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Load model and submit for inference.

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Sucessfully load model and initialize OpenVino engine with either CPU or GPU as device.
Does not parse results for objects.
This commit is contained in:
Nate Meyer 2022-08-26 02:00:11 -04:00
parent 4b675692ec
commit cf03f62088
3 changed files with 41 additions and 69 deletions
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1
docker/install_deps.sh
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@ -53,6 +53,7 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then
echo 'deb http://deb.debian.org/debian testing main non-free' >/etc/apt/sources.list.d/debian-testing.list echo 'deb http://deb.debian.org/debian testing main non-free' >/etc/apt/sources.list.d/debian-testing.list
apt-get -qq update apt-get -qq update
apt-get -qq install --no-install-recommends --no-install-suggests -y \ apt-get -qq install --no-install-recommends --no-install-suggests -y \
intel-opencl-icd \
mesa-va-drivers libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1 radeontop intel-gpu-tools mesa-va-drivers libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1 radeontop intel-gpu-tools
rm -f /etc/apt/sources.list.d/debian-testing.list rm -f /etc/apt/sources.list.d/debian-testing.list
fi fi

105
frigate/detectors/openvino.py
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@ -10,79 +10,48 @@ logger = logging.getLogger(__name__)
class OvDetector(DetectionApi): class OvDetector(DetectionApi):
def __init__(self, det_device=None, model_path=None, num_threads=1): def __init__(self, det_device=None, model_path=None, num_threads=1):
self.ovCore = ov.Core() self.ov_core = ov.Core()
self.ovModel = self.ovCore.read_model(model_path) self.ov_model = self.ov_core.read_model(model_path)
self.interpreter = self.ovCore.compile_model( self.interpreter = self.ov_core.compile_model(
model=self.ovModel, device_name=det_device model=self.ov_model, device_name=det_device
) )
logger.info(f"Model Input Shape: {self.interpreter.input().shape}")
self.interpreter.allocate_tensors() logger.info(f"Model Output Shape: {self.interpreter.output().shape}")
self.tensor_input_details = self.interpreter.get_input_details()
self.tensor_output_details = self.interpreter.get_output_details()
def detect_raw(self, tensor_input): def detect_raw(self, tensor_input):
self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input) tensor_transpose = np.reshape(tensor_input, self.interpreter.input().shape)
self.interpreter.invoke()
boxes = self.interpreter.tensor(self.tensor_output_details[0]["index"])()[0] infer_request = self.interpreter.create_infer_request()
class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0] results = infer_request.infer([tensor_transpose])
scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0]
count = int( # class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0]
self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0] # scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0]
) # count = int(
# self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0]
# # )
# class_ids = results[0, 0, :, 1]
# # class_ids = [0, 0, 1, 1]
# print(class_ids)
# scores = results
# print(scores)
detections = np.zeros((20, 6), np.float32) detections = np.zeros((20, 6), np.float32)
# i = 0
for i in range(count): # for object_detected in results["detection_out"][0, 0, :]:
if scores[i] < 0.4 or i == 20: # if object_detected[2] < 0.1 or i == 20:
break # break
detections[i] = [ # detections.append(
class_ids[i], # [
float(scores[i]), # object_detected[1],
boxes[i][0], # float(object_detected[2]),
boxes[i][1], # object_detected[3],
boxes[i][2], # object_detected[4],
boxes[i][3], # object_detected[5],
] # object_detected[6],
# ]
return detections # )
# i += 1
class GpuOpenVino(DetectionApi):
def __init__(self, det_device=None, model_path=None, num_threads=1):
self.interpreter = tflite.Interpreter(
model_path=model_path or "/cpu_model.tflite", num_threads=3
)
self.interpreter.allocate_tensors()
self.tensor_input_details = self.interpreter.get_input_details()
self.tensor_output_details = self.interpreter.get_output_details()
def detect_raw(self, tensor_input):
self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input)
self.interpreter.invoke()
boxes = self.interpreter.tensor(self.tensor_output_details[0]["index"])()[0]
class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0]
scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0]
count = int(
self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0]
)
detections = np.zeros((20, 6), np.float32)
for i in range(count):
if scores[i] < 0.4 or i == 20:
break
detections[i] = [
class_ids[i],
float(scores[i]),
boxes[i][0],
boxes[i][1],
boxes[i][2],
boxes[i][3],
]
return detections return detections

4
requirements-wheels.txt
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@ -3,7 +3,8 @@ Flask == 2.2.*
imutils == 0.5.* imutils == 0.5.*
matplotlib == 3.6.* matplotlib == 3.6.*
mypy == 0.942 mypy == 0.942
numpy == 1.22.* # numpy == 1.22.*
numpy == 1.19.*
opencv-python-headless == 4.5.5.* opencv-python-headless == 4.5.5.*
paho-mqtt == 1.6.* paho-mqtt == 1.6.*
peewee == 3.15.* peewee == 3.15.*
@ -18,3 +19,4 @@ scipy == 1.8.*
setproctitle == 1.2.* setproctitle == 1.2.*
ws4py == 0.5.* ws4py == 0.5.*
zeroconf == 0.39.4 zeroconf == 0.39.4
openvino == 2022.*