Fixes

bat_gui.py

@@ -10,11 +10,11 @@ import segments
 import utils
 import logging
 import librosa
+
 logging.basicConfig(filename='bat_gui.log', encoding='utf-8', level=logging.DEBUG)
 
 _WINDOW: webview.Window
 
-
 _AREA_ONE = "EU"
 _AREA_TWO = "Bavaria"
 _AREA_THREE = "USA"
@@ -28,11 +28,14 @@ OUTPUT_TYPE_MAP = {"Raven selection table": "table", "Audacity": "audacity", "R"
 ORIGINAL_MODEL_PATH = cfg.MODEL_PATH
 ORIGINAL_MDATA_MODEL_PATH = cfg.MDATA_MODEL_PATH
 ORIGINAL_LABELS_FILE = cfg.LABELS_FILE
-ORIGINAL_TRANSLATED_LABELS_PATH = cfg.TRANSLATED_BAT_LABELS_PATH # cfg.TRANSLATED_LABELS_PATH
+ORIGINAL_TRANSLATED_LABELS_PATH = cfg.TRANSLATED_BAT_LABELS_PATH  # cfg.TRANSLATED_LABELS_PATH
+
 
 def analyzeFile_wrapper(entry):
-    #return (entry[0], analyze.analyzeFile(entry))
+    # return (entry[0], analyze.analyzeFile(entry))
     return (entry[0], bat_ident.analyze_file(entry))
+
+
 def validate(value, msg):
     """Checks if the value ist not falsy.
     If the value is falsy, an error will be raised.
@@ -44,41 +47,6 @@ def validate(value, msg):
         raise gr.Error(msg)
 
 
-def runBatchAnalysis(
-    output_path,
-    confidence,
-    sensitivity,
-    overlap,
-    species_list_choice,
-    locale,
-    batch_size,
-    threads,
-    input_dir,
-    output_type_radio,
-    progress=gr.Progress(),
-):
-    validate(input_dir, "Please select a directory.")
-    batch_size = int(batch_size)
-    threads = int(threads)
-
-    return runAnalysis(
-        species_list_choice,
-        None,
-        output_path,
-        confidence,
-        sensitivity,
-        overlap,
-        output_type_radio,
-        "en" if not locale else locale,
-        batch_size,
-        threads,
-        input_dir,
-        progress,
-    )
-
-
-
-
 def runSingleFileAnalysis(input_path,
                           confidence,
                           sensitivity,
@@ -97,24 +65,25 @@ def runSingleFileAnalysis(input_path,
         "csv",
         "en" if not locale else locale,
         1,
-        4,
+        1,
         None,
         progress=None,
     )
 
+
 def runAnalysis(
-    species_list_choice: str,
-    input_path: str,
-    output_path: str | None,
-    confidence: float,
-    sensitivity: float,
-    overlap: float,
-    output_type: str,
-    locale: str,
-    batch_size: int,
-    threads: int,
-    input_dir: str,
-    progress: gr.Progress | None,
+        species_list_choice: str,
+        input_path: str,
+        output_path: str or None,
+        confidence: float,
+        sensitivity: float,
+        overlap: float,
+        output_type: str,
+        locale: str,
+        batch_size: int,
+        threads: int,
+        input_dir: str,
+        progress: gr.Progress or None,
 ):
     """Starts the analysis.
     Args:
@@ -143,7 +112,7 @@ def runAnalysis(
         progress(0, desc="Preparing ...")
     # locale = locale.lower()
     # Load eBird codes, labels
-    #cfg.CODES = analyze.loadCodes()
+    # cfg.CODES = analyze.loadCodes()
     # cfg.LABELS = utils.readLines(ORIGINAL_LABELS_FILE)
     cfg.LATITUDE, cfg.LONGITUDE, cfg.WEEK = -1, -1, -1
     cfg.LOCATION_FILTER_THRESHOLD = 0.03
@@ -282,10 +251,13 @@ def runAnalysis(
                     progress((i, len(flist)), total=len(flist), unit="files")
                 result = f.result()
                 result_list.append(result)
-    return [[os.path.relpath(r[0], input_dir), r[1]] for r in result_list] if input_dir else cfg.OUTPUT_PATH
+    return [[os.path.relpath(r[0], input_dir), r[1]] for r in result_list] if input_dir else cfg.OUTPUT_PATH + "Results.csv"
+
 
 def extractSegments_wrapper(entry):
     return (entry[0][0], segments.extractSegments(entry))
+
+
 def extract_segments(audio_dir, result_dir, output_dir, min_conf, num_seq, seq_length, threads, progress=gr.Progress()):
     validate(audio_dir, "No audio directory selected")
 
@@ -298,7 +270,6 @@ def extract_segments(audio_dir, result_dir, output_dir, min_conf, num_seq, seq_l
     if progress is not None:
         progress(0, desc="Searching files ...")
 
