{ "id": 30134, "title": "Official pre-trained models thread", "url": "/competitions/intel-mobileodt-cervical-cancer-screening/discussion/30134", "author_name": "Wendy Kan", "post_date": "2017-03-15T19:28:28.787000", "votes": 22, "comment_count": 188, "views": 0, "content": "

Please use this thread to share your pre-trained models. Please make sure you do so before June 7, 2017.

", "messages": [ { "id": 167900, "postDate": "2017-03-15T19:28:28.787Z", "content": "

Please use this thread to share your pre-trained models. Please make sure you do so before June 7, 2017.

", "rawMarkdown": "Please use this thread to share your pre-trained models. Please make sure you do so before June 7, 2017. ", "votes": 22 }, { "id": 179659, "postDate": "2017-05-02T12:30:04.413Z", "content": "

SqueezeNet: https://github.com/rcmalli/keras-squeezenet

", "rawMarkdown": "SqueezeNet: https://github.com/rcmalli/keras-squeezenet", "votes": 5 }, { "id": 167937, "postDate": "2017-03-15T21:06:58.440Z", "content": "

From the timeline:

\n\n

\"June 7, 2017 - Pre-trained models posting deadline.\" -- sounds better to non-US ears when month is spelled out.

", "rawMarkdown": "From the timeline:\n\n\"June 7, 2017 - Pre-trained models posting deadline.\" -- sounds better to non-US ears when month is spelled out.", "votes": 6, "replies": [ { "id": 168354, "postDate": "2017-03-16T23:02:35.510Z", "content": "

Edited. Btw, I'm not from the US either :)

", "rawMarkdown": "Edited. Btw, I'm not from the US either :) " } ] }, { "id": 189993, "postDate": "2017-06-07T02:50:41.467Z", "content": "

Using keras pretrained models - https://keras.io/applications/\nXception,ResNet50,InceptionV3

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/\nXception,ResNet50,InceptionV3", "votes": 1 }, { "id": 186430, "postDate": "2017-05-28T02:43:59.370Z", "content": "

I used caffe model: \nprototxt: https://github.com/soeaver/caffe-model/blob/master/prototxts/inception_resnet_v2_train_test.prototxt\npre-trained model: https://github.com/soeaver/caffe-model\nand\nprototxt: https://gist.github.com/ksimonyan/3785162f95cd2d5fee77#file-readme-md\ncaffemodel: http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_19_layers.caffemodel

", "rawMarkdown": "I used caffe model: \nprototxt: https://github.com/soeaver/caffe-model/blob/master/prototxts/inception_resnet_v2_train_test.prototxt\npre-trained model: https://github.com/soeaver/caffe-model\nand\nprototxt: https://gist.github.com/ksimonyan/3785162f95cd2d5fee77#file-readme-md\ncaffemodel: http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_19_layers.caffemodel", "votes": 1 }, { "id": 177551, "postDate": "2017-04-25T06:43:11.290Z", "content": "

I'm using following pre-trained model:\nInceptionV3 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

InceptionV4 from: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.1/inception-v4_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

DenseNet161 from: https://drive.google.com/open?id=0Byy2AcGyEVxfUDZwVjU2cFNidTA

\n\n

ResNet50 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

ResNet152 from: https://drive.google.com/file/d/0Byy2AcGyEVxfeXExMzNNOHpEODg/view?usp=sharing

", "rawMarkdown": "I'm using following pre-trained model:\nInceptionV3 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nInceptionV4 from: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.1/inception-v4_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nDenseNet161 from: https://drive.google.com/open?id=0Byy2AcGyEVxfUDZwVjU2cFNidTA\n\nResNet50 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nResNet152 from: https://drive.google.com/file/d/0Byy2AcGyEVxfeXExMzNNOHpEODg/view?usp=sharing\n\n", "votes": 1 }, { "id": 171557, "postDate": "2017-03-30T14:55:47.180Z", "content": "

I am using the pre-trained models from https://www.gradientzoo.com/

", "rawMarkdown": "I am using the pre-trained models from https://www.gradientzoo.com/", "votes": 1 }, { "id": 186691, "postDate": "2017-05-29T02:03:53.927Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/", "votes": 2 }, { "id": 184060, "postDate": "2017-05-20T09:30:08.260Z", "content": "

I am using the pre-trained models:

\n\n
\n\n

Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

ResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .

\n\n

ResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .

\n\n

VGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .

", "rawMarkdown": "I am using the pre-trained models:\n\n\n----------\n\n\nInception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .", "votes": 2 }, { "id": 194324, "postDate": "2017-06-20T04:33:43.013Z", "content": "

Using keras pretrained models - https://keras.io/applications/

\n\n

I learned it yesterday. (´・ω・`)

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/\n\nI learned it yesterday. (´・ω・`) " }, { "id": 193856, "postDate": "2017-06-18T13:32:36.360Z", "content": "

Using keras pretrained model - inception v3 - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained model - inception v3 - https://keras.io/applications/" }, { "id": 192543, "postDate": "2017-06-14T01:13:31.800Z", "content": "

We are using the Keras pre-trained models : https://keras.io/applications/#resnet50.

", "rawMarkdown": "We are using the Keras pre-trained models : https://keras.io/applications/#resnet50." }, { "id": 190836, "postDate": "2017-06-08T15:50:48.503Z", "content": "

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

", "rawMarkdown": "Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz ." }, { "id": 190629, "postDate": "2017-06-08T04:49:52.313Z", "content": "

Keras pre-trained models - https://keras.io/applications/

", "rawMarkdown": "Keras pre-trained models - https://keras.io/applications/ " }, { "id": 190609, "postDate": "2017-06-08T02:59:54.313Z", "content": "

using vgg16 pretrained model from https://github.com/fastai/courses/tree/master/deeplearning1/nbs

", "rawMarkdown": "using vgg16 pretrained model from https://github.com/fastai/courses/tree/master/deeplearning1/nbs" }, { "id": 190593, "postDate": "2017-06-08T01:34:44.160Z", "content": "

I am using keras pretrained model VGG16. May consider others in https://keras.io/applications/

", "rawMarkdown": "I am using keras pretrained model VGG16. May consider others in https://keras.io/applications/" }, { "id": 190589, "postDate": "2017-06-08T01:23:33.727Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 190577, "postDate": "2017-06-08T00:50:00.037Z", "content": "

Using keras pretrained models (https://keras.io/applications) as well as vgg16 via vgg16.py and vgg16bn.py located here: https://github.com/fastai/courses/tree/master/deeplearning1/nbs

", "rawMarkdown": "Using keras pretrained models (https://keras.io/applications) as well as vgg16 via vgg16.py and vgg16bn.py located here: https://github.com/fastai/courses/tree/master/deeplearning1/nbs" }, { "id": 190576, "postDate": "2017-06-08T00:38:33.030Z", "content": "

I'm using the Keras pretrained models : https://keras.io/applications/ and TensorFlow-slim models: https://github.com/tensorflow/models/blob/master/inception/inception/slim/README.md

