import sys
import matplotlib.pyplot as plt
import time
sys.path.append('.')
from docrec.strips.strips import Strips
# segmentation
print('=> Segmentation')
t0 = time.time()
strips = Strips(path='datasets/D2/mechanical/D002', filter_blanks=True)
strips.plot()
plt.show()
print('Strips elapsed time={:.2f} seconds'.format(time.time() - t0))
N = len(strips.strips)
fig = plt.figure(figsize=(8, 8), dpi=150)
for i in range(N):
for j in range(N):
if i + 1 == j:
t0 = time.time()
print(i, j, N)
image = strips.pair(i, j, filled=True)
print('Pairing time={:.2f} seconds'.format(time.time() - t0))
plt.clf()
plt.imshow(image)
#plt.savefig('/home/thiagopx/temo/{}-{}.pdf'.format(i, j))
plt.show()
#strips.plot()
t0_global = time.time()
print('=> Segmentation')
t0 = time.time()
#strips = StripsText(path=args.doc, filter_blanks=True)
strips = Strips(path=args.doc, filter_blanks=True)
print('Segmentation elapsed time={:.2f} seconds'.format(time.time() - t0))
N = len(strips.strips)
pcont = 0.2
scores = np.zeros((N, N), dtype=np.int32)
for i in range(N - 1):
border = strips.strips[i].offsets_r
j = i + 1
print('=> Scoring [{}][{}]'.format(i, j))
image = strips.pair(i, j, accurate=True, filled=True)
h, w, _ = image.shape
_, image_bin = cv2.threshold(cv2.cvtColor(image, cv2.COLOR_RGB2GRAY),
0, 1, cv2.THRESH_BINARY +
cv2.THRESH_OTSU) # range [0, 1]
temp = image_bin.astype(np.float32)
image3 = np.stack([temp, temp, temp])
batch = []
total_inferences = 0
yx = []
labels = []
for y in range(radius, h - radius):
x = border[y]
crop = image3[:, y - radius:y + radius + 1,
x - radius:x + radius + 1]