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Detection working with ssdlite_mobilenetv2 FP16 model

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Nate Meyer 2022-08-27 09:45:53 -04:00
parent cf03f62088
commit 6e8c91dd48
1 changed files with 22 additions and 33 deletions
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55
frigate/detectors/openvino.py
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@ -9,49 +9,38 @@ 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_config=None, num_threads=1):
self.ov_core = ov.Core() self.ov_core = ov.Core()
self.ov_model = self.ov_core.read_model(model_path) self.ov_model = self.ov_core.read_model(model_config.path)
self.interpreter = self.ov_core.compile_model( self.interpreter = self.ov_core.compile_model(
model=self.ov_model, device_name=det_device model=self.ov_model, device_name=det_device
) )
logger.info(f"Model Input Shape: {self.interpreter.input().shape}") logger.info(f"Model Input Shape: {self.interpreter.input(0).shape}")
logger.info(f"Model Output Shape: {self.interpreter.output().shape}") logger.info(f"Model Output Shape: {self.interpreter.output(0).shape}")
def detect_raw(self, tensor_input): def detect_raw(self, tensor_input):
tensor_transpose = np.reshape(tensor_input, self.interpreter.input().shape)
infer_request = self.interpreter.create_infer_request() infer_request = self.interpreter.create_infer_request()
results = infer_request.infer([tensor_transpose]) infer_request.infer([tensor_input])
# class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0] results = infer_request.get_output_tensor()
# 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 i = 0
# for object_detected in results["detection_out"][0, 0, :]: for object_detected in results.data[0, 0, :]:
# if object_detected[2] < 0.1 or i == 20: if object_detected[0] != -1:
# break logger.debug(object_detected)
# detections.append( if object_detected[2] < 0.1 or i == 20:
# [ break
# object_detected[1], detections[i] = [
# float(object_detected[2]), object_detected[1], # Label ID
# object_detected[3], float(object_detected[2]), # Confidence
# object_detected[4], object_detected[4], # y_min
# object_detected[5], object_detected[3], # x_min
# object_detected[6], object_detected[6], # y_max
# ] object_detected[5], # x_max
# ) ]
# i += 1 i += 1
return detections return detections