Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-02-20 15:11:55 +01:00
parent a65a383d3a
commit ead4af98b0
1 changed files with 14 additions and 3 deletions
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17
utils/utils.py
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@ -430,6 +430,17 @@ def coco_class_count(path='../coco/labels/train2014/'):
print(i, len(files)) print(i, len(files))
def coco_only_people(path='../coco/labels/val2014/'):
# find images with only people
import glob
files = sorted(glob.glob('%s/*.*' % path))
for i, file in enumerate(files):
labels = np.loadtxt(file, dtype=np.float32).reshape(-1, 5)
if all(labels[:, 0] == 0):
print(labels.shape[0], file)
def plot_results(): def plot_results():
# Plot YOLO training results file 'results.txt' # Plot YOLO training results file 'results.txt'
import glob import glob
@ -437,11 +448,11 @@ def plot_results():
import numpy as np import numpy as np
# import os; os.system('rm -rf results.txt && wget https://storage.googleapis.com/ultralytics/results_v1_0.txt') # import os; os.system('rm -rf results.txt && wget https://storage.googleapis.com/ultralytics/results_v1_0.txt')
plt.figure(figsize=(16, 8)) plt.figure(figsize=(14, 7))
s = ['XY', 'Width-Height', 'Confidence', 'Classification', 'Total Loss', 'mAP', 'Recall', 'Precision'] s = ['X + Y', 'Width + Height', 'Confidence', 'Classification', 'Total Loss', 'mAP', 'Recall', 'Precision']
files = sorted(glob.glob('results*.txt')) files = sorted(glob.glob('results*.txt'))
for f in files: for f in files:
results = np.loadtxt(f, usecols=[2, 3, 4, 5, 6, 11, 12, 13]).T # column 11 is mAP results = np.loadtxt(f, usecols=[2, 3, 4, 5, 6, 9, 10, 11]).T # column 11 is mAP
n = results.shape[1] n = results.shape[1]
for i in range(8): for i in range(8):
plt.subplot(2, 4, i + 1) plt.subplot(2, 4, i + 1)