Forums - detection_score is small when run MobileNet SSD with v1.13.0

Hi

I get dlc model with snpe v1.13.0 following "Example Tutorials->Model Conversion -> MobilenetSSD", then run app to detect a picture,

the detection_score is small， the max is only 0.047451537 .

Could u help me to resolve this problem。

01-01 21:20:54.107 19624 19648 W ClassifyImageTask: output.getKey():Postprocessor/BatchMultiClassNonMaxSuppression_scores
01-01 21:20:54.107 19624 19648 W ClassifyImageTask: ----------------------------------Postprocessor detection_scores:0,
01-01 21:20:54.108 19624 19648 W ClassifyImageTask: scores array:[0.047451537, 0.045016516, 0.04234872, 0.037280537, 0.03516005, 0.034554403, 0.033889897, 0.03270978, 0.030579194, 0.030491576, 0.030363169, 0.02960077, 0.02923276, 0.029092152, 0.029020712, 0.027904972, 0.027860774, 0.027644016, 0.02700325, 0.026978016, 0.026823623, 0.026066652, 0.024427043, 0.024424704, 0.023602612, 0.022090841, 0.022022866, 0.021087155, 0.020823762, 0.020724414, 0.020685662, 0.020259205, 0.020174442, 0.020161139, 0.020033423, 0.019928122, 0.019717976, 0.019147642, 0.018645195, 0.018471656, 0.018439967, 0.018391078, 0.018325279, 0.018218495, 0.018023254, 0.017945955, 0.017694205, 0.017552363, 0.017518418, 0.017478462, 0.017030304, 0.017022755, 0.017002787, 0.016452173, 0.016399756, 0.015928298, 0.015671186, 0.015602691, 0.01557738, 0.015318771, 0.015012533, 0.014995987, 0.014937035, 0.014803228, 0.014532335, 0.014189652, 0.014169502, 0.0140513545, 0.013975311, 0.013884049, 0.013696974, 0.01351327, 0.0133990375, 0.01337515, 0.013326407, 0.013159195, 0.013091592, 0.012999066, 0.012976114, 0.012964185, 0.012778291, 0.01267176, 0.012576585, 0.01255103, 0.012398688, 0.012389367, 0.012274813, 0.012159318, 0.012088774, 0.01208742, 0.011996952, 0.011957007, 0.011948583, 0.011940745, 0.011907221, 0.011834988, 0.011765445, 0.011723367, 0.011592826, 0.011577089]
 

01-01 21:20:54.108 19624 19648 W ClassifyImageTask: [0.0, 0.0, 0.0, 45.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 66.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 45.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 16.0, 0.0, 42.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 37.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 43.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 66.0, 45.0, 0.0]
 

Thanks