def save_images_with_cv(source_dir_name,
target_dir_name,
max_dim=None,
recursive=False):
if not os.path.isdir(target_dir_name):
file_helper.create_dir(target_dir_name)
i = 0
for fn in file_helper.enumerate_files(source_dir_name,
recursive=recursive):
try:
i += 1
print("{} - {}".format(i, fn), end=end_txt)
dir_name, name, extension = file_helper.get_file_name_extension(fn)
if string_helper.equals_case_insensitive(extension, ".txt"):
new_fn = file_helper.path_join(target_dir_name,
name + extension)
file_helper.copy_file(fn, new_fn)
else:
mat = cv2.imread(fn)
if max_dim is not None:
mat = image_helper.resize_if_larger(mat, max_dim)
new_fn = file_helper.path_join(target_dir_name, name + ".jpg")
cv2.imwrite(new_fn, mat)
except Exception as e:
print("error - save_images_with_cv: {}".format(fn))
print("save_images_with_cv finished")
def get_frames(self):
# count = 0
self.__stream.start()
try:
skip = 0
while True:
frame = self.__stream.read()
if frame is None:
break
if self._max_dim is not None:
frame = resize_if_larger(frame, self._max_dim)
if skip > 0:
skip = skip - 1
else:
yield frame
k = cv2.waitKey(1) & 0xFF
if k == ord("q"):
break
elif k == ord("s"):
skip = 10
except StopIteration:
pass
finally:
self.stop()
def get_frames(self):
# count = 0
try:
skip = 0
while self._capture.isOpened():
ok, frame = self._capture.read()
if frame is None:
break
if self._max_dim is not None and self._max_dim > 0:
frame = resize_if_larger(frame, self._max_dim)
if self._mirror:
frame = cv2.flip(frame, 1)
if skip > 0:
skip = skip - 1
else:
yield frame
k = cv2.waitKey(1) & 0xFF
if k == ord("q"):
break
elif k == ord("s"):
skip = 10
except StopIteration:
pass
finally:
cv2.destroyAllWindows()
def get_frames1(self):
# import required libraries
from vidgear.gears import CamGear
import cv2
# Add YouTube Video URL as input source (for e.g https://youtu.be/bvetuLwJIkA)
# and enable Stream Mode (`stream_mode = True`)
stream = CamGear(source=self.__url, stream_mode=True,
logging=True).start()
skip = 0
# loop over
while True:
# read frames from stream
frame = stream.read()
# check for frame if Nonetype
if frame is None:
break
if frame is None:
break
if self._max_dim is not None:
frame = resize_if_larger(frame, self._max_dim)
if skip > 0:
skip = skip - 1
else:
yield frame
k = cv2.waitKey(1) & 0xFF
if k == ord("q"):
break
elif k == ord("s"):
skip = 10
# close output window
cv2.destroyAllWindows()
# safely close video stream
stream.stop()
def combine_classes(class_items,
out_images_dir,
out_labels_dir,
out_classes_txt_fn,
out_style="yolo"):
# a typical class_item
# {
# "class_name": "vehicle license plate",
# "dirs":
# [
# {
# "images": "C:/_koray/train_datasets/yolo_oidv6_class0/vehicle_registration_plate",
# "labels": "C:/_koray/train_datasets/yolo_oidv6_class0/vehicle_registration_plate"
# },
# {
# "images": "C:/_koray/train_datasets/yolo_misc/vehicle_registration_plate/class0",
# "labels": "C:/_koray/train_datasets/yolo_misc/vehicle_registration_plate/class0"
# }
# ],
# "resize_style": None, "if_larger" or "crop" - if "crop" -> make the image unique, don't combine, other combine with other classes
# "image_size": 640, - if None no resize, combine all
# "style": "yolo"
# }
class_names = []
if out_style == "yolo":
if not os.path.isdir(out_images_dir):
file_helper.create_dir(out_images_dir)
if not os.path.isdir(out_labels_dir):
file_helper.create_dir(out_labels_dir)
if os.path.isfile(out_classes_txt_fn):
for class_name in file_helper.read_lines(out_classes_txt_fn):
class_names.append(class_name)
else:
raise Exception("Bad out_style: " + out_style)
for class_item in class_items:
class_name = class_item["class_name"]
resize_style = class_item["resize_style"]
image_size = class_item["image_size"]
if image_size is not None:
image_size_txt = "{}_{}".format(image_size[0], image_size[1])
else:
image_size_txt = None
input_style = class_item["input_style"]
if class_name in class_names:
class_index = class_names.index(class_name)
else:
class_index = len(class_names)
class_names.append(class_name)
file_helper.append_line(out_classes_txt_fn, class_name)
i = 0
for dir_item in class_item["dirs"]:
images_dir = dir_item["images"]
labels_dir = dir_item["labels"]
if input_style == "yolo":
for label_fn in file_helper.enumerate_files(
labels_dir, wildcard_pattern="*.txt"):
try:
_dir_name, name, _extension = file_helper.get_file_name_extension(
label_fn)
i += 1
print("{} - {}".format(i, label_fn), end=end_txt)
for line in file_helper.read_lines(label_fn):
line_items = line.split(" ")
cx_norm = float(line_items[1])
cy_norm = float(line_items[2])
w_norm = float(line_items[3])
h_norm = float(line_items[4])
line_items[0] = str(class_index)
out_lbl_fn = None
out_img_fn = None
mat = None
# for image_fn in file_helper.enumerate_files(images_dir, wildcard_pattern=name + ".*"):
image_fn = find_image_file(images_dir, name)
if image_fn is not None:
_dir_name, _name, extension = file_helper.get_file_name_extension(
image_fn)
if extension != ".txt":
try:
mat = cv2.imread(image_fn)
except Exception as e:
print(
'Error reading image file: {} msg:{}'
.format(image_fn, str(e)))
if mat is not None:
if image_size is None or resize_style is None:
out_img_fn = file_helper.path_join(
out_images_dir, name + ".jpg")
out_lbl_fn = file_helper.path_join(
out_labels_dir, name + ".txt")
elif resize_style == "if_larger":
out_img_fn = file_helper.path_join(
out_images_dir, name + "_" +
image_size_txt + ".jpg")
out_lbl_fn = file_helper.path_join(
out_labels_dir, name + "_" +
image_size_txt + ".txt")
mat = image_helper.resize_if_larger(
mat,
max(image_size[0],
image_size[1]))
elif resize_style == "crop":
new_name = file_helper.get_unique_file_name(
)
out_img_fn = file_helper.path_join(
out_images_dir, name +
"_crop_" + new_name + ".jpg")
out_lbl_fn = file_helper.path_join(
out_labels_dir, name +
"_crop_" + new_name + ".txt")
mat, cx, cy, w, h = crop_rect(
mat, cx_norm, cy_norm, w_norm,
h_norm, image_size)
line_items[1] = str(cx)
line_items[2] = str(cy)
line_items[3] = str(w)
line_items[4] = str(h)
else:
raise Exception(
"Bad resize_style: " +
resize_style)
else:
raise Exception("Cannot find image file")
if out_lbl_fn is not None:
line = string_helper.join(line_items, " ")
if os.path.isfile(out_lbl_fn):
file_helper.append_line(out_lbl_fn, line)
else:
file_helper.write_lines(out_lbl_fn, [line])
if out_img_fn is not None and mat is not None:
if not os.path.isfile(out_img_fn):
cv2.imwrite(out_img_fn, mat)
except Exception as e:
print('Error - file:{} msg:{}'.format(
label_fn, str(e)))
else:
raise Exception("Bad input_style: " + out_style)