def finding_lungs_non_DL_approach_and_save(image, file_name):
# print(row.columns.values)
# file_name = row[0]
# print("line is", file_name, image.shape)
# when reading from txt there is something in the end so we need to eliminate that
# image = cv2.imread(os.path.join("Z:\\", "Data", "ChestXRay", "images", file_name), 0)
img_height = image.shape[0]
img_width = image.shape[1]
# Get both lungs image. It uses HOG as main method,
# but if HOG found nothing it uses HAAR or LBP.
found_lungs = lf.get_lungs(image)
# this can be written in a more concise way but we just keep it a bit redundant for easy reading
if found_lungs is not None and found_lungs.shape[
0] > img_height / 2 and found_lungs.shape[1] > img_width / 2:
# print(found_lungs.shape)
found_lungs_resized = cv2.resize(found_lungs, im_shape)
# cv2.imshow(file_name, found_lungs)
# code = cv2.waitKey(0)
cv2.imwrite(os.path.join(out_folder_matched_img, file_name),
found_lungs_resized)
return True
else:
cv2.imwrite(os.path.join(out_folder_mismatched_image, file_name),
cv2.resize(image, im_shape))
return False
def lung_finder(data):
''' The purpose of below is to find
just the lungs from the chest
scans. '''
comb = []
for i in data:
found_lungs = lf.get_lungs(i)
if found_lungs is not None:
comb.append(found_lungs)
return comb
def extract_lungs(self, image_group):
""" use lung-finder to extract lung region
"""
new_group = []
for img in image_group:
found_lungs = lf.get_lungs(img)
if found_lungs is not None and 0 not in found_lungs.shape:
new_group.append(found_lungs)
else:
new_group.append(img)
return new_group
def scan(argv):
path_to_folder, use_labels = parse_argv(argv)
walks = list(os.walk(path_to_folder))
i = 0
while i < len(walks):
path, directories, files = walks[i]
files = [file for file in files if not file[0] == "."]
j = 0
while j < len(files):
file = files[j]
_, extension = os.path.splitext(file)
if extension == ".dcm" and dicom_support:
parsed = dicomparser.DicomParser(path + os.sep + file)
image = np.array(parsed.GetImage(), dtype=np.uint8)
if parsed.GetImageData(
)["photometricinterpretation"] == "MONOCHROME1":
image = 255 - image
image = cv2.equalizeHist(image)
image = cv2.medianBlur(image, 3)
elif extension in [
".bmp", ".pbm", ".pgm", ".ppm", ".sr", ".ras", ".jpeg",
".jpg", ".jpe", ".png", ".tiff", ".tif"
]:
image = cv2.imread(path + os.sep + file, 0)
image = cv2.equalizeHist(image)
image = cv2.medianBlur(image, 3)
else:
j += 1
continue
scaled_image = proportional_resize(image, 512)
right_lung_hog_rectangle = lf.find_right_lung_hog(scaled_image)
left_lung_hog_rectangle = lf.find_left_lung_hog(scaled_image)
right_lung_lbp_rectangle = lf.find_right_lung_lbp(scaled_image)
left_lung_lbp_rectangle = lf.find_left_lung_lbp(scaled_image)
right_lung_haar_rectangle = lf.find_right_lung_haar(scaled_image)
left_lung_haar_rectangle = lf.find_left_lung_haar(scaled_image)
color_image = cv2.cvtColor(scaled_image, cv2.COLOR_GRAY2BGR)
if right_lung_hog_rectangle is not None:
x, y, width, height = right_lung_hog_rectangle
cv2.rectangle(color_image, (x, y), (x + width, y + height),
(59, 254, 211), 2)
if use_labels:
cv2.putText(color_image, "HOG Right", (x + 5, y + 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (59, 254, 211),
1)
if left_lung_hog_rectangle is not None:
x, y, width, height = left_lung_hog_rectangle
cv2.rectangle(color_image, (x, y), (x + width, y + height),
(59, 254, 211), 2)
if use_labels:
cv2.putText(color_image, "HOG Left", (x + 5, y + 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (59, 254, 211),
1)
if right_lung_lbp_rectangle is not None:
x, y, width, height = right_lung_lbp_rectangle
cv2.rectangle(color_image, (x, y), (x + width, y + height),
(130, 199, 0), 2)
if use_labels:
cv2.putText(color_image, "LBP Right", (x + 5, y + 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (130, 199, 0),
1)
if left_lung_lbp_rectangle is not None:
x, y, width, height = left_lung_lbp_rectangle
cv2.rectangle(color_image, (x, y), (x + width, y + height),
(130, 199, 0), 2)
if use_labels:
cv2.putText(color_image, "LBP Left", (x + 5, y + 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (130, 199, 0),
1)
if right_lung_haar_rectangle is not None:
x, y, width, height = right_lung_haar_rectangle
cv2.rectangle(color_image, (x, y), (x + width, y + height),
(245, 199, 75), 2)
if use_labels:
cv2.putText(color_image, "HAAR Right", (x + 5, y + 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (245, 199, 75),
1)
if left_lung_haar_rectangle is not None:
x, y, width, height = left_lung_haar_rectangle
cv2.rectangle(color_image, (x, y), (x + width, y + height),
(245, 199, 75), 2)
if use_labels:
cv2.putText(color_image, "HAAR Left", (x + 5, y + 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (245, 199, 75),
1)
cv2.imshow("lungs-finder", color_image)
found_lungs = lf.get_lungs(scaled_image)
if found_lungs is not None:
cv2.imshow("Found lungs", found_lungs)
code = cv2.waitKey(0)
while code not in [2, 3, 27, 32]:
code = cv2.waitKey(0)
if code == 27:
exit(0)
elif code in [3, 32]:
j += 1
else:
if j > 0:
j -= 1
else:
if i > 0:
i -= 2
i += 1