[M] Move non-api scripts to experiment\

experiment/validate_cn_celeb.py

@@ -0,0 +1,168 @@
+import json
+import os
+import warnings
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+import pygame
+from inaSpeechSegmenter import Segmenter
+
+from ina_main import process, get_result_percentages
+from utils import color, printc
+
+
+def segment_all():
+    # Create segmenter
+    seg = Segmenter()
+    np.seterr(invalid='ignore')
+
+    # Loop through all celebrities
+    for id in ids:
+        id_dir = data_dir.joinpath(id)
+
+        # Loop through all recordings (Exclude singing for now)
+        utters = [r for r in os.listdir(id_dir) if r.endswith('.flac')
+                  and not r.startswith('singing')]
+
+        # Exclude existing
+        utters = [id_dir.joinpath(u) for u in utters]
+        utters = [u for u in utters if not u.with_suffix('.json').exists()]
+
+        if len(utters) == 0:
+            continue
+
+        # Analyze
+        results = process(seg, [str(u) for u in utters], verbose=True)
+
+        # Write results
+        total = [0, 0, 0, 0, 0]
+        type_totals = {}
+        for result in results.results:
+            file = Path(result.file).with_suffix('.json')
+
+            # Get results
+            # f: Frames, r: Ratios
+            ratios = [round(r, 3) for r in get_result_percentages(result)]
+            stored = {'f': result.frames, 'r': ratios}
+
+            # Count type total (type_totals[utter_type][-1] is the count)
+            file_name = file.name
+            utter_type = file_name[:file_name.index('-')]
+            type_totals.setdefault(utter_type, [0, 0, 0, 0, 0])
+            for i in range(4):
+                type_totals[utter_type][i] += ratios[i]
+                total[i] += ratios[i]
+            type_totals[utter_type][-1] += 1
+            total[-1] += 1
+
+            # Write result
+            file.write_text(json.dumps(stored))
+
+        # Write type averages
+        type_averages = {t: [r / type_totals[t][-1] for r in type_totals[t][:-1]] for t in type_totals}
+        total_average = [r / total[-1] for r in total[:-1]]
+        obj = {'type_averages': type_averages, 'total_averages': total_average}
+        id_dir.joinpath('total.json').write_text(json.dumps(obj))
+
+
+def graph_histogram():
+    closest_to_half = 1000
+    closest_to_half_id = ''
+    id_pf_map = {}
+    for id in ids:
+        id_dir = data_dir.joinpath(id)
+        json_path = id_dir.joinpath('total.json')
+
+        if not json_path.exists():
+            continue
+
+        obj = json.loads(json_path.read_text())
+        f, m, o, pf = obj['total_averages']
+
+        # Recalculate pf (pf is actually calculated incorrectly)
+        if f + m == 0:
+            continue
+        pf = f / (f + m)
+        id_pf_map[id] = pf
+
+        # Save fixed json
+        obj['total_averages'][3] = pf
+        json_path.write_text(json.dumps(obj))
+
+        # Find pf closest to .5
+        dist = abs(pf - .5)
+        if dist < closest_to_half:
+            closest_to_half = dist
+            closest_to_half_id = id
+
+    data_dir.joinpath('id_pf_map.json').write_text(json.dumps(id_pf_map))
+    plt.hist(id_pf_map.values(), bins=50)
+    plt.show()
+    print(closest_to_half_id)
+
+
+def manually_label_data():
+    """
+    Since CN-Celeb isn't labelled with the speaker's gender, this script is used to manually label
+    them.
+    """
+    pygame.mixer.init()
+
+    # Load existing labels
+    labels_json = data_dir.joinpath('id_labels.json')
+    id_labels = json.loads(labels_json.read_text()) if labels_json.exists() else {}
+
+    # Load pf table
+    id_pfs = json.loads(data_dir.joinpath('id_pf_map.json').read_text())
+
+    # Loop through all speaker
+    for id in sorted(ids):
+        id_dir = data_dir.joinpath(id)
+
+        # Skip already identified labels
+        if id in id_labels:
+            continue
+
+        # Get ina choice
+        pf = id_pfs.get(id, -1)
+        ina_choice = 'f' if pf > 0.5 else 'm'
+
+        # Loop through all tracks until identified
+        tracks = [f for f in os.listdir(id_dir) if f.endswith('.flac')]
+        for track_i, audio in enumerate(tracks):
+            # Play track
+            sound = pygame.mixer.Sound(id_dir.joinpath(audio))
+            sound.play()
+            i = input(color(
+                f'\n&7Playing speaker {id[-3:]}/{len(ids)} - track {track_i}/{len(tracks)} - {audio}&r'
+                f'\n- Press f / m, or anything else to play next track: '))\
+                .lower().strip()
+            sound.stop()
+
+            # Skip
+            if i == 's':
+                break
+
+            # Labeled
+            if i == 'f' or i == 'm':
+                id_labels[id] = i
+                labels_json.write_text(json.dumps(id_labels))
+
+                # Print choice match
+                if pf != -1:
+                    agree = '&aINA agrees' if ina_choice == i else '&cINA disagree'
+                    printc(f'{agree} with confidence {abs(pf - 0.5) * 200:.0f}%')
+                else:
+                    printc(f"&7INA didn't identify any voice")
+                break
+
+
+if __name__ == '__main__':
+    cn_celeb_root = Path('C:/Users/me/Workspace/Data/CN-Celeb_flac')
+    data_dir = cn_celeb_root.joinpath('data')
+    ids = [id for id in os.listdir(data_dir) if id.startswith('id0')]
+
+    # segment_all()
+    # graph_histogram()
+    manually_label_data()