def fit(self, x, y, precision=0.007, step=0.04):
h = precision
prev_gammas = [0] * len(y)
cur_gammas = [1] * len(y)
cur_loo = self.__loo(x, y, h, cur_gammas)
min_loo = cur_loo
min_h = h
while cur_loo > precision and h > step:
h -= step
print(h)
idx = 0
while prev_gammas != cur_gammas:
prev_gammas = cur_gammas
for xi, yi in zip(x, y):
newX = np.delete(x, xi)
newY = np.delete(y, yi)
parameter = self.__kern_smooth(xi, newX, newY,
self._kernel, self._dist, h,
cur_gammas)
value = rectangle(abs(parameter - yi))
cur_gammas[idx] = value
idx += 1
cur_loo = self.__loo(x, y, h, cur_gammas)
if min_loo > cur_loo:
min_loo = cur_loo
min_h = h
print("LOWESS MIN H", min_h)
self._gammas = cur_gammas
self._h = min_h
self._x = x
self._y = y
#剪切目录
imgcutpath = 'C:/Users/xiaoqiang/Desktop/NODE/public/zb_pythonF/table-detect-master/imgcut/'
os.chdir(MyPath)
for i in os.listdir(os.getcwd()):
postfix = i
#saveimg=i
postfix = cv2.imread(postfix)
print(type(postfix))
t = time.time()
boxes, adBoxes, scores = table_detect(postfix,
sc=(416, 416),
thresh=0.5,
NMSthresh=0.3)
# print("正在处理" + i + "图片")
# print("处理时间",time.time() - t, "边框坐标",boxes,"回归边框坐标",adBoxes,"置信度",scores)
img = rectangle(postfix, adBoxes)
#print(os.getcwd())
img.save(OutPath + i, "png")
#cv2.imwrite(OutPath + i+ ".png", postfix)
#print(MyPath + i)
#saveimg = cv2.imread(MyPath + i)
#print(type(saveimg))
img = cv2.imread(MyPath + i)
# print(type(img))
for k in range(len(adBoxes)):
# print("剪切第" + str(k) + "表格区域")
# print(len(adBoxes))
crop1 = img[int(adBoxes[k][1]):int(adBoxes[k][3]),
int(adBoxes[k][0]):int(adBoxes[k]
[2])] # 裁剪坐标为[y0:y1, x0:x1]
cv2.imwrite(imgcutpath + str(k) + i, crop1)
:param img: 源文件是cv2格式
:param adBoxes: bboxing的坐标列表，可以有多个
:return:
"""
img_name_split = img_name.split('.')
img_name_prefix = '.'.join(img_name_split[:-1])
image_name_extention = '.' + img_name_split[-1]
for idx, bbox in enumerate(adBoxes):
xmin, ymin, xmax, ymax = [int(b) for b in bbox]
crop_img = img[ymin:ymax,xmin:xmax]
name = img_name_prefix + f'_cropimg_{idx}' + image_name_extention
cv2.imwrite(name, crop_img)
print(f'已经把表格保存到{name}')
if __name__ == '__main__':
import time
# p = 'img/table-detect.jpg'
p = 'img/table_without_line.jpg'
#读取图片
img = cv2.imread(p)
t = time.time()
#获取bbox
boxes, adBoxes, scores = table_detect(img, sc=(416, 416), thresh=0.5, NMSthresh=0.3)
print(time.time() - t, boxes, adBoxes, scores)
#把adBoxed画到图像上
newimg = rectangle(img, adBoxes)
newimg.save('img/table_without_line_detect.png')
# img.save('img/table_detect.png')
#截取表格图像,并保存
crop_img(img_name=p, img=img, adBoxes=adBoxes)
def plot_rectangle(x,y, szx, szy, color, ax):
utils.rectangle(x, y, szx, szy, color, ax)