", "rawMarkdown": "I'm using the Keras pretrained models : https://keras.io/applications/ and TensorFlow-slim models: https://github.com/tensorflow/models/blob/master/inception/inception/slim/README.md " }, { "id": 190558, "postDate": "2017-06-07T22:49:32.363Z", "content": "

Link to Team WolfPack initial model (python-based)!!: https://github.com/iball41/kaggle/blob/master/TPOT_WolfPack.py

", "rawMarkdown": "Link to Team WolfPack initial model (python-based)!!: https://github.com/iball41/kaggle/blob/master/TPOT_WolfPack.py\n\n", "replies": [ { "id": 190570, "postDate": "2017-06-07T23:43:04.690Z", "content": "

Link to Team WolfPack model (Intel Deep Learning Tool-based): https://github.com/bobhuynh/Intel

", "rawMarkdown": "Link to Team WolfPack model (Intel Deep Learning Tool-based): https://github.com/bobhuynh/Intel" } ] }, { "id": 190548, "postDate": "2017-06-07T22:15:21.097Z", "content": "

I'm using the caffe pretrained models from Model Zoo.

", "rawMarkdown": "I'm using the caffe pretrained models from Model Zoo. " }, { "id": 190537, "postDate": "2017-06-07T21:11:40.670Z", "content": "

I am using keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I am using keras pretrained models : https://keras.io/applications/" }, { "id": 190532, "postDate": "2017-06-07T21:05:32.100Z", "content": "

I am using models from\nKeras - https://keras.io/applications/ \nCaffe - https://github.com/BVLC/caffe/wiki/Model-Zoo https://github.com/soeaver/caffe-model

", "rawMarkdown": "I am using models from\nKeras - https://keras.io/applications/ \nCaffe - https://github.com/BVLC/caffe/wiki/Model-Zoo https://github.com/soeaver/caffe-model" }, { "id": 190520, "postDate": "2017-06-07T20:33:48.517Z", "content": "

We will give a try at the retrained models in Matconvnet

\n\n

http://www.vlfeat.org/matconvnet/pretrained/

", "rawMarkdown": "We will give a try at the retrained models in Matconvnet\n\nhttp://www.vlfeat.org/matconvnet/pretrained/" }, { "id": 190512, "postDate": "2017-06-07T20:16:40.493Z", "content": "

Keras pretrained models, Torchvision pretrained models, https://github.com/flyyufelix/DenseNet-Keras & https://github.com/titu1994/DenseNet, https://github.com/yhenon/keras-frcnn, Darknet's YOLO.\nIf a link wasn't provided here, it means that it was already posted in the thread.

", "rawMarkdown": "Keras pretrained models, Torchvision pretrained models, https://github.com/flyyufelix/DenseNet-Keras & https://github.com/titu1994/DenseNet, https://github.com/yhenon/keras-frcnn, Darknet's YOLO.\nIf a link wasn't provided here, it means that it was already posted in the thread." }, { "id": 190494, "postDate": "2017-06-07T19:44:06.227Z", "content": "

Imagenet pre-trained models from https://keras.io/applications/\nImagenet pre-trained models from https://github.com/flyyufelix/cnn_finetune

", "rawMarkdown": "Imagenet pre-trained models from [https://keras.io/applications/][1]\nImagenet pre-trained models from [https://github.com/flyyufelix/cnn_finetune][2]\n [1]: https://keras.io/applications/\n [2]: https://github.com/flyyufelix/cnn_finetune" }, { "id": 190436, "postDate": "2017-06-07T17:27:59.827Z", "content": "

Probably using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Probably using keras pretrained models - https://keras.io/applications/\n" }, { "id": 190428, "postDate": "2017-06-07T17:15:34.197Z", "content": "

i am using https://keras.io/applications/ and https://github.com/rykov8/ssd_keras

", "rawMarkdown": "i am using https://keras.io/applications/ and https://github.com/rykov8/ssd_keras" }, { "id": 190424, "postDate": "2017-06-07T17:09:54.693Z", "content": "

My pretrained models https://github.com/fchollet/deep-learning-models

", "rawMarkdown": "My pretrained models https://github.com/fchollet/deep-learning-models" }, { "id": 190423, "postDate": "2017-06-07T17:09:02.963Z", "content": "

I will be using pre-trained InceptionResnet_V2 from http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz

", "rawMarkdown": "I will be using pre-trained InceptionResnet_V2 from http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz" }, { "id": 190416, "postDate": "2017-06-07T16:59:23.853Z", "content": "

AlexNet, VGG16 and VGG19

", "rawMarkdown": "AlexNet, VGG16 and VGG19" }, { "id": 190388, "postDate": "2017-06-07T15:33:04.947Z", "content": "

Keras pretrained models - https://keras.io/applications/\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .

", "rawMarkdown": "Keras pretrained models - https://keras.io/applications/\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz ." }, { "id": 190365, "postDate": "2017-06-07T14:53:17.737Z", "content": "

Using pretrained darknet models https://pjreddie.com/darknet/yolo/

", "rawMarkdown": "Using pretrained darknet models https://pjreddie.com/darknet/yolo/" }, { "id": 190362, "postDate": "2017-06-07T14:50:21.867Z", "content": "

I am using https://keras.io/applications/

", "rawMarkdown": "I am using https://keras.io/applications/" }, { "id": 190358, "postDate": "2017-06-07T14:36:09.643Z", "content": "

pretrained model: https://keras.io/applications/\nhttps://github.com/udacity/deep-learning/tree/master/transfer-learning/tensorflow_vgg

", "rawMarkdown": "pretrained model: https://keras.io/applications/\nhttps://github.com/udacity/deep-learning/tree/master/transfer-learning/tensorflow_vgg" }, { "id": 190355, "postDate": "2017-06-07T14:32:12.197Z", "content": "

Checking out:\nhttps://keras.io/applications/\nhttps://github.com/farizrahman4u/keras-contrib/tree/master/keras_contrib/applications\nhttps://github.com/flyyufelix/cnn_finetune\nhttps://github.com/BVLC/caffe/wiki/Model-Zoo\nhttps://github.com/soeaver/caffe-model

", "rawMarkdown": "Checking out:\nhttps://keras.io/applications/\nhttps://github.com/farizrahman4u/keras-contrib/tree/master/keras_contrib/applications\nhttps://github.com/flyyufelix/cnn_finetune\nhttps://github.com/BVLC/caffe/wiki/Model-Zoo\nhttps://github.com/soeaver/caffe-model" }, { "id": 190352, "postDate": "2017-06-07T14:21:54.300Z", "content": "

Pretrained resnet, inception-v3, resnet-inception-v2

", "rawMarkdown": "Pretrained resnet, inception-v3, resnet-inception-v2" }, { "id": 190345, "postDate": "2017-06-07T14:10:35.813Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 190344, "postDate": "2017-06-07T14:08:25.317Z", "content": "

Keras pretrained models - https://keras.io/applications/

\n\n

SqueezeNet: https://github.com/rcmalli/keras-squeezenet

\n\n

Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

ResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .

