本文整理汇总了Python中skimage.feature.local_binary_pattern方法的典型用法代码示例。如果您正苦于以下问题：Python feature.local_binary_pattern方法的具体用法？Python feature.local_binary_pattern怎么用？Python feature.local_binary_pattern使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类skimage.feature的用法示例。
在下文中一共展示了feature.local_binary_pattern方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: objective
# 需要导入模块: from skimage import feature [as 别名]
# 或者: from skimage.feature import local_binary_pattern [as 别名]
def objective(trial):
# Get Olivetti faces dataset.
x_ref, x_valid, y_ref, y_valid = load_data()
# We optimize parameters of local_binary_pattern function in skimage
# and the choice of distance metric classes.
P = trial.suggest_int("P", 1, 15)
R = trial.suggest_uniform("R", 1, 10)
method = trial.suggest_categorical("method", ["default", "uniform"])
metric = trial.suggest_categorical("metric", ["kl", "cos", "euc"])
x_ref_hist = img2hist(x_ref, P, R, method)
x_valid_hist = img2hist(x_valid, P, R, method)
dist = calc_dist(x_ref_hist, x_valid_hist, metric)
y_pred = np.argmin(dist, axis=1)
accuracy = sklearn.metrics.accuracy_score(y_valid, y_pred)
return accuracy 示例2: turn_lbp_desc
# 需要导入模块: from skimage import feature [as 别名]
# 或者: from skimage.feature import local_binary_pattern [as 别名]
def turn_lbp_desc(old: np.ndarray, radius: int = None) -> np.ndarray:
if not radius:
radius = 3
n_points = 8 * radius
grey = turn_grey(old)
lbp = local_binary_pattern(grey, n_points, radius, method="default")
return lbp 示例3: demoLBP
# 需要导入模块: from skimage import feature [as 别名]
# 或者: from skimage.feature import local_binary_pattern [as 别名]
def demoLBP(fn):
fn = Path(fn).expanduser()
vid = cv2.VideoCapture(str(fn))
# vidparam = getaviprop(vid)
while True:
ret, img = vid.read()
if not ret:
break
if img.ndim == 3:
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
lbp = local_binary_pattern(img, 8, 3, 'default')
cv2.imshow('lbp', lbp)
cv2.waitKey(delay=1) 示例4: get_lbp_hist
# 需要导入模块: from skimage import feature [as 别名]
# 或者: from skimage.feature import local_binary_pattern [as 别名]
def get_lbp_hist(img, P, R, method):
lbp = ft.local_binary_pattern(img, P, R, method)
if method == "uniform":
bin_max = P + 3
range_max = P + 2
elif method == "default":
bin_max = 2 ** P
range_max = 2 ** P - 1
hist, _ = np.histogram(
lbp.ravel(), density=True, bins=np.arange(0, bin_max), range=(0, range_max)
)
return hist 示例5: compute_lbp
# 需要导入模块: from skimage import feature [as 别名]
# 或者: from skimage.feature import local_binary_pattern [as 别名]
def compute_lbp(img, params):
lbp_radius = float(params.get("lbp_radius", 3))
lbp_points = int(params.get("lbp_points", 24)) # example sets radius * 8
lbp_method = params.get("lbp_method", "default")
return local_binary_pattern(rgb2gray(img), P=lbp_points, R=lbp_radius, method=lbp_method)[:, :, None]