def load_from_json(self, filename):
"Load all parameters of the dataset from a JSON file."
with open(filename) as f:
config = json.load(f)
self.classes = config["classes"]
for data in config["images"]:
self.images.append(Image.load_from_json_data(self.classes, data))
def load_from_json(self, filename):
"Load all parameters of the dataset from a JSON file."
with open(filename) as f:
config = json.load(f)
self.classes = config['classes']
for data in config['images']:
self.images.append(Image.load_from_json_data(self.classes, data))
def test_get_det_gt(self):
image = Image.load_from_json_data(self.classes, self.data)
objects_table = Table(
np.array([[0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 0, 0],
[2, 2, 2, 2, 2, 0, 0]]), self.columns)
assert (image.get_objects() == objects_table)
data = self.data.copy()
data['objects'][0]['diff'] = 1
data['objects'][1]['trun'] = 1
image = Image.load_from_json_data(self.classes, data)
objects_table = Table(
np.array([[0, 0, 0, 0, 0, 1, 0], [1, 1, 1, 1, 1, 0, 1],
[2, 2, 2, 2, 2, 0, 0]]), self.columns)
assert (image.get_objects(with_diff=True,
with_trun=True) == objects_table)
objects_table = Table(
np.array([[1, 1, 1, 1, 1, 0, 1], [2, 2, 2, 2, 2, 0, 0]]),
self.columns)
assert (image.get_objects(with_diff=False,
with_trun=True) == objects_table)
# this should be default behavior
assert (image.get_objects() == objects_table)
objects_table = Table(np.array([[2, 2, 2, 2, 2, 0, 0]]), self.columns)
assert (image.get_objects(with_diff=False,
with_trun=False) == objects_table)
objects_table = Table(
np.array([[0, 0, 0, 0, 0, 1, 0], [2, 2, 2, 2, 2, 0, 0]]),
self.columns)
assert (image.get_objects(with_diff=True,
with_trun=False) == objects_table)
# What if everything is filtered out?
data['objects'] = data['objects'][:-1]
objects_table = Table(
np.array([[0, 0, 0, 0, 0, 1, 0], [1, 1, 1, 1, 1, 0, 1]]),
self.columns)
image = Image.load_from_json_data(self.classes, data)
assert (image.get_objects(with_diff=True,
with_trun=True) == objects_table)
assert (image.get_objects(with_diff=False,
with_trun=False).shape[0] == 0)
def test_load_json_data(self):
image = Image.load_from_json_data(self.classes, self.data)
assert (image.width == 640 and image.height == 480)
assert (image.classes == ['A', 'B', 'C'])
assert (image.name == 'test_image')
objects_table = Table(
np.array([[0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 0, 0],
[2, 2, 2, 2, 2, 0, 0]]), self.columns)
assert (image.objects_table == objects_table)
def test_get_det_gt(self):
image = Image.load_from_json_data(self.classes,self.data)
objects_table = Table(np.array([
[0,0,0,0,0,0,0],
[1,1,1,1,1,0,0],
[2,2,2,2,2,0,0]]), self.columns)
assert(image.get_objects() == objects_table)
data = self.data.copy()
data['objects'][0]['diff'] = 1
data['objects'][1]['trun'] = 1
image = Image.load_from_json_data(self.classes,data)
objects_table = Table(np.array([
[0,0,0,0,0,1,0],
[1,1,1,1,1,0,1],
[2,2,2,2,2,0,0]]), self.columns)
assert(image.get_objects(with_diff=True,with_trun=True) == objects_table)
objects_table = Table(np.array([
[1,1,1,1,1,0,1],
[2,2,2,2,2,0,0]]),self.columns)
assert(image.get_objects(with_diff=False,with_trun=True) == objects_table)
# this should be default behavior
assert(image.get_objects() == objects_table)
objects_table = Table(np.array([
[2,2,2,2,2,0,0]]),self.columns)
assert(image.get_objects(with_diff=False,with_trun=False) == objects_table)
objects_table = Table(np.array([
[0,0,0,0,0,1,0],
[2,2,2,2,2,0,0]]), self.columns)
assert(image.get_objects(with_diff=True,with_trun=False) == objects_table)
# What if everything is filtered out?
data['objects'] = data['objects'][:-1]
objects_table = Table(np.array([
[0,0,0,0,0,1,0],
[1,1,1,1,1,0,1]]), self.columns)
image = Image.load_from_json_data(self.classes,data)
assert(image.get_objects(with_diff=True,with_trun=True) == objects_table)
assert(image.get_objects(with_diff=False,with_trun=False).shape[0] == 0)
def test_load_json_data(self):
image = Image.load_from_json_data(self.classes,self.data)
assert(image.width == 640 and image.height == 480)
assert(image.classes == ['A','B','C'])
assert(image.name == 'test_image')
objects_table = Table(np.array([
[0,0,0,0,0,0,0],
[1,1,1,1,1,0,0],
[2,2,2,2,2,0,0]]), self.columns)
assert(image.objects_table == objects_table)
def test_get_cls_counts_and_gt(self):
data = self.data.copy()
image = Image.load_from_json_data(self.classes, data)
assert (np.all(image.get_cls_counts() == np.array([1, 1, 1])))
assert (np.all(image.get_cls_gt() == np.array([True, True, True])))
assert (image.contains_class('A') == True)
assert (image.contains_class('B') == True)
data['objects'][0]['class'] = 'B'
image = Image.load_from_json_data(self.classes, data)
# doesn't actually have to be Series, can be ndarray for comparison
assert (np.all(image.get_cls_counts() == np.array([0, 2, 1])))
assert (np.all(image.get_cls_gt() == np.array([False, True, True])))
assert (image.contains_class('A') == False)
assert (image.contains_class('B') == True)
data['objects'] = []
image = Image.load_from_json_data(self.classes, data)
assert (np.all(image.get_cls_counts() == np.array([0, 0, 0])))
assert (np.all(image.get_cls_gt() == np.array([False, False, False])))
assert (image.contains_class('A') == False)
assert (image.contains_class('B') == False)
def test_get_cls_counts_and_gt(self):
data = self.data.copy()
image = Image.load_from_json_data(self.classes,data)
assert(np.all(image.get_cls_counts() == np.array([1,1,1])))
assert(np.all(image.get_cls_gt() == np.array([True,True,True])))
assert(image.contains_class('A') == True)
assert(image.contains_class('B') == True)
data['objects'][0]['class'] = 'B'
image = Image.load_from_json_data(self.classes,data)
# doesn't actually have to be Series, can be ndarray for comparison
assert(np.all(image.get_cls_counts() == np.array([0,2,1])))
assert(np.all(image.get_cls_gt() == np.array([False,True,True])))
assert(image.contains_class('A') == False)
assert(image.contains_class('B') == True)
data['objects'] = []
image = Image.load_from_json_data(self.classes,data)
assert(np.all(image.get_cls_counts() == np.array([0,0,0])))
assert(np.all(image.get_cls_gt() == np.array([False,False,False])))
assert(image.contains_class('A') == False)
assert(image.contains_class('B') == False)