\n\n

ResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .

\n\n

VGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .

\n\n

Caffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo

\n\n

Pytorch Vision model - https://github.com/pytorch/vision#models

\n\n

Mxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery

\n\n

Torch pre-trained Resnet from Facebook - https://github.com/facebook/fb.resnet.torch/tree/master/pretrained

", "rawMarkdown": "Keras pretrained models - https://keras.io/applications/\n\nSqueezeNet: https://github.com/rcmalli/keras-squeezenet\n\nInception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .\n\nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo\n\nPytorch Vision model - https://github.com/pytorch/vision#models\n\nMxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery\n\nTorch pre-trained Resnet from Facebook - https://github.com/facebook/fb.resnet.torch/tree/master/pretrained" }, { "id": 190290, "postDate": "2017-06-07T12:54:09.743Z", "content": "

Pretrained models from https://keras.io/applications and https://github.com/fchollet/deep-learning-models.

", "rawMarkdown": "Pretrained models from https://keras.io/applications and https://github.com/fchollet/deep-learning-models." }, { "id": 190285, "postDate": "2017-06-07T12:50:57.160Z", "content": "

We are using pre-trained Models InceptionV3 or VGG16.

", "rawMarkdown": "We are using pre-trained Models InceptionV3 or VGG16." }, { "id": 190253, "postDate": "2017-06-07T11:51:16.077Z", "content": "

Using the models from the following libraries:

\n\n

Keras pre-trained models - https://keras.io/applications/ \nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo

", "rawMarkdown": "Using the models from the following libraries:\n\nKeras pre-trained models - https://keras.io/applications/ \nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo " }, { "id": 190197, "postDate": "2017-06-07T09:38:22.187Z", "content": "

Using Keras pre-trained model : https://keras.io/applications/ + 1

", "rawMarkdown": "Using Keras pre-trained model : https://keras.io/applications/ + 1\n" }, { "id": 190170, "postDate": "2017-06-07T09:00:19.053Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 190158, "postDate": "2017-06-07T08:45:28.393Z", "content": "

I am using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "I am using keras pretrained models - https://keras.io/applications/" }, { "id": 190129, "postDate": "2017-06-07T07:59:32.043Z", "content": "

caffe: Reference CaffeNet, AlexNet, GoogLeNet, VGG19 http://caffe.berkeleyvision.org/model_zoo.html https://github.com/BVLC/caffe/wiki/Model-Zoo#models-used-by-the-vgg-team-in-ilsvrc-2014

\n\n

darknet: darknet19 448 yolo2 darknet19_448.conv.23 https://pjreddie.com/darknet/imagenet/ https://pjreddie.com/darknet/yolo/ https://pjreddie.com/darknet/imagenet/

\n\n

keras: https://keras.io/applications/

", "rawMarkdown": "**caffe**: Reference CaffeNet, AlexNet, GoogLeNet, VGG19 http://caffe.berkeleyvision.org/model_zoo.html https://github.com/BVLC/caffe/wiki/Model-Zoo#models-used-by-the-vgg-team-in-ilsvrc-2014\n\n**darknet**: darknet19 448 yolo2 darknet19_448.conv.23 https://pjreddie.com/darknet/imagenet/ https://pjreddie.com/darknet/yolo/ https://pjreddie.com/darknet/imagenet/ \n\n**keras**: https://keras.io/applications/" }, { "id": 190082, "postDate": "2017-06-07T06:37:05.947Z", "content": "

I will be using DenseNet implemented in keras fromhttps://github.com/flyyufelix/DenseNet-Keras and imagenet models

", "rawMarkdown": "I will be using DenseNet implemented in keras from[https://github.com/flyyufelix/DenseNet-Keras][1] and imagenet models\n\n\n [1]: https://github.com/flyyufelix/DenseNet-Keras" }, { "id": 190077, "postDate": "2017-06-07T06:27:40.970Z", "content": "

I am using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "I am using keras pretrained models - https://keras.io/applications/\n" }, { "id": 190072, "postDate": "2017-06-07T06:20:15.217Z", "content": "

I am using https://github.com/fchollet/deep-learning-models/blob/master/resnet50.py

", "rawMarkdown": "I am using https://github.com/fchollet/deep-learning-models/blob/master/resnet50.py" }, { "id": 190065, "postDate": "2017-06-07T05:45:59.093Z", "content": "

I am using following pretrained models:

\n\n
    \n
  1. Inception V4: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz
    2. \n
  2. Inception Resnet V2: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz
    3. \n
  3. ResNet V2 50: http://download.tensorflow.org/models/resnet_v2_50_2017_04_14.tar.gz
    4. \n
  4. ResNet V2 101: http://download.tensorflow.org/models/resnet_v2_101_2017_04_14.tar.gz
    5. \n
  5. VGG 16: https://www.cs.toronto.edu/~frossard/vgg16/vgg16_weights.npz
    6. \n
", "rawMarkdown": "I am using following pretrained models:\n\n 1. Inception V4: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz\n 2. Inception Resnet V2: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz\n 3. ResNet V2 50: http://download.tensorflow.org/models/resnet_v2_50_2017_04_14.tar.gz\n 4. ResNet V2 101: http://download.tensorflow.org/models/resnet_v2_101_2017_04_14.tar.gz\n 5. VGG 16: https://www.cs.toronto.edu/~frossard/vgg16/vgg16_weights.npz" }, { "id": 190053, "postDate": "2017-06-07T04:51:35.710Z", "content": "

Also using keras pretraind models https://keras.io/applications/

", "rawMarkdown": "Also using keras pretraind models https://keras.io/applications/" }, { "id": 190029, "postDate": "2017-06-07T04:05:49.437Z", "content": "

PyTorch pretrained models:

\n\n

https://github.com/pytorch/vision/tree/master/torchvision/models

", "rawMarkdown": "PyTorch pretrained models:\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models" }, { "id": 189988, "postDate": "2017-06-07T02:40:47.253Z", "content": "

Mxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery

", "rawMarkdown": "Mxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery " }, { "id": 189983, "postDate": "2017-06-07T02:31:25.020Z", "content": "

Using Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

", "rawMarkdown": "Using Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz ." }, { "id": 189972, "postDate": "2017-06-07T02:12:48.827Z", "content": "

Also using MXNet pretrained models from http://data.dmlc.ml/models

", "rawMarkdown": "Also using MXNet pretrained models from http://data.dmlc.ml/models" }, { "id": 189921, "postDate": "2017-06-07T00:49:25.890Z", "content": "

I am using keras pretrained models: https://keras.io/applications/

", "rawMarkdown": "I am using keras pretrained models: https://keras.io/applications/" }, { "id": 189855, "postDate": "2017-06-06T23:56:50.313Z", "content": "

based on keras.applications.VGG16

", "rawMarkdown": "based on keras.applications.VGG16" }, { "id": 189802, "postDate": "2017-06-06T21:25:45.710Z", "content": "", "rawMarkdown": " - https://github.com/facebookresearch/ResNeXt\n - https://github.com/facebook/fb.resnet.torch" }, { "id": 189759, "postDate": "2017-06-06T20:01:13.580Z", "content": "

