Différences

Ci-dessous, les différences entre deux révisions de la page.

--- yolo_darknet_avec_un_vrai_semaphore_resultat_des_calculs [2019/05/26 17:30] – créée serge
+++ yolo_darknet_avec_un_vrai_semaphore_resultat_des_calculs [2019/05/26 17:32] – [Calcul 1] serge
@@ Ligne 43: / Ligne 43: @@
 </code>
+=====Calcul 2=====
+<code txt>
+ calculation mAP (mean average precision)...
+ detections_count = 9682, unique_truth_count = 5987
+class_id = 0, name = a, ap = 97.65%   	 (TP = 232, FP = 118)
+class_id = 1, name = space, ap = 91.08%   	 (TP = 152, FP = 0)
+class_id = 2, name = b, ap = 99.55%   	 (TP = 220, FP = 0)
+class_id = 3, name = c, ap = 97.35%   	 (TP = 227, FP = 40)
+class_id = 4, name = d, ap = 100.00%   	 (TP = 218, FP = 0)
+class_id = 5, name = e, ap = 94.33%   	 (TP = 215, FP = 0)
+class_id = 6, name = f, ap = 100.00%   	 (TP = 212, FP = 0)
+class_id = 7, name = g, ap = 96.39%   	 (TP = 207, FP = 0)
+class_id = 8, name = h, ap = 100.00%   	 (TP = 219, FP = 0)
+class_id = 9, name = i, ap = 97.12%   	 (TP = 205, FP = 61)
+class_id = 10, name = j, ap = 100.00%   	 (TP = 228, FP = 0)
+class_id = 11, name = k, ap = 100.00%   	 (TP = 241, FP = 0)
+class_id = 12, name = l, ap = 99.25%   	 (TP = 180, FP = 3)
+class_id = 13, name = m, ap = 98.64%   	 (TP = 218, FP = 0)
+class_id = 14, name = n, ap = 98.89%   	 (TP = 218, FP = 96)
+class_id = 15, name = o, ap = 99.58%   	 (TP = 237, FP = 18)
+class_id = 16, name = p, ap = 97.62%   	 (TP = 220, FP = 58)
+class_id = 17, name = q, ap = 100.00%   	 (TP = 207, FP = 35)
+class_id = 18, name = r, ap = 100.00%   	 (TP = 195, FP = 0)
+class_id = 19, name = s, ap = 99.57%   	 (TP = 229, FP = 57)
+class_id = 20, name = t, ap = 91.33%   	 (TP = 215, FP = 138)
+class_id = 21, name = u, ap = 99.99%   	 (TP = 213, FP = 6)
+class_id = 22, name = v, ap = 97.73%   	 (TP = 180, FP = 0)
+class_id = 23, name = w, ap = 99.99%   	 (TP = 235, FP = 15)
+class_id = 24, name = x, ap = 97.32%   	 (TP = 177, FP = 0)
+class_id = 25, name = y, ap = 99.55%   	 (TP = 223, FP = 0)
+class_id = 26, name = z, ap = 97.29%   	 (TP = 199, FP = 10)
+ for thresh = 0.25, precision = 0.90, recall = 0.96, F1-score = 0.93
+ for thresh = 0.25, TP = 5722, FP = 655, FN = 265, average IoU = 83.17 %
+ mean_average_precision (mAP@0.5) = 0.981556
+</code>
+=====Calcul 3=====
+<code txt>
+ calculation mAP (mean average precision)...
+ detections_count = 17161, unique_truth_count = 5987
+class_id = 0, name = a,  17161   ap = 82.72 %
+class_id = 1, name = space, 	 ap = 80.00 %
+class_id = 2, name = b, 	 ap = 100.00 %
+class_id = 3, name = c, 	 ap = 94.55 %
+class_id = 4, name = d, 	 ap = 100.00 %
+class_id = 5, name = e, 	 ap = 79.73 %
+class_id = 6, name = f, 	 ap = 100.00 %
+class_id = 7, name = g, 	 ap = 88.52 %
+class_id = 8, name = h, 	 ap = 99.72 %
+class_id = 9, name = i, 	 ap = 94.52 %
+class_id = 10, name = j, 	 ap = 99.88 %
+class_id = 11, name = k, 	 ap = 97.39 %
+class_id = 12, name = l, 	 ap = 96.58 %
+class_id = 13, name = m, 	 ap = 100.00 %
+class_id = 14, name = n, 	 ap = 93.39 %
+class_id = 15, name = o, 	 ap = 98.15 %
+class_id = 16, name = p, 	 ap = 94.77 %
+class_id = 17, name = q, 	 ap = 97.96 %
+class_id = 18, name = r, 	 ap = 100.00 %
+class_id = 19, name = s, 	 ap = 97.23 %
+class_id = 20, name = t, 	 ap = 81.34 %
+class_id = 21, name = u, 	 ap = 98.94 %
+class_id = 22, name = v, 	 ap = 65.49 %
+class_id = 23, name = w, 	 ap = 98.84 %
+class_id = 24, name = x, 	 ap = 88.67 %
+class_id = 25, name = y, 	 ap = 99.96 %
+class_id = 26, name = z, 	 ap = 81.75 %
+ for thresh = 0.25, precision = 0.94, recall = 0.86, F1-score = 0.90
+ for thresh = 0.25, TP = 5175, FP = 343, FN = 812, average IoU = 82.32 %
+ IoU threshold = 50 %
+ mean average precision (mAP@0.50) = 0.929660, or 92.97 %
+ mean_average_precision (mAP@0.5) = 0.929660
+</code>