def save(dt0: datetime):
global dict_path_csv_datetime, dict_info
dict_info["last_looked"] = str(dt0)
dict_info["shape_img"] = str(img_size_info[1]) + "," + str(
img_size_info[0])
detect.save_csv_data(path_csv_current, dict_info)
dict_path_csv_datetime[path_csv_current] = dt0
def conv9():
detect_cv = detect.FaceDetectorCV()
detect_dnn = detect.FaceDetectorDNN(".")
path_dir_root = "/home/nobuyuki/project/face/rect_manual"
for path_csv in glob.glob(path_dir_root + "/**/*.csv", recursive=True):
dict_data = detect.get_csv_data(path_csv)
bnwe_md5 = os.path.basename(path_csv).split(".", 1)[0]
path_dir = path_csv.rsplit("/", 1)[0]
ext = ".png"
if not os.path.isfile(path_dir + "/" + bnwe_md5 + ext):
ext = ".jpg"
path_img = path_dir + "/" + bnwe_md5 + ext
# print(path_img)
img = cv2.imread(path_img)
#### reject image if you don't like
rect_cv2 = detect_cv.get_one_face(img)
rect_dnn = detect_dnn.get_one_face(img)
# print(rect_dnn)
####
if rect_cv2 is not None:
dict_data["rect_face_cv"] = str(rect_cv2[0]) + "," + str(
rect_cv2[1]) + "," + str(rect_cv2[2]) + "," + str(rect_cv2[3])
if rect_dnn is not None:
dict_data["rect_face_dnn"] = str(rect_dnn[0]) + "," + str(
rect_dnn[1]) + "," + str(rect_dnn[2]) + "," + str(rect_dnn[3])
detect.save_csv_data(path_csv, dict_data)
def conv3():
key_old = "face_rect"
key_new = "rect_face_manual"
for path_csv in glob.glob("/Volumes/PortableHDD/face/rect_manual/*.csv"):
# print(path_csv)
dict_data = detect.get_csv_data(path_csv)
detect.swap_keyword(key_old, key_new, dict_data)
print(dict_data)
detect.save_csv_data(path_csv, dict_data)
def conv11():
#path_dir_root = "/home/nobuyuki/project/face/rect_manual"
#path_dir_root = "/Volumes/PortableHDD/rect_manual"
path_dir_root = "/Volumes/PortableHDD/umet55"
for path_csv in glob.glob(path_dir_root + "/**/*.csv", recursive=True):
dict_data = detect.get_csv_data(path_csv)
bnwe_md5 = os.path.basename(path_csv).split(".", 1)[0]
path_dir = path_csv.rsplit("/", 1)[0]
ext = ".png"
if not os.path.isfile(path_dir + "/" + bnwe_md5 + ext):
ext = ".jpg"
path_img = path_dir + "/" + bnwe_md5 + ext
img = cv2.imread(path_img)
print(path_csv, img.shape)
dict_data["shape_img"] = str(img.shape[0]) + "," + str(img.shape[1])
detect.save_csv_data(path_csv, dict_data)
def conv7():
path_dir_root = "/Volumes/PortableHDD/face/rect_cv"
hex = [str(format(i, 'x')) for i in range(0, 16)]
print(hex)
for ch in hex:
if not os.path.isdir(path_dir_root + "/" + ch):
os.mkdir(path_dir_root + "/" + ch)
for path_csv in glob.glob(path_dir_root + "/**/*.csv", recursive=True):
dict_data = detect.get_csv_data(path_csv)
bn = os.path.basename(path_csv)
bnwe = bn.rsplit(".", 1)[0]
path_dir_img = os.path.dirname(path_csv)
ext_img = ".png"
if not os.path.isfile(path_dir_img + "/" + bnwe + ext_img):
ext_img = ".jpg"
dict_data["url_name"] = bnwe + ext_img
detect.save_csv_data(path_csv, dict_data)
path_img = path_dir_img + "/" + bnwe + ext_img
assert os.path.isfile(path_img)
bnwe_md5 = detect.getMD5(path_img)
print(bn, bnwe_md5)
def conv12(path_dir_root):
is_cuda = torch.cuda.is_available()
if is_cuda:
print("using GPU")
else:
print("using CPU")
net_d, net_c, net_l = detect.load_detection_network(is_cuda, '.')
######
print("select good and bad:", path_dir_root)
list_path_img = []
list_path_img = glob.glob(path_dir_root + '/xinbox/*.jpg',
recursive=True) + list_path_img
list_path_img = glob.glob(path_dir_root + '/xinbox/*.png',
recursive=True) + list_path_img
print("there is ", len(list_path_img), "images")
for path_img in list_path_img:
if not os.path.isfile(path_img):
continue
npImg = cv2.imread(path_img)
if npImg is None:
continue
####
print(npImg.shape[0], npImg.shape[1])
list_rect_dnn0 = detect.detect_face_dnn_multires(net_d,
net_c,
net_l,
npImg,
threshold_prob=0.6)
for rect in list_rect_dnn0:
detect.highlight_rect(npImg, rect, (255, 255, 0), width=1)
list_rect_dnn = detect.marge_rects(list_rect_dnn0)
for rect in list_rect_dnn:
detect.highlight_rect(npImg, rect, (0, 255, 255), width=2)
cv2.imshow('img', npImg)
key = cv2.waitKey(100)
ikey = int(key)
print(ikey)
if ikey == 113:
exit()
'''
if key == 8: # delete key
path_img_new = path_dir_root + '/xtrash/' + os.path.basename(path_img)
print("move_to_trash")
shutil.move(path_img, path_img_new)
continue
if ikey != 32: #space key
print("this image is bad. do nothing")
continue
'''
### md5
bnwe_md5 = detect.getMD5(path_img)
ext = path_img.rsplit(".", 1)[1]
dir_dist = path_dir_root + "/" + str(bnwe_md5[0])
path_img_new = dir_dist + "/" + bnwe_md5 + "." + ext
print(path_img_new, dir_dist)
if os.path.isfile(path_img_new):
print("there is already one:")
os.remove(path_img)
continue
### register image
print("found new iamge:", path_img, path_img_new)
shutil.move(path_img, path_img_new)
dict_data = {}
dict_data["url_name"] = os.path.basename(path_img)
dict_data["shape_img"] = str(npImg.shape[0]) + "," + str(
npImg.shape[1])
if len(list_rect_dnn) > 0:
str_csv = detect.get_str_csv_list_rect(list_rect_dnn)
dict_data["rect_face_dnn"] = str_csv
detect.save_csv_data(dir_dist + "/" + bnwe_md5 + ".csv", dict_data)