Using Keras pre-trained models: https://keras.io/applications/

", "rawMarkdown": "Using Keras pre-trained models: https://keras.io/applications/" }, { "id": 189758, "postDate": "2017-06-06T19:59:18.720Z", "content": "

Also using Keras pre-trained models (https://keras.io/applications/)

", "rawMarkdown": "Also using Keras pre-trained models (https://keras.io/applications/)" }, { "id": 189722, "postDate": "2017-06-06T18:35:17.280Z", "content": "

Hey, I'm also using the Keras pre-trained model;\nhttps://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

", "rawMarkdown": "Hey, I'm also using the Keras pre-trained model;\nhttps://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5 " }, { "id": 189712, "postDate": "2017-06-06T18:06:20.603Z", "content": "

Using Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "Using Keras pretrained models : https://keras.io/applications/\n" }, { "id": 189711, "postDate": "2017-06-06T17:59:27.720Z", "content": "

Keras models: https://keras.io/applications/

", "rawMarkdown": "Keras models: https://keras.io/applications/" }, { "id": 189696, "postDate": "2017-06-06T17:12:28.877Z", "content": "

Using models:\nXception\nVGG16\nVGG19\nResNet50\nInceptionV3

\n\n

from https://keras.io/applications/

", "rawMarkdown": "Using models:\nXception\nVGG16\nVGG19\nResNet50\nInceptionV3\n\nfrom https://keras.io/applications/" }, { "id": 189685, "postDate": "2017-06-06T16:27:11.373Z", "content": "

I will also try caffe https://github.com/soeaver/caffe-model/blob/master/prototxts/inception_resnet_v2_train_test.prototxt

", "rawMarkdown": "I will also try caffe https://github.com/soeaver/caffe-model/blob/master/prototxts/inception_resnet_v2_train_test.prototxt" }, { "id": 189684, "postDate": "2017-06-06T16:22:35.170Z", "content": "

Googlenet | Alexnet | Resnet | Inception | VGG | LeNet

", "rawMarkdown": "Googlenet | Alexnet | Resnet | Inception | VGG | LeNet\n" }, { "id": 189675, "postDate": "2017-06-06T15:55:28.087Z", "content": "

Using\nKeras - Squeezenet: https://github.com/rcmalli/keras-squeezenet\nPytorch pretrained models: https://github.com/pytorch/vision#models\nKeras pretrained models: https://keras.io/applications/\nFast.ai pretrained models: files.fast.ai\nand some more from here: https://github.com/flyyufelix/cnn_finetune

", "rawMarkdown": "Using\nKeras - Squeezenet: https://github.com/rcmalli/keras-squeezenet\nPytorch pretrained models: https://github.com/pytorch/vision#models\nKeras pretrained models: https://keras.io/applications/\nFast.ai pretrained models: files.fast.ai\nand some more from here: https://github.com/flyyufelix/cnn_finetune" }, { "id": 189674, "postDate": "2017-06-06T15:51:33.250Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 189621, "postDate": "2017-06-06T13:49:38.473Z", "content": "

Using Keras Pretrained models : https://keras.io/applications/#resnet50

", "rawMarkdown": "Using Keras Pretrained models : https://keras.io/applications/#resnet50" }, { "id": 189600, "postDate": "2017-06-06T12:45:33.907Z", "content": "

I am using the resnet50 model with keras from the keras library:\nhttps://keras.io/applications/

", "rawMarkdown": "I am using the resnet50 model with keras from the keras library:\nhttps://keras.io/applications/ " }, { "id": 189585, "postDate": "2017-06-06T12:01:47.520Z", "content": "

Using SSD port https://github.com/rykov8/ssd_keras and keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using SSD port https://github.com/rykov8/ssd_keras and keras pretrained models - https://keras.io/applications/" }, { "id": 189540, "postDate": "2017-06-06T09:41:10.343Z", "content": "

might use pre-trained models in Keras: https://keras.io/applications/

", "rawMarkdown": "might use pre-trained models in Keras: https://keras.io/applications/" }, { "id": 189516, "postDate": "2017-06-06T08:25:06.610Z", "content": "

I am using Torch pre-trained models from Facebook: \nhttps://github.com/facebook/fb.resnet.torch/tree/master/pretrained\nhttps://github.com/facebookresearch/ResNeXt

", "rawMarkdown": "I am using Torch pre-trained models from Facebook: \nhttps://github.com/facebook/fb.resnet.torch/tree/master/pretrained\nhttps://github.com/facebookresearch/ResNeXt" }, { "id": 189475, "postDate": "2017-06-06T06:18:56.373Z", "content": "

I'm using Inception V3, ResNet, VGG, FCN and a slightly modified version of the same

", "rawMarkdown": "I'm using Inception V3, ResNet, VGG, FCN and a slightly modified version of the same" }, { "id": 189469, "postDate": "2017-06-06T05:56:40.423Z", "content": "

I'm using keras pretrained models from applications submodule

", "rawMarkdown": "I'm using keras pretrained models from applications submodule" }, { "id": 189428, "postDate": "2017-06-06T02:24:08.943Z", "content": "

Using pre-trained models from:
\nhttps://github.com/BVLC/caffe/wiki/Model-Zoo
\nhttps://github.com/soeaver/caffe-model

", "rawMarkdown": "Using pre-trained models from: \nhttps://github.com/BVLC/caffe/wiki/Model-Zoo \nhttps://github.com/soeaver/caffe-model" }, { "id": 189404, "postDate": "2017-06-06T00:08:28.337Z", "content": "

I'm using the Keras pretrained models as well : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras pretrained models as well : https://keras.io/applications/\n" }, { "id": 189366, "postDate": "2017-06-05T21:50:38.113Z", "content": "

using https://keras.io/applications/ :btw do we need to even post this if it is already been posted?

