def __init__(
self,
ip_address,
port,
api_key,
timeout,
target,
confidence,
save_file_folder,
camera_entity,
name=None,
):
"""Init with the API key and model id."""
super().__init__()
self._dsobject = ds.DeepstackObject(ip_address, port, api_key, timeout)
self._target = target
self._confidence = confidence
self._camera = camera_entity
if name:
self._name = name
else:
camera_name = split_entity_id(camera_entity)[1]
self._name = "{} {}".format(CLASSIFIER, camera_name)
self._state = None
self._targets_confidences = []
self._predictions = {}
if save_file_folder:
self._save_file_folder = save_file_folder
def __init__(
self,
ip_address,
port,
api_key,
timeout,
target,
confidence,
save_file_folder,
save_timestamped_file,
camera_entity,
name=None,
):
"""Init with the API key and model id."""
super().__init__()
self._dsobject = ds.DeepstackObject(ip_address, port, api_key, timeout)
self._target = target
self._confidence = confidence
self._camera = camera_entity
if name:
self._name = name
else:
camera_name = split_entity_id(camera_entity)[1]
self._name = "deepstack_object_{}".format(camera_name)
self._state = None
self._targets_confidences = [None] * len(self._target)
self._targets_found = [0] * len(self._target)
self._predictions = {}
self._summary = {}
self._last_detection = None
self._image_width = None
self._image_height = None
if save_file_folder:
self._save_file_folder = save_file_folder
self._save_timestamped_file = save_timestamped_file
def test_DeepstackObject_detect_timeout():
"""Test a timeout. THIS SHOULD FAIL"""
with pytest.raises(ds.DeepstackException) as excinfo:
with requests_mock.Mocker() as mock_req:
mock_req.post(OBJ_URL, exc=requests.exceptions.ConnectTimeout)
dsobject = ds.DeepstackObject(MOCK_IP_ADDRESS, MOCK_PORT)
dsobject.detect(MOCK_BYTES)
assert False
assert "SHOULD FAIL" in str(excinfo.value)
def test_DeepstackObject_detect():
"""Test a good response from server."""
with requests_mock.Mocker() as mock_req:
mock_req.post(OBJ_URL,
status_code=ds.HTTP_OK,
json=MOCK_OBJECT_DETECTION_RESPONSE)
dsobject = ds.DeepstackObject(MOCK_IP_ADDRESS, MOCK_PORT)
predictions = dsobject.detect(MOCK_BYTES)
assert predictions == MOCK_OBJECT_PREDICTIONS
def __init__(self, config: Config):
self._config = config
self._detector = ds.DeepstackObject(
ip=config.host,
port=config.port,
api_key=config.api_key,
timeout=config.timeout,
min_confidence=0.1,
custom_model=config.custom_model,
)
def __init__(
self,
ip_address,
port,
api_key,
timeout,
targets,
confidence,
roi_y_min,
roi_x_min,
roi_y_max,
roi_x_max,
show_boxes,
save_file_folder,
save_timestamped_file,
camera_entity,
name=None,
):
"""Init with the API key and model id."""
super().__init__()
self._dsobject = ds.DeepstackObject(ip_address, port, api_key, timeout)
self._targets = targets
self._confidence = confidence
self._camera = camera_entity
if name:
self._name = name
else:
camera_name = split_entity_id(camera_entity)[1]
self._name = "deepstack_object_{}".format(camera_name)
self._state = None
self._objects = [] # The parsed raw data
self._targets_found = []
self._summary = {}
self._roi_dict = {
"y_min": roi_y_min,
"x_min": roi_x_min,
"y_max": roi_y_max,
"x_max": roi_x_max,
}
self._show_boxes = show_boxes
self._last_detection = None
self._image_width = None
self._image_height = None
self._save_file_folder = save_file_folder
self._save_timestamped_file = save_timestamped_file
def __init__(
self,
ip_address,
port,
api_key,
timeout,
custom_model,
targets,
confidence,
roi_y_min,
roi_x_min,
roi_y_max,
roi_x_max,
scale,
show_boxes,
save_file_folder,
save_file_format,
save_timestamped_file,
always_save_latest_file,
camera_entity,
name=None,
):
"""Init with the API key and model id."""
