regression_housing.ipynb		tutorial109_regression_housing.ipynb
tutorial10_first_lines_of_code.py		tutorial10_first_lines_of_code.py
tutorial110_binary_classification_malaria.ipynb		tutorial110_binary_classification_malaria.ipynb
tutorial11_operators_basic_math.py		tutorial11_operators_basic_math.py
tutorial12_lists.py		tutorial12_lists.py
tutorial13_tuples.py		tutorial13_tuples.py
tutorial14_dictionaries.py		tutorial14_dictionaries.py
tutorial15_numpy_arrays.py		tutorial15_numpy_arrays.py
tutorial16_data_types_in_python.py		tutorial16_data_types_in_python.py
tutorial17_if_else_statements.py		tutorial17_if_else_statements.py
tutorial18_automating_using_while_loops.py		tutorial18_automating_using_while_loops.py
tutorial19_automating_using_for_loops.py		tutorial19_automating_using_for_loops.py
tutorial20_functions.py		tutorial20_functions.py
tutorial21_lambda_functions.py		tutorial21_lambda_functions.py
tutorial22_reading_images_into_python.py		tutorial22_reading_images_into_python.py
tutorial23_reading_proprietary_images_into_python.py		tutorial23_reading_proprietary_images_into_python.py
tutorial24_saving_images_in_python.py		tutorial24_saving_images_in_python.py
tutorial25_viewing_images_in_python.py		tutorial25_viewing_images_in_python.py
tutorial26_plotting_using_pyplots_python.py		tutorial26_plotting_using_pyplots_python.py
tutorial27_using_glob_to_read_multiple_images.py		tutorial27_using_glob_to_read_multiple_images.py
tutorial28_using_os.listdir_to_read_multiple_images.py		tutorial28_using_os.listdir_to_read_multiple_images.py
tutorial29_image_processing_using_scikit-image.py		tutorial29_image_processing_using_scikit-image.py
tutorial30_image_processing_using_opencv.py		tutorial30_image_processing_using_opencv.py
tutorial31_image_sharpening_using_unsharp_mask.py		tutorial31_image_sharpening_using_unsharp_mask.py
tutorial32_denoising_using_gaussian.py		tutorial32_denoising_using_gaussian.py
tutorial33_denoising_using_median.py		tutorial33_denoising_using_median.py
tutorial34_denoising_using_bilateral.py		tutorial34_denoising_using_bilateral.py
tutorial35_denoising_using_NLM.py		tutorial35_denoising_using_NLM.py
tutorial36_denoising_using_total_variance.py		tutorial36_denoising_using_total_variance.py
tutorial37_denoising_using_BM3D.py		tutorial37_denoising_using_BM3D.py
tutorial38_edge_detection_filters.py		tutorial38_edge_detection_filters.py
tutorial39_edge_detection_using_canny.py		tutorial39_edge_detection_using_canny.py
tutorial40_what_is_fourier_transform.py		tutorial40_what_is_fourier_transform.py
tutorial41_image_filters_using_fourier_transform_DFT.py		tutorial41_image_filters_using_fourier_transform_DFT.py
tutorial42_what_is_histogram_equalization_CLAHE.py		tutorial42_what_is_histogram_equalization_CLAHE.py
tutorial43_shading_correction_using_rolling_ball.py		tutorial43_shading_correction_using_rolling_ball.py
tutorial44_a_note_about_color_spaces.py		tutorial44_a_note_about_color_spaces.py
tutorial45_applying_grey_scale_filters_to_color_images.py		tutorial45_applying_grey_scale_filters_to_color_images.py
tutorial46_img_registration_libraries_in_python.py		tutorial46_img_registration_libraries_in_python.py
tutorial47_image_registration_using_pystackreg.py		tutorial47_image_registration_using_pystackreg.py
tutorial48_reference_based_image_quality.py		tutorial48_reference_based_image_quality.py
tutorial49_no_reference_image_quality_sharpness.py		tutorial49_no_reference_image_quality_sharpness.py
tutorial50_no_reference_image_quality_assessment_BRISQUE.py		tutorial50_no_reference_image_quality_assessment_BRISQUE.py
tutorial51_what_is_image_segmentation_and_thresholding.py		tutorial51_what_is_image_segmentation_and_thresholding.py
tutorial52_multi_thresholding_and_morph_operators.py		tutorial52_multi_thresholding_and_morph_operators.py
tutorial53-using_texture_to_segment_images.py		tutorial53-using_texture_to_segment_images.py
tutorial54-scratch_assay_in_python.py		tutorial54-scratch_assay_in_python.py
