Pre-trained models
Contents
Pre-trained models#
The currently available model checkpoints can be seen by running the command:
echofilter --list-checkpoints
All current checkpoints were trained on data acquired by FORCE.
Training Datasets#
Stationary#
- data collection
bottom-mounted stationary, autonomous
- orientation
uplooking
- echosounder
120 kHz Simrad WBAT
- locations
FORCE tidal power demonstration site, Minas Passage
45°21’47.34”N 64°25’38.94”W
December 2017 through November 2018
SMEC, Grand Passage
44°15’49.80”N 66°20’12.60”W
December 2019 through January 2020
- organization
FORCE
Mobile#
- data collection
vessel-based 24-hour transect surveys
- orientation
downlooking
- echosounder
120 kHz Simrad EK80
- locations
FORCE tidal power demonstration site, Minas Passage
45°21’57.58”N 64°25’50.97”W
May 2016 through October 2018
- organization
FORCE
Model checkpoints#
The architecture used for all current models is a U-Net with a backbone of 6 EfficientNet blocks in each direction (encoding and decoding). There are horizontal skip connections between compression and expansion blocks at the same spatial scale and a latent space of 32 channels throughout the network. The depth dimension of the input is halved (doubled) after each block, whilst the time dimension is halved (doubled) every other block.
Details for notable model checkpoints are provided below.
- conditional_mobile-stationary2_effunet6x2-1_lc32_v2.2
Trained on both upfacing stationary and downfacing mobile data.
Jaccard Index of 96.84% on downfacing mobile and 94.51% on upfacing stationary validation data.
Default model checkpoint.
- conditional_mobile-stationary2_effunet6x2-1_lc32_v2.1
Trained on both upfacing stationary and downfacing mobile data.
Jaccard Index of 96.8% on downfacing mobile and 94.4% on upfacing stationary validation data.
- conditional_mobile-stationary2_effunet6x2-1_lc32_v2.0
Trained on both upfacing stationary and downfacing mobile data.
Jaccard Index of 96.62% on downfacing mobile and 94.29% on upfacing stationary validation data.
Sample outputs on upfacing stationary data were thoroughly verified via manual inspection by trained analysts.
- stationary2_effunet6x2-1_lc32_v2.1
Trained on upfacing stationary data only.
Jaccard Index of 94.4% on upfacing stationary validation data.
- stationary2_effunet6x2-1_lc32_v2.0
Trained on upfacing stationary data only.
Jaccard Index of 94.41% on upfacing stationary validation data.
Sample outputs thoroughly were thoroughly verified via manual inspection by trained analysts.
- mobile_effunet6x2-1_lc32_v1.0
Trained on downfacing mobile data only.