def test_random_with_same_aspect():
# rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize)
# if not any((rect.intersects_pixelrectangle(pr) for pr in excl_info)):
# # Test random_with_same_aspect:
# img_path = neg_regions[0].fname
# img = cv2.imread(img_path)
window_dims = (300, 200)
img = np.zeros((500, 500, 3), np.uint8)
h, w = img.shape[:2]
imsize = (w, h)
rects = []
for i in range(10000):
rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize)
rects.append(rect)
clone = img.copy()
training.cvDrawRectangle(clone, rect, (255, 0, 0), 2)
# Test moved_to_clear:
new_rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize)
training.cvDrawRectangle(clone, new_rect, (0, 255, 0), 2)
moved_rect = new_rect.moved_to_clear(rect)
training.cvDrawRectangle(clone, moved_rect, (0, 0, 255), 2)
print rect.intersects_pixelrectangle(moved_rect)
# Test intersects_pixelrectangle:
# for i in range(200):
# new_rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize)
# col = (0, 0, 255) if rect.intersects_pixelrectangle(new_rect) else (255, 255, 255)
# if not rect.intersects_pixelrectangle(new_rect):
# training.cvDrawRectangle(clone, new_rect, col, 2)
cv2.imshow("img", clone)
while True:
key = cv2.waitKey(1) & 0xFF
# if key == 27: # ESC key
# cv2.destroyAllWindows()
# return
if key != 255:
break
print "Saving histogram..."
from cardetection.carutils.plotting import saveHistogram
aspects = map(lambda r: r.w, rects)
saveHistogram("region-aspects.pdf", aspects, bins=20)
print "Saved!"
def test_random_with_same_aspect():
# rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize)
# if not any((rect.intersects_pixelrectangle(pr) for pr in excl_info)):
# # Test random_with_same_aspect:
# img_path = neg_regions[0].fname
# img = cv2.imread(img_path)
window_dims = (300, 200)
img = np.zeros((500, 500, 3), np.uint8)
h, w = img.shape[:2]
imsize = (w, h)
rects = []
for i in range(10000):
rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize)
rects.append(rect)
clone = img.copy()
training.cvDrawRectangle(clone, rect, (255, 0, 0), 2)
# Test moved_to_clear:
new_rect = gm.PixelRectangle.random_with_same_aspect(
window_dims, imsize)
training.cvDrawRectangle(clone, new_rect, (0, 255, 0), 2)
moved_rect = new_rect.moved_to_clear(rect)
training.cvDrawRectangle(clone, moved_rect, (0, 0, 255), 2)
print rect.intersects_pixelrectangle(moved_rect)
# Test intersects_pixelrectangle:
# for i in range(200):
# new_rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize)
# col = (0, 0, 255) if rect.intersects_pixelrectangle(new_rect) else (255, 255, 255)
# if not rect.intersects_pixelrectangle(new_rect):
# training.cvDrawRectangle(clone, new_rect, col, 2)
cv2.imshow('img', clone)
while True:
key = cv2.waitKey(1) & 0xFF
# if key == 27: # ESC key
# cv2.destroyAllWindows()
# return
if key != 255:
break
print 'Saving histogram...'
from cardetection.carutils.plotting import saveHistogram
aspects = map(lambda r: r.w, rects)
saveHistogram('region-aspects.pdf', aspects, bins=20)
print 'Saved!'
# for img_path in training.sampleTrainingImages(positive_dir, ['.*'], None, require_bboxes=True, bbinfo_dir=bbinfo_dir):
# key = img_path.split('/')[-1]
# rects_str = global_info[key]
# rects = utils.rectangles_from_cache_string(rects_str)
# for rect in rects:
# all_rects.append(rect)
#
#
# aspects = map(lambda rect: rect.h/float(rect.w), all_rects)
kitti_base = '/Users/mitchell/data/kitti/'
category_types = ['Car', 'Van']
pos_labels = kitti.getPositiveImageLabels(kitti_base, category_types)
aspects = map(lambda l: l.aspect, pos_labels)
saveHistogram('aspects.pdf', aspects)
plt.close()
# angles = map(lambda l: l.alpha*180.0/np.pi, pos_labels)
angles = map(lambda l: l.ry * 180.0 / np.pi, pos_labels)
# angles = map(lambda l: l.ry, pos_labels)
saveHistogram('angles.pdf', angles)
shape = (64, 64)
aspect = shape[0] / float(shape[1])
angle = -90
angleRange = 5
aspectRange = 0.5
filtered = pos_labels
filtered = filter(
# for img_path in training.sampleTrainingImages(positive_dir, ['.*'], None, require_bboxes=True, bbinfo_dir=bbinfo_dir):
# key = img_path.split('/')[-1]
# rects_str = global_info[key]
# rects = utils.rectangles_from_cache_string(rects_str)
# for rect in rects:
# all_rects.append(rect)
#
#
# aspects = map(lambda rect: rect.h/float(rect.w), all_rects)
kitti_base = '/Users/mitchell/data/kitti/'
category_types = ['Car', 'Van']
pos_labels = kitti.getPositiveImageLabels(kitti_base, category_types)
aspects = map(lambda l: l.aspect, pos_labels)
saveHistogram('aspects.pdf', aspects)
plt.close()
# angles = map(lambda l: l.alpha*180.0/np.pi, pos_labels)
angles = map(lambda l: l.ry*180.0/np.pi, pos_labels)
# angles = map(lambda l: l.ry, pos_labels)
saveHistogram('angles.pdf', angles)
shape = (64, 64)
aspect = shape[0]/float(shape[1])
angle = -90
angleRange = 5
aspectRange = 0.5
filtered = pos_labels
filtered = filter(lambda l: abs(l.ry*180.0/np.pi - angle) < angleRange/2.0, filtered)