Official External Data Thread

N+1 Fish, N+2 Fish
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If you use external data, per this announcement, include a link to the data here!

It must be freely publicly available.

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I plan to use the following pretrained models:
DenseNet: https ://github.com/flyyufelix/DenseNet-Keras
ResNet-101: https ://gist.github.com/flyyufelix/65018873f8cb2bbe95f429c474aa1294
ResNet-152: https ://gist.github.com/flyyufelix/7e2eafb149f72f4d38dd661882c554a6
SqueezeNet: https ://github.com/rcmalli/keras-squeezenet
Inception v4: https ://github.com/titu1994/Inception-v4/releases
VGG16: https ://gist.github.com/baraldilorenzo/07d7802847aaad0a35d3
VGG19: https ://gist.github.com/baraldilorenzo/8d096f48a1be4a2d660d
Other Keras models: https ://keras.io/applications/

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I plan to use pre-trained VGG-16 referenced here https://github.com/amdegroot/ssd.pytorch#training-ssd and pre-trained pytorch models http://pytorch.org/docs/master/torchvision/models.html

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Using keras weights from https ://keras.io/applications/

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In addition to listed pretrained models:

DenseNet: https ://github.com/flyyufelix/DenseNet-Keras
and other Keras models: https ://keras.io/applications/

I’m also using

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Using this: https://github.com/tensorflow/models/tree/master/research/object_detection

1 Like
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I am using pretrained pytorch models from https://github.com/pytorch/vision

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I’m planning to use this https://github.com/yhenon/keras-frcnn
And the models referenced here: https://github.com/fchollet/deep-learning-models

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I am using pretrained ‘imagenet’ weights for VGG-16 from KERAS applications here: https://keras.io/applications/#vgg16

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Trying to use: vgg1, vgg2, mobilenet, resnet, pva, densenet.

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I am also using pytorch/vision models.

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Pretrained keras weights from https ://keras.io/applications/

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Should we post the pretrained models we are using, even if they were already posted?
Just in case, I’ve tried some of the pytorch models already mentioned.