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ultralytics 8.0.72 faster Windows trainings and corrupt cache fix (#1912)

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Co-authored-by: andreaswimmer <53872150+andreaswimmer@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2023-04-10 00:21:03 +02:00
committed by GitHub
parent 48f1d269fb
commit 95f96dc5bc
18 changed files with 312 additions and 413 deletions
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38
ultralytics/tracker/utils/gmc.py
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@ -3,7 +3,6 @@
import copy
import cv2
import matplotlib.pyplot as plt
import numpy as np
from ultralytics.yolo.utils import LOGGER
@ -205,24 +204,25 @@ class GMC:
currPoints = np.array(currPoints)
# Draw the keypoint matches on the output image
if 0:
matches_img = np.hstack((self.prevFrame, frame))
matches_img = cv2.cvtColor(matches_img, cv2.COLOR_GRAY2BGR)
W = np.size(self.prevFrame, 1)
for m in goodMatches:
prev_pt = np.array(self.prevKeyPoints[m.queryIdx].pt, dtype=np.int_)
curr_pt = np.array(keypoints[m.trainIdx].pt, dtype=np.int_)
curr_pt[0] += W
color = np.random.randint(0, 255, 3)
color = (int(color[0]), int(color[1]), int(color[2]))
matches_img = cv2.line(matches_img, prev_pt, curr_pt, tuple(color), 1, cv2.LINE_AA)
matches_img = cv2.circle(matches_img, prev_pt, 2, tuple(color), -1)
matches_img = cv2.circle(matches_img, curr_pt, 2, tuple(color), -1)
plt.figure()
plt.imshow(matches_img)
plt.show()
# if False:
# import matplotlib.pyplot as plt
# matches_img = np.hstack((self.prevFrame, frame))
# matches_img = cv2.cvtColor(matches_img, cv2.COLOR_GRAY2BGR)
# W = np.size(self.prevFrame, 1)
# for m in goodMatches:
# prev_pt = np.array(self.prevKeyPoints[m.queryIdx].pt, dtype=np.int_)
# curr_pt = np.array(keypoints[m.trainIdx].pt, dtype=np.int_)
# curr_pt[0] += W
# color = np.random.randint(0, 255, 3)
# color = (int(color[0]), int(color[1]), int(color[2]))
#
# matches_img = cv2.line(matches_img, prev_pt, curr_pt, tuple(color), 1, cv2.LINE_AA)
# matches_img = cv2.circle(matches_img, prev_pt, 2, tuple(color), -1)
# matches_img = cv2.circle(matches_img, curr_pt, 2, tuple(color), -1)
#
# plt.figure()
# plt.imshow(matches_img)
# plt.show()
# Find rigid matrix
if (np.size(prevPoints, 0) > 4) and (np.size(prevPoints, 0) == np.size(prevPoints, 0)):