\n\n

Also using nets I pretrained myself on ILSVRC2012 imagenet CLS

", "rawMarkdown": "using https://keras.io/applications/ :btw do we need to even post this if it is already been posted?\n\nAlso using nets I pretrained myself on ILSVRC2012 imagenet CLS " }, { "id": 189357, "postDate": "2017-06-05T21:08:49.657Z", "content": "

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

", "rawMarkdown": "Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz ." }, { "id": 189339, "postDate": "2017-06-05T20:21:56.873Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 189269, "postDate": "2017-06-05T16:24:47.463Z", "content": "

I used the Keras pre-trained model:
\nhttps://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

", "rawMarkdown": "I used the Keras pre-trained model: \nhttps://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5" }, { "id": 189215, "postDate": "2017-06-05T14:07:27.153Z", "content": "

Using MXNet pretrained models - http://data.dmlc.ml/models

", "rawMarkdown": "Using MXNet pretrained models - http://data.dmlc.ml/models" }, { "id": 189214, "postDate": "2017-06-05T14:04:57.003Z", "content": "

Using MXNet pretrained models - http://data.dmlc.ml/models

", "rawMarkdown": "Using MXNet pretrained models - http://data.dmlc.ml/models" }, { "id": 189213, "postDate": "2017-06-05T14:03:59.477Z", "content": "

Using MXNet pretrained models from http://data.dmlc.ml/models

", "rawMarkdown": "Using MXNet pretrained models from http://data.dmlc.ml/models" }, { "id": 189212, "postDate": "2017-06-05T14:02:54.233Z", "content": "

Using MXNet pretrained models - http://data.dmlc.ml/models

", "rawMarkdown": "Using MXNet pretrained models - http://data.dmlc.ml/models" }, { "id": 189172, "postDate": "2017-06-05T12:25:11.233Z", "content": "
ImageNet Pretrained Weights \nhttps://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_th_dim_ordering_th_kernels.h5\n
", "rawMarkdown": " ImageNet Pretrained Weights \n https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_th_dim_ordering_th_kernels.h5\n" }, { "id": 189155, "postDate": "2017-06-05T11:35:50.067Z", "content": "

I'm trying different pre-trained models and I'll select 1 or 2 for the final 2 submitions: \n vgg16 and others from http://files.fast.ai/models/vgg16_bn.h5 http://files.fast.ai/models/vgg16_bn_conv.h5 http://files.fast.ai/models/vgg16.h5

\n\n

Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

ResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .

\n\n

ResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .

\n\n

VGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .\nGoogleNet and Caffe from Intel sdk tool

", "rawMarkdown": "I'm trying different pre-trained models and I'll select 1 or 2 for the final 2 submitions: \n vgg16 and others from http://files.fast.ai/models/vgg16_bn.h5 http://files.fast.ai/models/vgg16_bn_conv.h5 http://files.fast.ai/models/vgg16.h5\n\n Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .\nGoogleNet and Caffe from Intel sdk tool" }, { "id": 189140, "postDate": "2017-06-05T10:52:37.617Z", "content": "

and also the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "and also the Keras pretrained models : https://keras.io/applications/" }, { "id": 189116, "postDate": "2017-06-05T10:00:10.110Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 189040, "postDate": "2017-06-05T01:01:22.940Z", "content": "

Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

Inception V4. FROM: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz .

\n\n

ResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .

\n\n

ResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .

\n\n

VGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .

", "rawMarkdown": "Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nInception V4. FROM: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz ." }, { "id": 189007, "postDate": "2017-06-04T20:05:33.947Z", "content": "

Using: https://keras.io/applications/\nOr/And: https://github.com/titu1994/DenseNet\nhttps://github.com/rcmalli/keras-squeezenet

", "rawMarkdown": "Using: https://keras.io/applications/\nOr/And: https://github.com/titu1994/DenseNet\nhttps://github.com/rcmalli/keras-squeezenet" }, { "id": 188888, "postDate": "2017-06-04T12:06:43.137Z", "content": "

Using various pre-trained models from :\nhttps://github.com/syeddanish41/cnn_finetune

", "rawMarkdown": "Using various pre-trained models from :\n[https://github.com/syeddanish41/cnn_finetune][1]\n\n\n [1]: https://github.com/syeddanish41/cnn_finetune" }, { "id": 188881, "postDate": "2017-06-04T11:25:01.580Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 188837, "postDate": "2017-06-04T07:51:31.037Z", "content": "

Original vgg16, vgg16 with batch normalization, and vgg19

", "rawMarkdown": "Original vgg16, vgg16 with batch normalization, and vgg19" }, { "id": 188830, "postDate": "2017-06-04T07:33:04.463Z", "content": "

Using keras pretrained models - https://keras.io/applications/\nAnd fast.ai pretrained models - http://files.fast.ai/models/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/\nAnd fast.ai pretrained models - http://files.fast.ai/models/", "replies": [ { "id": 190435, "postDate": "2017-06-07T17:27:16.363Z", "content": "

And let's add https://github.com/yhenon/keras-frcnn, https://github.com/rykov8/ssd_keras & https://github.com/allanzelener/YAD2K for good measure.

", "rawMarkdown": "And let's add https://github.com/yhenon/keras-frcnn, https://github.com/rykov8/ssd_keras & https://github.com/allanzelener/YAD2K for good measure." } ] }, { "id": 188828, "postDate": "2017-06-04T07:07:13.673Z", "content": "

I am using the models from following libraries:

\n\n

Keras pre-trained models - https://keras.io/applications/
\nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo
\nPytorch Vision model - https://github.com/pytorch/vision#models
\nMxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery
\nTorch pre-trained Resnet from Facebook - https://github.com/facebook/fb.resnet.torch/tree/master/pretrained

", "rawMarkdown": "I am using the models from following libraries: \n\nKeras pre-trained models - https://keras.io/applications/ \nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo \nPytorch Vision model - https://github.com/pytorch/vision#models \nMxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery \nTorch pre-trained Resnet from Facebook - https://github.com/facebook/fb.resnet.torch/tree/master/pretrained \n\n" }, { "id": 188799, "postDate": "2017-06-04T04:29:34.930Z", "content": "

Keras pretrained models: https://keras.io/applications/

\n\n

Keras 2 Inception V4: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.1/

\n\n

Keras 1 Inception V4: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.0/

", "rawMarkdown": "Keras pretrained models: https://keras.io/applications/\n\nKeras 2 Inception V4: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.1/\n\nKeras 1 Inception V4: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.0/\n" }, { "id": 188784, "postDate": "2017-06-04T03:30:53.543Z", "content": "

Using Keras pretrained models: https://keras.io/applications/

", "rawMarkdown": "Using Keras pretrained models: https://keras.io/applications/" }, { "id": 188638, "postDate": "2017-06-03T13:57:00.350Z", "content": "

I am using keras pre-trained models vgg16 or vgg19 from Keras Applications

", "rawMarkdown": "I am using keras pre-trained models vgg16 or vgg19 from Keras Applications" }, { "id": 188628, "postDate": "2017-06-03T13:08:08.413Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 188447, "postDate": "2017-06-02T21:39:15.040Z", "content": "

I am using Pre-trained models:

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

Inception V2. FROM: http://download.tensorflow.org/models/inception_v2_2016_08_28.tar.gz .

\n\n

Inception V4. FROM: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz .

