From b48a1c6292a095fea59b30e0ab814961128b23cc Mon Sep 17 00:00:00 2001
From: gferraro <g.ferraro22@gmail.com>
Date: Wed, 8 Nov 2023 10:49:19 +1300
Subject: [PATCH] filter tracks below 1000

---
 Melt/identify_tracks.py | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/Melt/identify_tracks.py b/Melt/identify_tracks.py
index 42a9b6f..f6b6120 100644
--- a/Melt/identify_tracks.py
+++ b/Melt/identify_tracks.py
@@ -59,9 +59,10 @@ def load_samples(
     power=1,
     db_scale=False,
     filter_freqs=True,
+    filter_below=None,
 ):
     logging.debug(
-        "Loading samples with length %s stride %s hop length %s and mean_sub %s mfcc %s break %s htk %s n mels %s fmin %s fmax %s filtering freqs %s",
+        "Loading samples with length %s stride %s hop length %s and mean_sub %s mfcc %s break %s htk %s n mels %s fmin %s fmax %s filtering freqs %s filter below %s",
         segment_length,
         stride,
         hop_length,
@@ -73,6 +74,7 @@ def load_samples(
         fmin,
         fmax,
         filter_freqs,
+        filter_below,
     )
     mels = []
     i = 0
@@ -97,6 +99,13 @@ def load_samples(
             track_frames = butter_bandpass_filter(
                 track_frames, t.freq_start, t.freq_end, sr
             )
+        elif filter_below and t.freq_end < filter_below:
+            logging.info(
+                "Filter freq below %s %s %s", filter_below, t.freq_start, t.freq_end
+            )
+            track_frames = butter_bandpass_filter(
+                track_frames, t.freq_start, t.freq_end, sr
+            )
         while True:
             data = track_frames[sr_start:sr_end]
             if len(data) != sample_size:
@@ -323,6 +332,7 @@ def classify(file, models):
     for model_file in models:
         model, meta = load_model(model_file)
         filter_freqs = meta.get("filter_freq", True)
+        filter_below = meta.get("filter_below", 1000)
 
         labels = meta.get("labels")
         multi_label = meta.get("multi_label")
@@ -366,6 +376,7 @@ def classify(file, models):
                 power=power,
                 db_scale=db_scale,
                 filter_freqs=filter_freqs,
+                filter_below=filter_below,
             )
             data = mel_data
         if len(data) == 0: