Analyse tracks (#15)

* load values from metadata and allow for slightly longer last cacophony index bin

* add support for new audio models

* add chirps

* adjust chirps and track generation

* reduce min track length

* analyse tracks

---------

Co-authored-by: gferraro <[email protected]>

Melt/chain.py

@@ -12,8 +12,9 @@
 from identify_morepork import identify_morepork
 from identify_tracks import classify, get_max_chirps
 import math
-
+from pathlib import Path
 import argparse
+import json
 
 NON_BIRD = ["human", "noise"]
 
@@ -99,38 +100,45 @@ def filter_tracks(tracks):
     return filtered
 
 
-def species_identify(file_name, morepork_model, bird_models):
+def species_identify(file_name, morepork_model, bird_models,analyse_tracks):
     labels = []
     result = {}
-    if morepork_model is not None:
+    meta_file = Path(file_name).with_suffix(".txt")
+    meta_data = None
+    if meta_file.exists():
+        with meta_file.open("r") as f:
+            meta_data = json.load(f)
+    if morepork_model is not None and not analyse_tracks:
         morepork_ids = identify_morepork(file_name, morepork_model)
         labels.extend(morepork_ids)
     if bird_models is not None:
-        bird_ids, length, chirps, signals = classify(file_name, bird_models)
+        bird_ids, length, chirps, signals = classify(file_name, bird_models,analyse_tracks,meta_data)
         labels.extend(bird_ids)
         cacophony_index, version = calc_cacophony_index(filter_tracks(bird_ids), length)
-        max_chirps = get_max_chirps(length)
-        version = "2.0"
-        chirp_index = 0 if max_chirps == 0 else round(100 * chirps / max_chirps)
-
-        result["cacophony_index"] = cacophony_index
-        result["cacophony_index_version"] = version
-        result["chirps"] = {
-            "chirps": chirps,
-            "max_chirps": max_chirps,
-            "chirp_index": chirp_index,
-            "signals": [s.to_array() for s in signals],
-        }
+        if not analyse_tracks: 
+            max_chirps = get_max_chirps(length)
+            version = "2.0"
+            chirp_index = 0 if max_chirps == 0 else round(100 * chirps / max_chirps)
+
+            result["cacophony_index"] = cacophony_index
+            result["cacophony_index_version"] = version
+            result["chirps"] = {
+                "chirps": chirps,
+                "max_chirps": max_chirps,
+                "chirp_index": chirp_index,
+                "signals": [s.to_array() for s in signals],
+            }
+
     result["species_identify"] = labels
     result["species_identify_version"] = "2021-02-01"
     return result
 
 
-def examine(file_name, morepork_model, bird_model):
+def examine(file_name, morepork_model, bird_model,analyse_tracks=False):
     import cacophony_index
 
     summary = cacophony_index.calculate(file_name)
-    summary.update(species_identify(file_name, morepork_model, bird_model))
+    summary.update(species_identify(file_name, morepork_model, bird_model,analyse_tracks))
     return summary
 
 
@@ -163,13 +171,30 @@ def parse_args():
 
     parser.add_argument("file", help="Audio file to run on")
 
+    parser.add_argument(
+        "--analyse-tracks",
+        type=str2bool,
+        default=False,
+        help="Classify human made tracks marked with classify flag, in metadata file",
+    )
+
     args = parser.parse_args()
     if args.bird_model is None or len(args.bird_model) == 0:
         args.bird_model = ["/models/bird-model"]
 
     return args
 
 
+def str2bool(v):
+    if isinstance(v, bool):
+        return v
+    if v.lower() in ("yes", "true", "t", "y", "1"):
+        return True
+    elif v.lower() in ("no", "false", "f", "n", "0"):
+        return False
+    else:
+        raise argparse.ArgumentTypeError("Boolean value expected.")
+
 def main():
     args = parse_args()
 
@@ -182,7 +207,7 @@ def main():
 
         summary = cacophony_index.calculate(args.file)
     else:
-        summary = examine(args.file, args.morepork_model, args.bird_model)
+        summary = examine(args.file, args.morepork_model, args.bird_model, analyse_tracks = args.analyse_tracks )
 
     t1 = time.time()
 

Melt/identify_tracks.py

@@ -22,6 +22,7 @@
 DEFAULT_BIRDS = ["bird"]
 DEFAULT_BIRDS.extend(DEFAULT_SPECIES)
 SIGNAL_WIDTH = 0.25
+MAX_FRQUENCY = 48000 / 2
 
 
 # roughly the max possible chirps
@@ -319,14 +320,30 @@ def get_end(frames, sr):
     return file_length
 
 
-def classify(file, models):
+def classify(file, models,analyse_tracks,meta_data = None):
     frames, sr = load_recording(file)
     length = get_end(frames, sr)
     signals = signal_noise(frames[: int(sr * length)], sr, 281)
     # want to use signals for chrips
-    tracks = [s.copy() for s in signals]
+
+    if analyse_tracks:
+        if meta_data is None:
+            return
+        meta_tracks = [t for t in meta_data["Tracks"] if t.get("classify")]
+        tracks = []
+        for t in meta_tracks:
+            pos = t["data"]["positions"][0]
+            freq_start = pos["y"] * MAX_FRQUENCY
+            freq_end = pos["height"]*MAX_FRQUENCY + freq_start
+
+            # add to signals also???
+            signal = Signal(t["data"]["start_s"], t["data"]["end_s"], freq_start,freq_end)
+            signal.track_id = t["id"]
+            tracks.append(signal)
+    else:
+        tracks = [s.copy() for s in signals]
 
-    tracks = get_tracks_from_signals(tracks, length)
+        tracks = get_tracks_from_signals(tracks, length)
     mel_data = None
 
     for model_file in models:
@@ -650,6 +667,7 @@ def __init__(self, start, end, freq_start, freq_end):
         self.mel_freq_start = mel_freq(freq_start)
         self.mel_freq_end = mel_freq(freq_end)
         self.predictions = []
+        self.track_id = None
         # self.model = None
         # self.labels = None
         # self.confidences = None
@@ -737,6 +755,8 @@ def get_meta(self):
         meta["freq_start"] = self.freq_start
         meta["freq_end"] = self.freq_end
         meta["predictions"] = [r.get_meta() for r in self.predictions]
+        if self.track_id is not None:
+            meta["track_id"] = self.track_id
         return meta