", "rawMarkdown": "I am using Pre-trained models:\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nInception V2. FROM: http://download.tensorflow.org/models/inception_v2_2016_08_28.tar.gz .\n\nInception V4. FROM: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz .\n" }, { "id": 188413, "postDate": "2017-06-02T20:08:57.267Z", "content": "

using vgg-* resnet-* pretrained from keras: https://keras.io/applications

\n\n

vgg-* resnet-* inception-v3 densenet-*\nfrom pytorch https://github.com/pytorch/vision/tree/master/torchvision/models

", "rawMarkdown": "using vgg-* resnet-* pretrained from keras: https://keras.io/applications\n\n\nvgg-* resnet-* inception-v3 densenet-*\nfrom pytorch https://github.com/pytorch/vision/tree/master/torchvision/models\n" }, { "id": 188399, "postDate": "2017-06-02T19:38:57.430Z", "content": "

torch pretrained\nhttps://github.com/facebook/fb.resnet.torch/tree/master/pretrained

\n\n

Lasagne model zoo\nhttps://github.com/Lasagne/Recipes/tree/master/modelzoo

", "rawMarkdown": "torch pretrained\nhttps://github.com/facebook/fb.resnet.torch/tree/master/pretrained\n\nLasagne model zoo\nhttps://github.com/Lasagne/Recipes/tree/master/modelzoo\n" }, { "id": 188295, "postDate": "2017-06-02T14:48:52.080Z", "content": "

Keras models: https://keras.io/applications/

", "rawMarkdown": "Keras models: https://keras.io/applications/" }, { "id": 188274, "postDate": "2017-06-02T13:17:56.993Z", "content": "

I am using the VGG19 model among others from Keras https://keras.io/applications/

", "rawMarkdown": "I am using the VGG19 model among others from Keras https://keras.io/applications/" }, { "id": 188225, "postDate": "2017-06-02T09:16:24.860Z", "content": "

We are using Keras pretrained models with imagenet weights: https://keras.io/applications/

", "rawMarkdown": "We are using Keras pretrained models with imagenet weights: https://keras.io/applications/" }, { "id": 188147, "postDate": "2017-06-02T04:55:33.313Z", "content": "

From Microsoft CNTK:

\n\n

ResNet 101: https://migonzastorage.blob.core.windows.net/deep-learning/models/cntk/imagenet/ResNet_101.model

\n\n

ResNet 152: https://migonzastorage.blob.core.windows.net/deep-learning/models/cntk/imagenet/ResNet_152.model

\n\n

From Keras:

\n\n

ResNet 50: https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

VGG 16: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

VGG 19: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

InceptionV3: https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

Xception: https://github.com/fchollet/deep-learning-models/releases/download/v0.4/xception_weights_tf_dim_ordering_tf_kernels_notop.h5

", "rawMarkdown": "**From Microsoft CNTK:**\n\nResNet 101: https://migonzastorage.blob.core.windows.net/deep-learning/models/cntk/imagenet/ResNet_101.model\n\nResNet 152: https://migonzastorage.blob.core.windows.net/deep-learning/models/cntk/imagenet/ResNet_152.model\n\n\n**From Keras:**\n\nResNet 50: https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nVGG 16: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nVGG 19: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nInceptionV3: https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nXception: https://github.com/fchollet/deep-learning-models/releases/download/v0.4/xception_weights_tf_dim_ordering_tf_kernels_notop.h5\n\n" }, { "id": 188101, "postDate": "2017-06-02T01:27:25.997Z", "content": "

I used caffe model : bvlc_googlenet

", "rawMarkdown": "I used caffe model : [bvlc_googlenet][1]\n\n\n [1]: https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet" }, { "id": 188096, "postDate": "2017-06-02T01:01:03.133Z", "content": "

using ResNet-50 from https://onedrive.live.com/?authkey=%21AAFW2-FVoxeVRck&id=4006CBB8476FF777%2117887&cid=4006CBB8476FF777

", "rawMarkdown": "using ResNet-50 from https://onedrive.live.com/?authkey=%21AAFW2-FVoxeVRck&id=4006CBB8476FF777%2117887&cid=4006CBB8476FF777" }, { "id": 188082, "postDate": "2017-06-01T23:40:06.460Z", "content": "

DenseNet for Keras: https://github.com/flyyufelix/DenseNet-Keras

", "rawMarkdown": "DenseNet for Keras: https://github.com/flyyufelix/DenseNet-Keras" }, { "id": 188081, "postDate": "2017-06-01T23:32:50.787Z", "content": "

I'm using the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras pretrained models : https://keras.io/applications/" }, { "id": 188073, "postDate": "2017-06-01T22:54:17.660Z", "content": "

I use Keras' pretrained models : https://keras.io/applications

", "rawMarkdown": "I use Keras' pretrained models : https://keras.io/applications\n" }, { "id": 188059, "postDate": "2017-06-01T22:13:46.513Z", "content": "

I'm using some of the caffe standard models: resnet-50, google1, vgg-19, squeezenet, ...

", "rawMarkdown": "I'm using some of the caffe standard models: resnet-50, google1, vgg-19, squeezenet, ..." }, { "id": 187594, "postDate": "2017-05-31T17:56:20.257Z", "content": "

Hi, I am using vgg16 from http://files.fast.ai/models/vgg16_bn.h5, http://files.fast.ai/models/vgg16_bn_conv.h5 , and Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "Hi, I am using vgg16 from http://files.fast.ai/models/vgg16_bn.h5, http://files.fast.ai/models/vgg16_bn_conv.h5 , and Keras pretrained models : https://keras.io/applications/ " }, { "id": 187393, "postDate": "2017-05-31T05:18:06.533Z", "content": "

I am using the model from https://github.com/pertusa/InceptionBN-21K-for-Caffe

", "rawMarkdown": "I am using the model from https://github.com/pertusa/InceptionBN-21K-for-Caffe" }, { "id": 187380, "postDate": "2017-05-31T04:14:29.300Z", "content": "

I used Res-152-model.caffemodel , Res-101-model.caffemodel , Res-50-model.caffemodel

\n\n

download model from url : https://onedrive.live.com/?authkey=%21AAFW2-FVoxeVRck&id=4006CBB8476FF777%2117887&cid=4006CBB8476FF777

", "rawMarkdown": "I used Res-152-model.caffemodel , Res-101-model.caffemodel , Res-50-model.caffemodel \n\ndownload model from url : https://onedrive.live.com/?authkey=%21AAFW2-FVoxeVRck&id=4006CBB8476FF777%2117887&cid=4006CBB8476FF777\n" }, { "id": 187334, "postDate": "2017-05-31T01:38:25.447Z", "content": "

I am using the model from
\n1. https://github.com/soeaver/caffe-model
\n2. https://github.com/KaimingHe/deep-residual-networks
\n3. https://github.com/pertusa/InceptionBN-21K-for-Caffe
\n4. https://github.com/DeepScale/SqueezeNet

", "rawMarkdown": "I am using the model from \n1. https://github.com/soeaver/caffe-model \n2. https://github.com/KaimingHe/deep-residual-networks \n3. https://github.com/pertusa/InceptionBN-21K-for-Caffe \n4. https://github.com/DeepScale/SqueezeNet" }, { "id": 187133, "postDate": "2017-05-30T15:00:59.117Z", "content": "

Not sure if everyone needs to comment, but in case we do I am using the Keras pretrained models like many others are: https://keras.io/applications/