-
     # Parse audio and result folders
     cfg.FILE_LIST = segments.parseFolders(audio_dir, result_dir)
 
@@ -353,6 +324,7 @@ def select_file(filetypes=()):
     files = _WINDOW.create_file_dialog(webview.OPEN_DIALOG, file_types=filetypes)
     return files[0] if files else None
 
+
 def format_seconds(secs: float):
     """Formats a number of seconds into a string.
 
@@ -369,6 +341,7 @@ def format_seconds(secs: float):
 
     return "{:2.0f}:{:02.0f}:{:06.3f}".format(hours, minutes, secs)
 
+
 def select_directory(collect_files=True):
     """Shows a directory selection system dialog.
 
@@ -417,10 +390,6 @@ def show_species_choice(choice: str):
     ]
 
 
-
-
-
-
 #
 # VIEW - This is where the UI elements are defined
 #
@@ -436,7 +405,8 @@ def sample_sliders(opened=True):
     with gr.Accordion("Inference settings", open=opened):
         with gr.Row():
             confidence_slider = gr.Slider(
-                minimum=0, maximum=1, value=0.5, step=0.01, label="Minimum Confidence", info="Minimum confidence threshold."
+                minimum=0, maximum=1, value=0.5, step=0.01, label="Minimum Confidence",
+                info="Minimum confidence threshold."
             )
             sensitivity_slider = gr.Slider(
                 minimum=0.5,
@@ -452,6 +422,7 @@ def sample_sliders(opened=True):
 
     return confidence_slider, sensitivity_slider, overlap_slider
 
+
 def locale():
     """Creates the gradio elements for locale selection
     Reads the translated labels inside the checkpoints directory.
@@ -461,7 +432,9 @@ def locale():
     label_files = os.listdir(os.path.join(os.path.dirname(sys.argv[0]), ORIGINAL_TRANSLATED_LABELS_PATH))
     options = ["EN"] + [label_file.rsplit("_", 1)[-1].split(".")[0].upper() for label_file in label_files]
 
-    return gr.Dropdown(options, value="EN", label="Locale", info="Locale for the translated species common names.",visible=False)
+    return gr.Dropdown(options, value="EN", label="Locale", info="Locale for the translated species common names.",
+                       visible=False)
+
 
 def species_lists(opened=True):
     """Creates the gradio accordion for species selection.
@@ -489,6 +462,7 @@ def species_lists(opened=True):
             #
     return species_list_radio
 
+
 #
 # Design main frame for analysis of a single file
 #
@@ -520,158 +494,12 @@ def build_single_analysis_tab():
                                   )
 
