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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2020-01-08 16:36:35 -08:00
parent 11ce877bdf
commit 3e5b007e3a
2 changed files with 4 additions and 3 deletions
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4
test.py
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@ -158,8 +158,8 @@ def test(cfg,
stats = [np.concatenate(x, 0) for x in list(zip(*stats))] # to numpy stats = [np.concatenate(x, 0) for x in list(zip(*stats))] # to numpy
if len(stats): if len(stats):
p, r, ap, f1, ap_class = ap_per_class(*stats) p, r, ap, f1, ap_class = ap_per_class(*stats)
# if niou > 1: if niou > 1:
# p, r, ap, f1 = p[:, 0], r[:, 0], ap[:, 0], ap.mean(1) # average across ious p, r, ap, f1 = p[:, 0], r[:, 0], ap.mean(1), ap[:, 0] # [P, R, AP@0.5:0.95, AP@0.5]
mp, mr, map, mf1 = p.mean(), r.mean(), ap.mean(), f1.mean() mp, mr, map, mf1 = p.mean(), r.mean(), ap.mean(), f1.mean()
nt = np.bincount(stats[3].astype(np.int64), minlength=nc) # number of targets per class nt = np.bincount(stats[3].astype(np.int64), minlength=nc) # number of targets per class
else: else:

3
utils/utils.py
View File

@ -863,7 +863,8 @@ def apply_classifier(x, model, img, im0):
def fitness(x): def fitness(x):
# Returns fitness (for use with results.txt or evolve.txt) # Returns fitness (for use with results.txt or evolve.txt)
return x[:, 2] * 0.3 + x[:, 3] * 0.7 # weighted combination of x=[p, r, mAP@0.5, F1 or mAP@0.5:0.95] w = [0.1, 0.1, 0.6, 0.2] # weights for [P, R, mAP, F1]@0.5 or [P, R, mAP@0.5:0.95, mAP@0.5]
return (x[:, :4] * np.array([w])).sum(1)
# Plotting functions --------------------------------------------------------------------------------------------------- # Plotting functions ---------------------------------------------------------------------------------------------------