", "rawMarkdown": "Not sure if everyone needs to comment, but in case we do I am using the Keras pretrained models like many others are: https://keras.io/applications/" }, { "id": 186932, "postDate": "2017-05-29T19:30:45.990Z", "content": "

I'm using the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras pretrained models : https://keras.io/applications/" }, { "id": 186821, "postDate": "2017-05-29T12:41:00.563Z", "content": "

VGG16 from caffe model ZOO https://gist.github.com/ksimonyan/211839e770f7b538e2d8\nResnets from https://drive.google.com/drive/folders/0B9IPQTvr2BBkTXBlZmh1cmlnQ0k\nKeras pretrained models : https://keras.io/applications/\nModels from tensorflow slim: https://github.com/tensorflow/models/tree/master/slim#Pretrained

", "rawMarkdown": "VGG16 from caffe model ZOO https://gist.github.com/ksimonyan/211839e770f7b538e2d8\nResnets from https://drive.google.com/drive/folders/0B9IPQTvr2BBkTXBlZmh1cmlnQ0k\nKeras pretrained models : https://keras.io/applications/\nModels from tensorflow slim: https://github.com/tensorflow/models/tree/master/slim#Pretrained" }, { "id": 186790, "postDate": "2017-05-29T09:17:20.577Z", "content": "

I am using the pre-trained models: \nhttps://keras.io/applications/

", "rawMarkdown": "I am using the pre-trained models: \nhttps://keras.io/applications/" }, { "id": 186754, "postDate": "2017-05-29T07:45:33.690Z", "content": "

using keras pre-trained models - https://keras.io/applications/

", "rawMarkdown": "using keras pre-trained models - https://keras.io/applications/" }, { "id": 186746, "postDate": "2017-05-29T07:19:56.690Z", "content": "

Using keras pretrained models - https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models - https://keras.io/applications/" }, { "id": 186576, "postDate": "2017-05-28T15:43:22.117Z", "content": "

Starting with the Keras models: https://keras.io/applications/

", "rawMarkdown": "Starting with the Keras models: https://keras.io/applications/" }, { "id": 186494, "postDate": "2017-05-28T09:24:55.753Z", "content": "

Also attempting various models starting with vgg16 and others from http://files.fast.ai/models/vgg16_bn.h5 http://files.fast.ai/models/vgg16_bn_conv.h5 http://files.fast.ai/models/vgg16.h5

\n\n

Will consider others as part of ensemble Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

ResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .

\n\n

ResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .

\n\n

VGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .

", "rawMarkdown": "Also attempting various models starting with vgg16 and others from http://files.fast.ai/models/vgg16_bn.h5 http://files.fast.ai/models/vgg16_bn_conv.h5 http://files.fast.ai/models/vgg16.h5\n\nWill consider others as part of ensemble Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz ." }, { "id": 186314, "postDate": "2017-05-27T15:59:39.560Z", "content": "

Also I am using the pre-trained model:\nInception V2. FROM: http://download.tensorflow.org/models/inception_v2_2016_08_28.tar.gz

", "rawMarkdown": "Also I am using the pre-trained model:\nInception V2. FROM: http://download.tensorflow.org/models/inception_v2_2016_08_28.tar.gz" }, { "id": 186265, "postDate": "2017-05-27T09:34:32.737Z", "content": "

Keras models: https://keras.io/applications/

", "rawMarkdown": "Keras models: https://keras.io/applications/" }, { "id": 186211, "postDate": "2017-05-27T03:48:39.200Z", "content": "

Will be using one of those models\nvgg16 and others \nhttp://files.fast.ai/models/vgg16_bn.h5\nhttp://files.fast.ai/models/vgg16_bn_conv.h5\nhttp://files.fast.ai/models/vgg16.h5

\n\n

Will consider others as part of ensemble\nInception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

ResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .

\n\n

ResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .

\n\n

VGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .

", "rawMarkdown": "Will be using one of those models\nvgg16 and others \nhttp://files.fast.ai/models/vgg16_bn.h5\nhttp://files.fast.ai/models/vgg16_bn_conv.h5\nhttp://files.fast.ai/models/vgg16.h5\n\nWill consider others as part of ensemble\nInception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .\n" }, { "id": 186061, "postDate": "2017-05-26T16:21:03.847Z", "content": "

I am using pytorch pretrained models: https://github.com/pytorch/vision/tree/master/torchvision/models

\n\n

ResNet models :

\n\n

resnet50: https://download.pytorch.org/models/resnet50-19c8e357.pth

\n\n

resnet101: https://download.pytorch.org/models/resnet101-5d3b4d8f.pth

\n\n

resnet152: https://download.pytorch.org/models/resnet152-b121ed2d.pth

\n\n

DenseNet models:

\n\n

densenet121: https://download.pytorch.org/models/densenet121-241335ed.pth

\n\n

densenet169: https://download.pytorch.org/models/densenet169-6f0f7f60.pth

\n\n

densenet201: https://download.pytorch.org/models/densenet201-4c113574.pth

\n\n

densenet161: https://download.pytorch.org/models/densenet161-17b70270.pth

\n\n

InceptionV3: https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth

\n\n

VGG Models:

\n\n

vgg16_bn: https://download.pytorch.org/models/vgg16_bn-6c64b313.pth

\n\n

vgg19_bn: https://download.pytorch.org/models/vgg19_bn-c79401a0.pth

", "rawMarkdown": "I am using pytorch pretrained models: https://github.com/pytorch/vision/tree/master/torchvision/models\n\nResNet models :\n\nresnet50: https://download.pytorch.org/models/resnet50-19c8e357.pth\n\nresnet101: https://download.pytorch.org/models/resnet101-5d3b4d8f.pth\n\nresnet152: https://download.pytorch.org/models/resnet152-b121ed2d.pth\n\nDenseNet models:\n \ndensenet121: https://download.pytorch.org/models/densenet121-241335ed.pth\n\ndensenet169: https://download.pytorch.org/models/densenet169-6f0f7f60.pth\n\ndensenet201: https://download.pytorch.org/models/densenet201-4c113574.pth\n\ndensenet161: https://download.pytorch.org/models/densenet161-17b70270.pth\n\nInceptionV3: https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth\n\nVGG Models:\n \nvgg16_bn: https://download.pytorch.org/models/vgg16_bn-6c64b313.pth\n\nvgg19_bn: https://download.pytorch.org/models/vgg19_bn-c79401a0.pth\n\n" }, { "id": 186034, "postDate": "2017-05-26T14:42:35.877Z", "content": "

I use keras applications and SqueezeNet

", "rawMarkdown": " I use [keras applications](https://keras.io/applications/) and [SqueezeNet](https://github.com/rcmalli/keras-squeezenet)\n" }, { "id": 186015, "postDate": "2017-05-26T13:51:45.430Z", "content": "

I'm using the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras pretrained models : https://keras.io/applications/" }, { "id": 185582, "postDate": "2017-05-25T13:55:55.127Z", "content": "

Using Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "Using Keras pretrained models : https://keras.io/applications/" }, { "id": 184597, "postDate": "2017-05-22T13:10:57.130Z", "content": "

I'm using the Keras pretrained models. (VGG16, ResNet50, InceptionV3, Xception).

