[+] Accuracy calculation

src/accuracy_calculation.py

@@ -0,0 +1,57 @@
+import json
+
+if __name__ == '__main__':
+    with open('C:\Workspace\EECS 6414\Datasets\CN-Celeb_flac\id_labels.json', 'r', encoding='UTF-8') as f:
+        labels = json.load(f)
+
+    with open('C:\Workspace\EECS 6414\Datasets\CN-Celeb_flac\ina_pf_map.json', 'r', encoding='UTF-8') as f:
+        pf = json.load(f)
+
+    correct_f = []
+    correct_m = []
+    incorrect_f = []
+    incorrect_m = []
+
+    for k in labels:
+        if k not in pf:
+            print(f'Skipped {k}')
+            continue
+
+        if labels[k] == 'f':
+            if pf[k] > 0.5:
+                correct_f += k
+            else:
+                incorrect_f += k
+
+        if labels[k] == 'm':
+            if pf[k] < 0.5:
+                correct_m += k
+            else:
+                incorrect_m += k
+
+    print('Done Reading\n')
+
+    tp = len(correct_f)
+    tn = len(correct_m)
+    fp = len(incorrect_f)
+    fn = len(incorrect_m)
+
+    print('True Positive (F classified as F):', tp)
+    print('True Negative (M classified as M):', tn)
+    print('False Positive (F classified as M):', fp)
+    print('False Negative (M classified as F):', fn)
+
+    acc = (tp + tn) / (tp + tn + fp + fn)
+    precision_f = tp / (tp + fp)
+    recall_f = tp / (tp + fn)
+    precision_m = tn / (tn + fn)
+    recall_m = tn / (tn + fp)
+
+    print('Accuracy:', acc)
+    print('Precision F:', precision_f)
+    print('Recall F:', recall_f)
+    print('Precision M:', precision_m)
+    print('Recall M:', recall_m)
+
+
+

src/ina_main.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import io
 import os
+import subprocess
 import tempfile
 import time
 import warnings
@@ -178,15 +179,26 @@ def test():
     seg = Segmenter()
 
     # Warmup run
-    results = process(seg, ['../test.mp3'])
+    results = process(seg, ['../test.flac'])
     print(results)
 
-    # Actual run
-    results = process(seg, ['../test.mp3'])
-    print(results)
+    # # Actual run
+    # results = process(seg, ['../test.flac'])
+    # print(results)
+
+    # Benchmark
+    iterations = 60
+    total_time = 0
+    audio_file = '../test.flac'
+    audio_len = float(subprocess.getoutput(f'ffprobe -i {audio_file} -show_entries format=duration -v quiet -of csv="p=0"'))
+
+    for i in range(iterations):
+        results = process(seg, ['../test.flac'])
+        total_time += results.time_full
+    print(f'Benchmark result: {total_time}s / {iterations} iterations = {total_time / iterations / audio_len} seconds of processing per second in audio')
 
     # Draw results
-    with draw_result('../test.mp3', results.results[0]) as buf:
+    with draw_result('../test.flac', results.results[0]) as buf:
         show_image_buffer(buf)
         print(get_result_percentages(results.results[0]))