tutorial55_image_segmentation_followed_by_measurements.py		tutorial55_image_segmentation_followed_by_measurements.py
tutorial56_simple_blob_detector.py		tutorial56_simple_blob_detector.py
tutorial56b_hough_circles.py		tutorial56b_hough_circles.py
tutorial57_Cell Nuclei analysis using watershed.py		tutorial57_Cell Nuclei analysis using watershed.py
tutorial58_object_detection_by_template_matching.py		tutorial58_object_detection_by_template_matching.py
tutorial59_data_analysis_using_Pandas_Intro_data_loading.py		tutorial59_data_analysis_using_Pandas_Intro_data_loading.py
tutorial60_data_analysis_using_Pandas_data_handling.py		tutorial60_data_analysis_using_Pandas_data_handling.py
tutorial61_data_analysis_using_Pandas_data_sorting.py		tutorial61_data_analysis_using_Pandas_data_sorting.py
tutorial62_data_analysis_using_Pandas_data_grouping.py		tutorial62_data_analysis_using_Pandas_data_grouping.py
tutorial63_dealing with null data_in_Pandas.py		tutorial63_dealing with null data_in_Pandas.py
tutorial64_basic_plotting_of_data_from_pandas_dataframe.py		tutorial64_basic_plotting_of_data_from_pandas_dataframe.py
tutorial65_pandas_data_plotting_using_Seaborn.py		tutorial65_pandas_data_plotting_using_Seaborn.py
tutorial66a_need_for_data_normalization.py		tutorial66a_need_for_data_normalization.py
tutorial66b_various_data_normalization_techniques.py		tutorial66b_various_data_normalization_techniques.py
tutorial68-linear_regression.py		tutorial68-linear_regression.py
tutorial69-multi_linear_regression.py		tutorial69-multi_linear_regression.py
tutorial70-Logistic_regression_breast_cancer.py		tutorial70-Logistic_regression_breast_cancer.py
tutorial71-K_means.py		tutorial71-K_means.py
tutorial71a-K_means_demo.py		tutorial71a-K_means_demo.py
tutorial72-GMM_image_segmentation.py		tutorial72-GMM_image_segmentation.py
tutorial74_what is gabor filter.py		tutorial74_what is gabor filter.py
tutorial75-Extracting_features_using_Gabor_Filter.py		tutorial75-Extracting_features_using_Gabor_Filter.py
tutorial76-Random Forest_breast_cancer.py		tutorial76-Random Forest_breast_cancer.py
tutorial77-SVM_breast_cancer.py		tutorial77-SVM_breast_cancer.py
tutorial79_part1_traditional_machine_learning_based_img_segmentation.py		tutorial79_part1_traditional_machine_learning_based_img_segmentation.py
tutorial80_part2_predict_ML_segmentation_All_filters_RForest.py		tutorial80_part2_predict_ML_segmentation_All_filters_RForest.py
tutorial81_part3_Feature_based_segm_RF_multi_image_TRAIN.py		tutorial81_part3_Feature_based_segm_RF_multi_image_TRAIN.py
tutorial83_feature_extraction_RF_classification_V2.0.py		tutorial83_feature_extraction_RF_classification_V2.0.py
tutorial84_IoU.py		tutorial84_IoU.py
tutorial85_working_with_imbalanced_data.py		tutorial85_working_with_imbalanced_data.py
tutorial86_87_PREDICT_img_segm_using_RF_XGB_LGBM.py		tutorial86_87_PREDICT_img_segm_using_RF_XGB_LGBM.py
tutorial86_87_TRAIN_img_segm_using_RF_XGB_LGBM.py		tutorial86_87_TRAIN_img_segm_using_RF_XGB_LGBM.py
tutorial88_BORUTA_for_feature_selection.py		tutorial88_BORUTA_for_feature_selection.py
tutorial91_binary_classification_breast_cancer.ipynb		tutorial91_binary_classification_breast_cancer.ipynb
tutorial93_DL_terminology_scaling.ipynb		tutorial93_DL_terminology_scaling.ipynb
tutorial94_DL_terminology_Activation.ipynb		tutorial94_DL_terminology_Activation.ipynb
tutorial95_DL_terminology_loss_functions.ipynb		tutorial95_DL_terminology_loss_functions.ipynb
tutorial96_DL_terminology_backpropagation_optimizers.ipynb		tutorial96_DL_terminology_backpropagation_optimizers.ipynb
tutorial97_DL_terminology_batch_size_iterations_epochs.ipynb		tutorial97_DL_terminology_batch_size_iterations_epochs.ipynb
tutorial98_99_100_DL_terminology_dropout_batch_norm.ipynb		tutorial98_99_100_DL_terminology_dropout_batch_norm.ipynb

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Introductory python tutorials for image processing

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