Comments (1)
I encountered NaN problem when I tried to support fp16 inference.
The cause is that some of MiDaS outputs are very large values, and that turns into inf
in float16.
A workaround is to clip MiDaS output within float16 range.
nagadomi@384f325
Also, running DPTDepthModel.head
with float16 degraded the accuracy, so it was better to use float32 for that one.
nagadomi/MiDaS_iw3@2e398c9
Note that I tried this only for inference.
--use_amp 0
{'a1': 0.954, 'a2': 0.995, 'a3': 0.999, 'abs_rel': 0.075, 'rmse': 0.27, 'log_10': 0.032, 'rmse_log': 0.095, 'silog': 7.034, 'sq_rel': 0.03}
654/654 [02:27<00:00, 4.42it/s]
--use_amp 1
{'a1': 0.954, 'a2': 0.995, 'a3': 0.999, 'abs_rel': 0.075, 'rmse': 0.271, 'log_10': 0.033, 'rmse_log': 0.095, 'silog': 7.039, 'sq_rel': 0.03}
654/654 [01:50<00:00, 5.90it/s]
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