def main():
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-m", "--map", required=False, help="Path to the map of the parking lot")
ap.add_argument("-mo", "--model", required=False, help="Path to model")
args = vars(ap.parse_args())
map_file = args['map']
model_path = args['model']
model_path = os.path.join(model_path, 'model.ckpt')
model_dir, model_filename = os.path.split(model_path)
uacj_images_path = 'C:\\Eduardo\\tesis\\datasets\\uacj'
error_filename = 'uacj_{}_test.json'.format(os.path.splitext(model_filename)[0])
if not os.path.isdir(os.path.join(model_dir, 'test_info')):
os.mkdir(os.path.join(model_dir, 'test_info'))
error_path = os.path.join(model_dir, 'test_info', error_filename)
if os.path.isfile(error_path):
print('This test was already made')
return
images_path = get_images_path(uacj_images_path)
test_all_images = TestAllImages(images_path, model_filename, map_file, model_path, 'psv1', time_step=5)
error_info = test_all_images.testAccuracy()
with open(error_path, 'w') as efile:
json.dump(error_info, efile)
def main():
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-s",
"--scale",
required=False,
default=3,
help="The scale where the image can be better managed")
ap.add_argument("-i", "--image", required=True, help="Initial image")
args = vars(ap.parse_args())
scale = float(args['scale'])
initial_image = args['image']
uacj_images_path = 'C:\\Eduardo\\tesis\\datasets\\uacj'
# uacj_images_path = 'C:\\Eduardo\\ProyectoFinal\\Pruebas_UACJ'
images_path = get_images_path(uacj_images_path)
if initial_image is not None:
try:
current_image_i = images_path.index(initial_image)
except:
print('The image given doesnt exist')
return
else:
current_image_i = 0
image_path = images_path[current_image_i]
# load the image, clone it, and setup the mouse callback function
image = cv2.imread(image_path)
cv2.namedWindow("image")
map_file = 'map_points_crop_rectangle_2.txt'
map = []
if os.path.isfile(map_file):
with open(map_file, 'r') as filehandle:
map1 = json.load(filehandle)
for info in map1:
info["rectangle"] = [
tuple([x for x in l]) for l in info["rectangle"]
]
info["angle"] = float(info["angle"])
map.append(info)
for m in map:
rectangle = m['rectangle']
fixed_rectangle = []
for p in rectangle:
p = (int(p[0] / scale), int(p[1] / scale))
fixed_rectangle.append(p)
m['rectangle_scaled'] = fixed_rectangle
define_states = DefineStates(image=image,
image_path=image_path,
map=map,
scale=scale,
angle=-1)
cv2.setMouseCallback("image", click_and_crop, define_states)
functionality = setFunctionality(define_states, [])
# keep looping until the 'q' key is pressed
while True:
key = cv2.waitKey(1) & 0xFF
for f in functionality:
if key == ord(f['key']):
if '_callback' in f:
if 'param' in f:
f['_callback'](f['param'])
else:
f['_callback']()
if key == ord("b"):
current_image_i -= 1
if current_image_i < 0:
current_image_i = len(images_path) - 1
image_path = images_path[current_image_i]
image = cv2.imread(image_path)
define_states.saveStates()
last_states = define_states.states
define_states = DefineStates(image=image,
image_path=image_path,
map=map,
angle=define_states.angle,
scale=scale)
functionality = setFunctionality(define_states, last_states)
cv2.setMouseCallback("image", click_and_crop, define_states)
if key == ord("n"):
current_image_i += 1
if current_image_i >= len(images_path):
current_image_i = 0
image_path = images_path[current_image_i]
print(image_path)
image = cv2.imread(image_path)
define_states.saveStates()
last_states = define_states.states
define_states = DefineStates(image=image,
image_path=image_path,
map=map,
angle=define_states.angle,
scale=scale)
functionality = setFunctionality(define_states, last_states)
cv2.setMouseCallback("image", click_and_crop, define_states)
if key == ord("x"):
break
define_states.showImage()
define_states.saveStates()
def main():
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i",
"--image",
required=False,
help="Path to the image",
default='29_07\\image28-11-2018_19-19-19.jpg')
ap.add_argument("-s",
"--scale",
required=False,
default=3,
help="The scale where the image can be better managed")
args = vars(ap.parse_args())
#uacj_images_path = 'C:\\Eduardo\\ProyectoFinal\\Pruebas_UACJ'
scale = float(args['scale'])
uacj_images_path = 'C:\\Eduardo\\tesis\\datasets\\uacj'
image_path = os.path.join(uacj_images_path, args["image"])
images_path = get_images_path(uacj_images_path)
image_path = images_path[0]
# load the image, clone it, and setup the mouse callback function
image = cv2.imread(image_path)
cv2.namedWindow("image")
map_file = 'map_points_crop_rectangle_2.txt'
map = []
if os.path.isfile(map_file):
with open(map_file, 'r') as filehandle:
map1 = json.load(filehandle)
for info in map1:
info["rectangle"] = [
tuple([x for x in l]) for l in info["rectangle"]
]
info["angle"] = float(info["angle"])
map.append(info)
for m in map:
rectangle = m['rectangle']
fixed_rectangle = []
for p in rectangle:
p = (int(p[0] / scale), int(p[1] / scale))
fixed_rectangle.append(p)
m['rectangle'] = fixed_rectangle
crop_rectangle = CropRectangles(image=image,
map=map,
scale=scale,
angle=-1)
cv2.setMouseCallback("image", click_and_crop, crop_rectangle)
functionality = set_functionality(crop_rectangle)
# keep looping until the 'q' key is pressed
while True:
key = cv2.waitKey(1) & 0xFF
# if the 'c' key is pressed, break from the loop
if key != 255 and crop_rectangle.getLetter(key):
crop_rectangle.show_image()
continue
for f in functionality:
if key == ord(f['key']):
if '_callback' in f:
if 'param' in f:
f['_callback'](f['param'])
else:
f['_callback']()
if key == ord("c"):
saveMap(map, map_file, scale)
if key == ord("x"):
break
if key == ord("j"):
image_path = random.choice(images_path)
# load the image, clone it, and setup the mouse callback function
image = cv2.imread(image_path)
crop_rectangle = CropRectangles(image=image,
map=map,
angle=crop_rectangle.angle,
scale=scale)
functionality = set_functionality(crop_rectangle)
cv2.setMouseCallback("image", click_and_crop, crop_rectangle)
crop_rectangle.show_image()
saveMap(map, map_file, scale)