super().__init__()
self._dsobject = ds.DeepstackObject(
ip=ip_address,
port=port,
api_key=api_key,
timeout=timeout,
min_confidence=MIN_CONFIDENCE,
custom_model=custom_model,
)
self._custom_model = custom_model
self._confidence = confidence
self._summary = {}
self._targets = targets
for target in self._targets:
if CONF_CONFIDENCE not in target.keys():
target.update({CONF_CONFIDENCE: self._confidence})
self._targets_names = [target[CONF_TARGET] for target in targets
] # can be a name or a type
self._camera = camera_entity
if name:
self._name = name
else:
camera_name = split_entity_id(camera_entity)[1]
self._name = "deepstack_object_{}".format(camera_name)
self._state = None
self._objects = [] # The parsed raw data
self._targets_found = []
self._last_detection = None
self._roi_dict = {
"y_min": roi_y_min,
"x_min": roi_x_min,
"y_max": roi_y_max,
"x_max": roi_x_max,
}
self._scale = scale
self._show_boxes = show_boxes
self._image_width = None
self._image_height = None
self._save_file_folder = save_file_folder
self._save_file_format = save_file_format
self._always_save_latest_file = always_save_latest_file
self._save_timestamped_file = save_timestamped_file
self._always_save_latest_file = always_save_latest_file
self._image = None
)
ROI_DICT = {
"x_min": ROI_X_MIN,
"y_min": ROI_Y_MIN,
"x_max": ROI_X_MAX,
"y_max": ROI_Y_MAX,
}
## Process image
if img_file_buffer is not None:
pil_image = Image.open(img_file_buffer)
else:
pil_image = Image.open(TEST_IMAGE)
dsobject = ds.DeepstackObject(DEEPSTACK_IP, DEEPSTACK_PORT, DEEPSTACK_API_KEY,
DEEPSTACK_TIMEOUT)
predictions = process_image(pil_image, dsobject)
objects = utils.get_objects(predictions, pil_image.width, pil_image.height)
all_objects_names = set([obj["name"] for obj in objects])
# Filter objects for display
objects = [obj for obj in objects if obj["confidence"] > CONFIDENCE_THRESHOLD]
objects = [obj for obj in objects if obj["name"] in CLASSES_TO_INCLUDE]
objects = [
obj for obj in objects if utils.object_in_roi(ROI_DICT, obj["centroid"])
]
# Draw object boxes
draw = ImageDraw.Draw(pil_image)
for obj in objects:
options=const.CLASSES,
default=const.CLASSES,
)
## Process image
if img_file_buffer is not None:
pil_image = Image.open(img_file_buffer)
else:
pil_image = Image.open(OBJECT_TEST_IMAGE)
if not DEEPSTACK_CUSTOM_MODEL:
dsobject = ds.DeepstackObject(
ip=DEEPSTACK_IP,
port=DEEPSTACK_PORT,
api_key=DEEPSTACK_API_KEY,
timeout=DEEPSTACK_TIMEOUT,
min_confidence=MIN_CONFIDENCE_THRESHOLD,
)
else:
dsobject = ds.DeepstackObject(
ip=DEEPSTACK_IP,
port=DEEPSTACK_PORT,
api_key=DEEPSTACK_API_KEY,
timeout=DEEPSTACK_TIMEOUT,
min_confidence=MIN_CONFIDENCE_THRESHOLD,
custom_model=DEEPSTACK_CUSTOM_MODEL,
)
predictions = process_image_object(pil_image, dsobject)
objects = utils.get_objects(predictions, pil_image.width, pil_image.height)
