From 6a5a95e84e79bb30ca9a24afd2644c1a32a940b5 Mon Sep 17 00:00:00 2001
From: Jason Parham <jason.parham@kitware.com>
Date: Thu, 29 Jan 2026 15:02:40 -0800
Subject: [PATCH 1/2] Added new mask and masked output image

---
 batbot/spectrogram/__init__.py | 24 ++++++++++++++++++++++++
 setup.cfg                      |  2 +-
 2 files changed, 25 insertions(+), 1 deletion(-)

diff --git a/batbot/spectrogram/__init__.py b/batbot/spectrogram/__init__.py
index 99fb956..1d73798 100644
--- a/batbot/spectrogram/__init__.py
+++ b/batbot/spectrogram/__init__.py
@@ -1823,6 +1823,8 @@ def compute_wrapper(
 
     output_paths = []
     compressed_paths = []
+    mask_paths = []
+    masked_paths = []
     if not fast_mode:
         datas = [
             (output_paths, 'jpg', stft_db),
@@ -1834,6 +1836,24 @@ def compute_wrapper(
             (compressed_paths, 'compressed.jpg', segments['stft_db']),
         ]
 
+    # Create masked image
+    weights = segments['costs'].copy()
+    weights[weights < weights.mean()] = 0
+    weights[weights > 0] = weights.max()
+    weights = weights.astype(np.float32)
+    kernel = 11
+    weights = cv2.GaussianBlur(
+        weights, (kernel, kernel), sigmaX=4, sigmaY=4, borderType=cv2.BORDER_DEFAULT
+    )
+    weights /= weights.max()
+    masked = segments['stft_db'] * weights
+    masked = normalize_stft(masked, None, np.uint8)
+
+    datas += [
+        (mask_paths, 'mask.jpg', segments['costs']),
+        (masked_paths, 'masked.jpg', masked),
+    ]
+
     for accumulator, tag, data in datas:
         if data.dtype != np.uint8:
             data_ = data.astype(np.float32)
@@ -1863,6 +1883,8 @@ def compute_wrapper(
         'spectrogram': {
             'uncompressed.path': output_paths,
             'compressed.path': compressed_paths,
+            'mask.path': mask_paths,
+            'masked.path': masked_paths,
         },
         'global_threshold.amp': int(round(255.0 * (global_threshold / max_value))),
         'sr.hz': int(sr),
@@ -1886,6 +1908,8 @@ def compute_wrapper(
             'width.px': segments['stft_db'].shape[1],
             'height.px': segments['stft_db'].shape[0],
         }
+    metadata['size']['mask'] = metadata['size']['compressed']
+    metadata['size']['masked'] = metadata['size']['compressed']
 
     metadata_path = f'{out_file_stem}.metadata.json'
     with open(metadata_path, 'w') as metafile:
diff --git a/setup.cfg b/setup.cfg
index d73eb80..3cf199b 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -38,7 +38,7 @@ python_requires = >=3.7
 
 [options.entry_points]
 console_scripts =
-    batbot = batbot.batbot:cli
+    batbot = batbot.batbot_cli:cli
 
 [tool:pytest]
 minversion = 5.4

From a2ec4900a11602fbdfaec2c6be4ceee30c147934 Mon Sep 17 00:00:00 2001
From: "trevor.stout" <trevor.stout@kitware.com>
Date: Wed, 4 Feb 2026 15:17:14 -0500
Subject: [PATCH 2/2] Mask creation now conditional to support fast mode

---
 batbot/spectrogram/__init__.py | 41 +++++++++++++++++++---------------
 1 file changed, 23 insertions(+), 18 deletions(-)

diff --git a/batbot/spectrogram/__init__.py b/batbot/spectrogram/__init__.py
index 1d73798..8b94716 100644
--- a/batbot/spectrogram/__init__.py
+++ b/batbot/spectrogram/__init__.py
@@ -1380,6 +1380,20 @@ def calculate_harmonic_and_echo_flags(
     return harmonic_flag, harmonic_peak, echo_flag, echo_peak
 
 
+def create_masked_image(stft_db, costs, kernel=11):
+    weights = costs.copy()
+    weights[weights < weights.mean()] = 0
+    weights[weights > 0] = weights.max()
+    weights = weights.astype(np.float32)
+    weights = cv2.GaussianBlur(
+        weights, (kernel, kernel), sigmaX=4, sigmaY=4, borderType=cv2.BORDER_DEFAULT
+    )
+    weights /= weights.max()
+    masked = stft_db * weights
+    masked = normalize_stft(masked, None, np.uint8)
+    return masked
+
+
 # @lp
 def compute_wrapper(
     wav_filepath,
@@ -1837,22 +1851,12 @@ def compute_wrapper(
         ]
 
     # Create masked image
-    weights = segments['costs'].copy()
-    weights[weights < weights.mean()] = 0
-    weights[weights > 0] = weights.max()
-    weights = weights.astype(np.float32)
-    kernel = 11
-    weights = cv2.GaussianBlur(
-        weights, (kernel, kernel), sigmaX=4, sigmaY=4, borderType=cv2.BORDER_DEFAULT
-    )
-    weights /= weights.max()
-    masked = segments['stft_db'] * weights
-    masked = normalize_stft(masked, None, np.uint8)
-
-    datas += [
-        (mask_paths, 'mask.jpg', segments['costs']),
-        (masked_paths, 'masked.jpg', masked),
-    ]
+    if 'costs' in segments and 'stft_db' in segments:
+        masked = create_masked_image(segments['stft_db'], segments['costs'])
+        datas += [
+            (mask_paths, 'mask.jpg', segments['costs']),
+            (masked_paths, 'masked.jpg', masked),
+        ]
 
     for accumulator, tag, data in datas:
         if data.dtype != np.uint8:
@@ -1908,8 +1912,9 @@ def compute_wrapper(
             'width.px': segments['stft_db'].shape[1],
             'height.px': segments['stft_db'].shape[0],
         }
-    metadata['size']['mask'] = metadata['size']['compressed']
-    metadata['size']['masked'] = metadata['size']['compressed']
+    if 'costs' in segments and 'stft_db' in segments:
+        metadata['size']['mask'] = metadata['size']['compressed']
+        metadata['size']['masked'] = metadata['size']['compressed']
 
     metadata_path = f'{out_file_stem}.metadata.json'
     with open(metadata_path, 'w') as metafile: