def best_edges(arr, threshold=0.025):
import cv2
from src.utils.preprocessing import sharpen
blurred = cv2.bilateralFilter(arr.copy(), 30, 5, 5)
cur_arr = blurred
sigma = 0.0
r = 1
repeat = 0
while r > threshold:
print "sigma: " + str(sigma)
ret = my_canny(cur_arr, sigma=sigma, save=False, show=False)
s, r = decide_sigma(ret, ret.size, threshold=threshold, show=False)
if s is False:
sigma += 0.5
else:
if sigma == 0.0 and r < 0.01 and r > 0 and repeat < 3:
repeat += 1
sharpened = sharpen(blurred, sigma=2)
cur_arr = sharpened
r = 1
continue
break
return ret, sigma, cur_arr
cur_arr = cur_arr_3[:, :, 0]
from src.utils import preprocessing
import cv2
from src.utils.canny import decide_sigma
for sigma in [5]:
for neighbor in [30]:
blur = cv2.bilateralFilter(cur_arr.copy(), neighbor, sigma, sigma)
showimage_pil(blur)
cur_arr = blur
sigma = 0.0
r = 1
threshold = 0.025
while r > threshold:
print "sigma: " + str(sigma)
ret = my_canny(cur_arr, sigma=sigma, save=False, show=False)
s, r = decide_sigma(ret, ret.size, threshold=threshold,show=True)
if s is False:
sigma += 0.5
else:
if sigma == 0.0 and r < 0.01:
sharpen = preprocessing.sharpen(blur, sigma=2)
cur_arr= sharpen
showimage_pil(sharpen)
r = 1
continue
break
showimage_pil(ret)
"""
###############################
set input/output path
###############################
"""
from src.utils import features
from src.utils import preprocessing
lns = ["L3"]
test_n = 1
for ln in lns:
input_dir = xray_dir + "/data/train/" + str(ln)
for dirName, subdirList, fileList in os.walk(input_dir):
for filename in fileList:
parts = filename.split(".")
if parts[0] == "":
continue
if parts[1] == "jpg" and test_n == 1:
test_n += 1
img = Image.open(dirName + "/" + filename)
arr_3 = np.array(img.getdata(), dtype=np.uint8).reshape(img.size[1], img.size[0], 3)
arr = arr_3[:, :, 0]
arr = preprocessing.normalize(arr)
arr = preprocessing.sharpen(arr)
# if DEBUG is True:
# showimage_pil(arr)
features.Harris_Corner(
arr, show=True, save=True, fn="/Users/ruhansa/Desktop/result/xray/feature_test/harris_corner.jpg"
)