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Changes to pass lint checks

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This commit is contained in:
Anil Ozyalcin 2023-02-16 22:20:35 -08:00
parent 10155d3b3e
commit e7436a413c
1 changed files with 14 additions and 11 deletions
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25
frigate/detectors/plugins/openvino.py
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@ -140,19 +140,20 @@ class OvDetector(DetectionApi):
scores = np.max(output_data[:, 4:], axis=1)
if len(scores) == 0:
return np.zeros((20, 6), np.float32)
scores = np.expand_dims(scores, axis=1)
dets = np.concatenate((output_data, scores), axis=1) # add scores to the last column
dets = dets[dets[:,-1] > 0.5,:] # filter out lines with scores below threshold
ordered = dets[dets[:, -1].argsort()[::-1]][:20] # limit to top 20 scores, descending order
# add scores to the last column
dets = np.concatenate((output_data, scores), axis=1)
# filter out lines with scores below threshold
dets = dets[dets[:, -1] > 0.3, :]
# limit to top 20 scores, descending order
ordered = dets[dets[:, -1].argsort()[::-1]][:20]
detections = np.zeros((20, 6), np.float32)
i = 0
for object_detected in ordered:
if i < 20:
detections[i] = [
np.argmax(object_detected[4:-1]) , # Label ID
np.argmax(object_detected[4:-1]), # Label ID
object_detected[-1], # Confidence
(object_detected[1] - (object_detected[3] / 2))
/ self.h, # y_min
@ -165,14 +166,16 @@ class OvDetector(DetectionApi):
]
i += 1
else:
break
break
return detections
elif self.ov_model_type == ModelTypeEnum.yolov5:
out_tensor = infer_request.get_output_tensor()
output_data = out_tensor.data[0]
conf_mask = (output_data[:, 4] >= 0.5).squeeze()
# filter out lines with scores below threshold
conf_mask = (output_data[:, 4] >= 0.3).squeeze()
output_data = output_data[conf_mask]
ordered = output_data[output_data[:, 4].argsort()[::-1]][:20] # limit to top 20 scores, descending order
# limit to top 20 scores, descending order
ordered = output_data[output_data[:, 4].argsort()[::-1]][:20]
detections = np.zeros((20, 6), np.float32)
i = 0
@ -180,7 +183,7 @@ class OvDetector(DetectionApi):
for object_detected in ordered:
if i < 20:
detections[i] = [
np.argmax(object_detected[5:]) , # Label ID
np.argmax(object_detected[5:]), # Label ID
object_detected[4], # Confidence
(object_detected[1] - (object_detected[3] / 2))
/ self.h, # y_min
@ -194,4 +197,4 @@ class OvDetector(DetectionApi):
i += 1
else:
break
return detections
return detections