 
-def build_multi_analysis_tab():
-    with gr.Tab("Multiple files"):
-        input_directory_state = gr.State()
-        output_directory_predict_state = gr.State()
-        with gr.Row():
-            with gr.Column():
-                select_directory_btn = gr.Button("Select directory (recursive)")
-                directory_input = gr.Matrix(interactive=False, elem_classes="mh-200", headers=["Subpath", "Length"])
-
-                def select_directory_on_empty():
-                    res = select_directory()
-
-                    return res if res[1] else [res[0], [["No files found"]]]
-
-                select_directory_btn.click(
-                    select_directory_on_empty, outputs=[input_directory_state, directory_input], show_progress=True
-                )
-
-            with gr.Column():
-                select_out_directory_btn = gr.Button("Select output directory.")
-                selected_out_textbox = gr.Textbox(
-                    label="Output directory",
-                    interactive=False,
-                    placeholder="If not selected, the input directory will be used.",
-                )
-
-                def select_directory_wrapper():
-                    return (select_directory(collect_files=False),) * 2
-
-                select_out_directory_btn.click(
-                    select_directory_wrapper,
-                    outputs=[output_directory_predict_state, selected_out_textbox],
-                    show_progress=False,
-                )
-
-        confidence_slider, sensitivity_slider, overlap_slider = sample_sliders()
-        species_list_radio = species_lists(False)
-
-        output_type_radio = gr.Radio(
-            list(OUTPUT_TYPE_MAP.keys()),
-            value="Raven selection table",
-            label="Result type",
-            info="Specifies output format.",
-        )
-
-        with gr.Row():
-            batch_size_number = gr.Number(
-                precision=1, label="Batch size", value=1, info="Number of samples to process at the same time."
-            )
-            threads_number = gr.Number(precision=1, label="Threads", value=4, info="Number of CPU threads.")
-
-        locale_radio = locale()
-
-        start_batch_analysis_btn = gr.Button("Analyze")
-
-        result_grid = gr.Matrix(headers=["File", "Execution"], elem_classes="mh-200")
-
-        inputs = [
-            output_directory_predict_state,
-            confidence_slider,
-            sensitivity_slider,
-            overlap_slider,
-            species_list_radio,
-            locale_radio,
-            batch_size_number,
-            threads_number,
-            input_directory_state,
-            output_type_radio
-        ]
-
-        start_batch_analysis_btn.click(runBatchAnalysis, inputs=inputs, outputs=result_grid)
-
-def build_segments_tab():
-    with gr.Tab("Segments"):
-        audio_directory_state = gr.State()
-        result_directory_state = gr.State()
-        output_directory_state = gr.State()
-
-        def select_directory_to_state_and_tb():
-            return (select_directory(collect_files=False),) * 2
-
-        with gr.Row():
-            select_audio_directory_btn = gr.Button("Select audio directory (recursive)")
-            selected_audio_directory_tb = gr.Textbox(show_label=False, interactive=False)
-            select_audio_directory_btn.click(
-                select_directory_to_state_and_tb,
-                outputs=[selected_audio_directory_tb, audio_directory_state],
-                show_progress=False,
-            )
-
-        with gr.Row():
-            select_result_directory_btn = gr.Button("Select result directory")
-            selected_result_directory_tb = gr.Textbox(
-                show_label=False, interactive=False, placeholder="Same as audio directory if not selected"
-            )
-            select_result_directory_btn.click(
-                select_directory_to_state_and_tb,
-                outputs=[result_directory_state, selected_result_directory_tb],
-                show_progress=False,
-            )
-
-        with gr.Row():
-            select_output_directory_btn = gr.Button("Select output directory")
-            selected_output_directory_tb = gr.Textbox(
-                show_label=False, interactive=False, placeholder="Same as audio directory if not selected"
-            )
-            select_output_directory_btn.click(
-                select_directory_to_state_and_tb,
-                outputs=[selected_output_directory_tb, output_directory_state],
-                show_progress=False,
-            )
-
-        min_conf_slider = gr.Slider(
-            minimum=0.1, maximum=0.99, step=0.01, label="Minimum confidence", info="Minimum confidence threshold."
-        )
-        num_seq_number = gr.Number(
-            100, label="Max number of segments", info="Maximum number of randomly extracted segments per species."
-        )
-        seq_length_number = gr.Number(3.0, label="Sequence length", info="Length of extracted segments in seconds.")
-        threads_number = gr.Number(4, label="Threads", info="Number of CPU threads.")
-
-        extract_segments_btn = gr.Button("Extract segments")
-
-        result_grid = gr.Matrix(headers=["File", "Execution"], elem_classes="mh-200")
-
-        extract_segments_btn.click(
-            extract_segments,
-            inputs=[
-                audio_directory_state,
-                result_directory_state,
-                output_directory_state,
-                min_conf_slider,
-                num_seq_number,
-                seq_length_number,
-                threads_number,
-            ],
-            outputs=result_grid,
-        )
-
 if __name__ == "__main__":
     freeze_support()
     with gr.Blocks(
-        css=r".d-block .wrap {display: block !important;} .mh-200 {max-height: 300px; overflow-y: auto !important;} footer {display: none !important;} #single_file_audio, #single_file_audio * {max-height: 81.6px; min-height: 0;}",
-        theme=gr.themes.Default(),
-        analytics_enabled=False,
+            css=r".d-block .wrap {display: block !important;} .mh-200 {max-height: 300px; overflow-y: auto !important;} footer {display: none !important;} #single_file_audio, #single_file_audio * {max-height: 81.6px; min-height: 0;}",
+            theme=gr.themes.Default(),
+            analytics_enabled=False,
     ) as demo:
         build_single_analysis_tab()
-        # build_multi_analysis_tab()
-        # build_segments_tab()
         demo.launch()
-
-    #url = demo.queue(api_open=False).launch(prevent_thread_lock=True, quiet=True)[1]
-    #_WINDOW = webview.create_window("BattyBirdNET-Analyzer", url.rstrip("/") +
-    #                                "?__theme=light", min_size=(1024, 768))
-    # webview.start(private_mode=False)

bat_ident.py

@@ -331,7 +331,6 @@ def analyze_file(item):
         with open(cfg.OUTPUT_PATH + "Results.csv", "a", encoding="utf-8") as rfile:
             postString = out_string.split("\n", 1)[1]
             # rfile.write(fpath.join(postString.splitlines(True)))
-            rfile.write("\n"+fpath+"\n")
             rfile.write(postString)
 
     except Exception as ex: