add new versions of classifier models for the shoreline segmentation …

…filters and image filters

run_image_classifier.py

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+from coastseg import classifier
+import os
+
+input_path =r'C:\development\doodleverse\coastseg\CoastSeg\data\ID_1_datetime06-04-24__12_09_54\jpg_files\preprocessed\RGB'
+output_path = input_path
+output_csv=os.path.join(input_path,'classification_results.csv')
+
+# classifier_path = classifier.get_image_classifier('RGB')
+classifier_path = classifier.get_image_classifier('rgb')
+print(f"Classifier path: {classifier_path}")
+classifier.run_inference_rgb_image_classifier(classifier_path,
+                input_path,
+                output_path,
+                output_csv,
+                threshold=0.40)
+
+# try the gray
+# classifier_path = classifier.get_image_classifier('gray')
+# print(f"Classifier path: {classifier_path}")
+# classifier.run_inference_gray_image_classifier(classifier_path,
+#                 input_path,
+#                 output_path,
+#                 output_csv,
+#                 threshold=0.40)
+
+
+
+
+# apply good bad classifier to the downloaded imagery
+# for key in roi_settings.keys():
+#     data_path = os.path.join(roi_settings[key]['filepath'],roi_settings[key]['sitename'])
+#     RGB_path = os.path.join(data_path,'jpg_files','preprocessed','RGB')
+#     print(f"Sorting images in {RGB_path}")
+#     input_path =RGB_path
+#     output_path = RGB_path
+#     output_csv=os.path.join(RGB_path,'classification_results.csv')
+#     # model_path = os.path.join(r'C:\development\doodleverse\coastseg\CoastSeg\src\coastseg\classifier_model','best.h5')
+#     model_path = classifier.get_classifier()
+#     classifier.run_inference(model_path,
+#                 input_path,
+#                 output_path,
+#                 output_csv,
+#                 threshold=0.10)

run_shoreline_segmentation_classifier.py

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+from coastseg import classifier
+import os
+
+input_path =r'C:\development\doodleverse\coastseg\CoastSeg\sessions\coreg_session2\good'
+output_path = input_path
+output_csv=os.path.join(input_path,'classification_results.csv')
+
+segmentation_classifier = classifier.get_segmentation_classifier()
+classifier.run_inference_segmentation_classifier(segmentation_classifier,
+                input_path,
+                output_path,
+                output_csv,
+                threshold=0.40)
+
+
+
+# apply good bad classifier to the downloaded imagery
+# for key in roi_settings.keys():
+#     data_path = os.path.join(roi_settings[key]['filepath'],roi_settings[key]['sitename'])
+#     RGB_path = os.path.join(data_path,'jpg_files','preprocessed','RGB')
+#     print(f"Sorting images in {RGB_path}")
+#     input_path =RGB_path
+#     output_path = RGB_path
+#     output_csv=os.path.join(RGB_path,'classification_results.csv')
+#     # model_path = os.path.join(r'C:\development\doodleverse\coastseg\CoastSeg\src\coastseg\classifier_model','best.h5')
+#     model_path = classifier.get_classifier()
+#     classifier.run_inference(model_path,
+#                 input_path,
+#                 output_path,
+#                 output_csv,
+#                 threshold=0.10)