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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-08-24 12:20:43 +02:00
parent bbe22dd7b4
commit 4b424b2381
1 changed files with 4 additions and 4 deletions
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8
utils/utils.py
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@ -592,7 +592,7 @@ def coco_only_people(path='../coco/labels/val2014/'):
def select_best_evolve(path='evolve*.txt'): # from utils.utils import *; select_best_evolve()
# Find best evolved mutation
for file in sorted(glob.glob(path)):
x = np.loadtxt(file, dtype=np.float32)
x = np.loadtxt(file, dtype=np.float32, ndmin=2)
fitness = x[:, 2] * 0.5 + x[:, 3] * 0.5 # weighted mAP and F1 combination
print(file, x[fitness.argmax()])
@ -774,7 +774,7 @@ def plot_targets_txt(): # from utils.utils import *; plot_targets_txt()
def plot_evolution_results(hyp): # from utils.utils import *; plot_evolution_results(hyp)
# Plot hyperparameter evolution results in evolve.txt
x = np.loadtxt('evolve.txt')
x = np.loadtxt('evolve.txt', ndmin=2)
f = fitness(x)
weights = (f - f.min()) ** 2 # for weighted results
fig = plt.figure(figsize=(12, 10))
@ -799,7 +799,7 @@ def plot_results(start=0, stop=0): # from utils.utils import *; plot_results()
s = ['GIoU', 'Confidence', 'Classification', 'Precision', 'Recall',
'val GIoU', 'val Confidence', 'val Classification', 'mAP', 'F1']
for f in sorted(glob.glob('results*.txt') + glob.glob('../../Downloads/results*.txt')):
results = np.loadtxt(f, usecols=[2, 4, 5, 9, 10, 13, 14, 15, 11, 12]).T
results = np.loadtxt(f, usecols=[2, 4, 5, 9, 10, 13, 14, 15, 11, 12], ndmin=2).T
n = results.shape[1] # number of rows
x = range(start, min(stop, n) if stop else n)
for i in range(10):
@ -821,7 +821,7 @@ def plot_results_overlay(start=0, stop=0): # from utils.utils import *; plot_re
s = ['train', 'train', 'train', 'Precision', 'mAP', 'val', 'val', 'val', 'Recall', 'F1'] # legends
t = ['GIoU', 'Confidence', 'Classification', 'P-R', 'mAP-F1'] # titles
for f in sorted(glob.glob('results*.txt') + glob.glob('../../Downloads/results*.txt')):
results = np.loadtxt(f, usecols=[2, 4, 5, 9, 11, 13, 14, 15, 10, 12]).T
results = np.loadtxt(f, usecols=[2, 4, 5, 9, 11, 13, 14, 15, 10, 12], ndmin=2).T
n = results.shape[1] # number of rows
x = range(start, min(stop, n) if stop else n)
fig, ax = plt.subplots(1, 5, figsize=(14, 3.5))