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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2018-12-03 15:42:10 +01:00
parent b64620cf75
commit 43d74fd840
2 changed files with 5 additions and 19 deletions
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1
utils/gcp.sh
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@ -29,6 +29,7 @@ gsutil cp yolov3/weights/latest.pt gs://ultralytics
# Copy latest.pt from bucket # Copy latest.pt from bucket
gsutil cp gs://ultralytics/latest.pt yolov3/weights/latest.pt gsutil cp gs://ultralytics/latest.pt yolov3/weights/latest.pt
wget https://storage.googleapis.com/ultralytics/latest.pt
# Testing # Testing
sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3 && cd yolov3 sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3 && cd yolov3

23
utils/utils.py
View File

@ -438,33 +438,18 @@ def coco_class_count(path='/Users/glennjocher/downloads/DATA/coco/labels/train20
def plot_results(): def plot_results():
# Plot YOLO training results file 'results.txt' # Plot YOLO training results file 'results.txt'
import glob
import numpy as np import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
plt.figure(figsize=(16, 8)) plt.figure(figsize=(16, 8))
s = ['X', 'Y', 'Width', 'Height', 'Objectness', 'Classification', 'Total Loss', 'Precision', 'Recall', 'mAP'] s = ['X', 'Y', 'Width', 'Height', 'Objectness', 'Classification', 'Total Loss', 'Precision', 'Recall', 'mAP']
for f in ('results_64.txt','results_642.txt' files = sorted(glob.glob('results*.txt'))
): for f in files:
results = np.loadtxt(f, usecols=[2, 3, 4, 5, 6, 7, 8, 17, 18, 16]).T # column 16 is mAP results = np.loadtxt(f, usecols=[2, 3, 4, 5, 6, 7, 8, 17, 18, 16]).T # column 16 is mAP
n = results.shape[1] n = results.shape[1]
for i in range(10): for i in range(10):
plt.subplot(2, 5, i + 1) plt.subplot(2, 5, i + 1)
plt.plot(range(1,n), results[i, 1:], marker='.', label=f) plt.plot(range(1, n), results[i, 1:], marker='.', label=f)
plt.title(s[i]) plt.title(s[i])
if i == 0: if i == 0:
plt.legend() plt.legend()
# def plot_results(): # (OLD FORMAT before October 2018)
# # Plot YOLO training results file 'results.txt'
# import numpy as np
# import matplotlib.pyplot as plt
# plt.figure(figsize=(16, 8))
# s = ['X', 'Y', 'Width', 'Height', 'Objectness', 'Classification', 'Total Loss', 'Precision', 'Recall', 'mAP']
# for f in ('results_d5.txt', 'results_d10.txt', 'results_64.txt',
# ):
# results = np.loadtxt(f, usecols=[16]).T # column 16 is mAP
# for i in range(1):
# plt.subplot(2, 5, i + 1)
# plt.plot(results, marker='.', label=f)
# plt.title(s[i])
# if i == 0:
# plt.legend()