def fire_prediction_events(self, predictions_json, confidence):
"""Fire events based on predictions if above confidence threshold."""
for prediction in predictions_json:
if ds.format_confidence(prediction["confidence"]) > confidence:
self.hass.bus.fire(
EVENT_OBJECT_DETECTED,
{
"classifier": CLASSIFIER,
ATTR_ENTITY_ID: self.entity_id,
OBJECT: prediction["label"],
ATTR_CONFIDENCE: ds.format_confidence(prediction["confidence"]),
},
)
def save_image(self, image, predictions_json, target, directory):
"""Save a timestamped image with bounding boxes around targets."""
from PIL import Image, ImageDraw
import io
img = Image.open(io.BytesIO(bytearray(image))).convert("RGB")
draw = ImageDraw.Draw(img)
for prediction in predictions_json:
prediction_confidence = ds.format_confidence(prediction["confidence"])
if (
prediction["label"] == target
and prediction_confidence >= self._confidence
):
draw_box(draw, prediction, str(prediction_confidence))
now = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
latest_save_path = directory + "deepstack_latest_{}.jpg".format(target)
timestamp_save_path = directory + "deepstack_{}_{}.jpg".format(target, now)
try:
img.save(latest_save_path)
img.save(timestamp_save_path)
self.fire_saved_file_event(timestamp_save_path)
_LOGGER.info("Saved bounding box image to %s", timestamp_save_path)
except Exception as exc:
_LOGGER.error("Error saving bounding box image : %s", exc)
def process_image(self, image):
"""Process an image."""
self._state = None
self._targets_confidences = []
self._predictions = {}
try:
self._dsobject.detect(image)
except ds.DeepstackException as exc:
_LOGGER.error("Depstack error : %s", exc)
return
predictions = self._dsobject.predictions.copy()
if len(predictions) > 0:
raw_confidences = ds.get_object_confidences(predictions, self._target)
self._targets_confidences = [
ds.format_confidence(confidence) for confidence in raw_confidences
]
self._state = len(
ds.get_confidences_above_threshold(
self._targets_confidences, self._confidence
)
)
self._predictions = ds.get_objects_summary(predictions)
self.fire_prediction_events(predictions, self._confidence)
if hasattr(self, "_save_file_folder") and self._state > 0:
self.save_image(
image, predictions, self._target, self._save_file_folder
)
def process_image(self, image):
"""Process an image."""
self._image_width, self._image_height = Image.open(
io.BytesIO(bytearray(image))).size
self._state = None
self._targets_confidences = []
self._predictions = {}
self._summary = {}
try:
self._dsobject.detect(image)
except ds.DeepstackException as exc:
_LOGGER.error("Depstack error : %s", exc)
return
self._predictions = self._dsobject.predictions.copy()
if len(self._predictions) > 0:
raw_confidences = ds.get_object_confidences(
self._predictions, self._target)
self._targets_confidences = [
ds.format_confidence(confidence)
for confidence in raw_confidences
]
self._state = len(
ds.get_confidences_above_threshold(self._targets_confidences,
self._confidence))
if self._state > 0:
self._last_detection = dt_util.now().strftime(DATETIME_FORMAT)
self._summary = ds.get_objects_summary(self._predictions)
self.fire_prediction_events(self._predictions, self._confidence)
if hasattr(self, "_save_file_folder") and self._state > 0:
self.save_image(image, self._predictions, self._target,
self._save_file_folder)
def save_image(self, image, predictions, target, directory):
"""Save a timestamped image with bounding boxes around targets."""
img = Image.open(io.BytesIO(bytearray(image))).convert("RGB")
draw = ImageDraw.Draw(img)
for prediction in predictions:
prediction_confidence = ds.format_confidence(
prediction["confidence"])
if (prediction["label"] == target
and prediction_confidence >= self._confidence):
box = get_box(prediction, self._image_width,
self._image_height)
draw_box(
draw,
box,
self._image_width,
self._image_height,
str(prediction_confidence),
)
latest_save_path = directory + "deepstack_latest_{}.jpg".format(target)
timestamp_save_path = directory + "deepstack_{}_{}.jpg".format(
target, self._last_detection.strftime("%Y-%m-%d-%H-%M-%S"))
try:
img.save(latest_save_path)
img.save(timestamp_save_path)
self.fire_saved_file_event(timestamp_save_path)
_LOGGER.info("Saved bounding box image to %s", timestamp_save_path)
except Exception as exc:
_LOGGER.error("Error saving bounding box image : %s", exc)
def fire_prediction_events(self, predictions, confidence):
"""Fire events based on predictions if above confidence threshold."""
for prediction in predictions:
if ds.format_confidence(prediction["confidence"]) > confidence:
box = get_box(prediction, self._image_width,
self._image_height)
self.hass.bus.fire(
EVENT_OBJECT_DETECTED,
{
ATTR_ENTITY_ID:
self.entity_id,
OBJECT:
prediction["label"],
ATTR_CONFIDENCE:
ds.format_confidence(prediction["confidence"]),
BOX:
box,
},
)
def save_image(self, image, predictions, target, directory):
"""Save a timestamped image with bounding boxes around targets."""
img = Image.open(io.BytesIO(bytearray(image))).convert("RGB")
draw = ImageDraw.Draw(img)
for prediction in predictions:
prediction_confidence = ds.format_confidence(prediction["score"])
if (prediction["name"] in target
and prediction_confidence >= self._confidence):
draw_box(
draw,
prediction['box'],
self._image_width,
self._image_height,
text=str(prediction_confidence),
color=RED,
)
latest_save_path = directory + "{}_latest_{}.jpg".format(
self._name, target[0])
img.save(latest_save_path)
def save_image(self, image, predictions, target, directory):
"""Save a timestamped image with bounding boxes around targets."""
img = Image.open(io.BytesIO(bytearray(image))).convert("RGB")
draw = ImageDraw.Draw(img)
for prediction in predictions:
prediction_confidence = ds.format_confidence(
prediction["confidence"])
if (prediction["label"] == target
and prediction_confidence >= self._confidence):
box = get_box(prediction, self._image_width,
self._image_height)
draw_box(
draw,
box,
self._image_width,
self._image_height,
text=str(prediction_confidence),
color=RED,
)
latest_save_path = directory + "{}_latest_{}.jpg".format(
self._name, target)
img.save(latest_save_path)
if self._save_timestamped_file:
timestamp_save_path = directory + "{}_{}_{}.jpg".format(
self._name, target, self._last_detection)
out_file = open(timestamp_save_path, "wb")
img.save(out_file, format="JPEG")
out_file.flush()
os.fsync(out_file)
out_file.close()
self.fire_saved_file_event(timestamp_save_path)
_LOGGER.info("Saved bounding box image to %s", timestamp_save_path)