", "rawMarkdown": "I'm using the Keras pretrained models. (VGG16, ResNet50, InceptionV3, Xception)." }, { "id": 184371, "postDate": "2017-05-21T15:28:02.253Z", "content": "

We are using the pre-trained models available from PyTorch: https://github.com/pytorch/vision

", "rawMarkdown": "We are using the pre-trained models available from PyTorch: https://github.com/pytorch/vision" }, { "id": 184087, "postDate": "2017-05-20T12:23:42.433Z", "content": "

Trying models from https://keras.io/applications/ as well

", "rawMarkdown": "Trying models from https://keras.io/applications/ as well" }, { "id": 184079, "postDate": "2017-05-20T11:31:27.313Z", "content": "

I'm using the Keras pretrained models.\n(InceptionV3, Xception, ResNet50)

", "rawMarkdown": "I'm using the Keras pretrained models.\n(InceptionV3, Xception, ResNet50)" }, { "id": 183994, "postDate": "2017-05-20T01:10:31.663Z", "content": "

using pretrained models from https://keras.io/applications/

", "rawMarkdown": "using pretrained models from https://keras.io/applications/", "replies": [ { "id": 189184, "postDate": "2017-06-05T12:40:05.143Z", "content": "

Also using PyTorch pretrained models:

\n\n

http://pytorch.org/docs/torchvision/models.html

", "rawMarkdown": "Also using PyTorch pretrained models:\n\nhttp://pytorch.org/docs/torchvision/models.html" } ] }, { "id": 183909, "postDate": "2017-05-19T18:08:50.030Z", "content": "

Keras pretrained models with imagenet weights: https://keras.io/applications/

", "rawMarkdown": "Keras pretrained models with imagenet weights: https://keras.io/applications/" }, { "id": 183350, "postDate": "2017-05-18T00:20:24.480Z", "content": "

I'm using inceptionv3 pre-trained on imagenet from keras

", "rawMarkdown": "I'm using inceptionv3 pre-trained on imagenet from keras" }, { "id": 183327, "postDate": "2017-05-17T21:00:58.153Z", "content": "

Keras for me as well.

", "rawMarkdown": "Keras for me as well." }, { "id": 183250, "postDate": "2017-05-17T14:04:25.607Z", "content": "

I am using the Keras pretrained models (https://keras.io/applications/) and the models from Caffe Model Zoo (https://github.com/BVLC/caffe/wiki/Model-Zoo).

", "rawMarkdown": "I am using the Keras pretrained models (https://keras.io/applications/) and the models from Caffe Model Zoo (https://github.com/BVLC/caffe/wiki/Model-Zoo)." }, { "id": 183129, "postDate": "2017-05-17T02:02:15.103Z", "content": "

I am using the model from

", "rawMarkdown": "I am using the model from " }, { "id": 182968, "postDate": "2017-05-16T14:51:22.963Z", "content": "

I'm using the Keras Xception model : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras Xception model : https://keras.io/applications/" }, { "id": 182762, "postDate": "2017-05-15T18:42:14.340Z", "content": "

I'm using VGG_16 with weights from https://github.com/tensorflow/models/blob/master/slim/README.md#Pretrained

", "rawMarkdown": "I'm using VGG_16 with weights from https://github.com/tensorflow/models/blob/master/slim/README.md#Pretrained" }, { "id": 182344, "postDate": "2017-05-13T09:38:55.193Z", "content": "

I'd be using the keras pretrained models: https://keras.io/applications/

", "rawMarkdown": "I'd be using the keras pretrained models: https://keras.io/applications/" }, { "id": 182198, "postDate": "2017-05-12T17:29:11.883Z", "content": "

VGG16 with batch normalization:\nhttp://files.fast.ai/models/vgg16_bn.h5

", "rawMarkdown": "VGG16 with batch normalization:\nhttp://files.fast.ai/models/vgg16_bn.h5\n" }, { "id": 182008, "postDate": "2017-05-11T23:39:01.420Z", "content": "

I m using models from tensorflow https://github.com/tensorflow/models/tree/master/slim#Pretrained

", "rawMarkdown": "I m using models from tensorflow https://github.com/tensorflow/models/tree/master/slim#Pretrained" }, { "id": 181605, "postDate": "2017-05-10T07:45:48Z", "content": "

I am using VGG16 pre-trained on 'imagenet', using keras.

", "rawMarkdown": "I am using VGG16 pre-trained on 'imagenet', using keras." }, { "id": 181305, "postDate": "2017-05-09T05:03:29.690Z", "content": "

I'm using the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras pretrained models : https://keras.io/applications/" }, { "id": 181233, "postDate": "2017-05-08T21:48:28.943Z", "content": "

I am using the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I am using the Keras pretrained models : https://keras.io/applications/" }, { "id": 181227, "postDate": "2017-05-08T21:22:11.903Z", "content": "

Using Keras pretrianed.

", "rawMarkdown": "Using Keras pretrianed." }, { "id": 180907, "postDate": "2017-05-07T21:04:44.350Z", "content": "

I'm also using the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I'm also using the Keras pretrained models : https://keras.io/applications/" }, { "id": 180656, "postDate": "2017-05-06T12:05:27.610Z", "content": "

PyTorch pre-trained models: https://github.com/pytorch/vision#models, https://github.com/pytorch/vision/tree/master/torchvision/models

", "rawMarkdown": "PyTorch pre-trained models: https://github.com/pytorch/vision#models, https://github.com/pytorch/vision/tree/master/torchvision/models" }, { "id": 179784, "postDate": "2017-05-02T21:17:24.527Z", "content": "

Starting with Keras pretrained models as well.

", "rawMarkdown": "Starting with Keras pretrained models as well." }, { "id": 179562, "postDate": "2017-05-02T02:44:39.863Z", "content": "

Using pre-trained models from official pytorch models: https://github.com/pytorch/vision#models

", "rawMarkdown": "Using pre-trained models from official pytorch models: https://github.com/pytorch/vision#models" }, { "id": 179010, "postDate": "2017-04-29T18:14:43.623Z", "content": "

Trying models in https://github.com/tensorflow/models

", "rawMarkdown": "Trying models in https://github.com/tensorflow/models" }, { "id": 178888, "postDate": "2017-04-29T05:57:05.437Z", "content": "

Using Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "Using Keras pretrained models : https://keras.io/applications/" }, { "id": 178848, "postDate": "2017-04-29T02:11:27.423Z", "content": "

I'm also using the Keras pretrained models : https://keras.io/applications/

\n\n

I also plan to try Tensorflow pretrained models: https://github.com/tensorflow/models/tree/master/slim#Pretrained

", "rawMarkdown": "I'm also using the Keras pretrained models : https://keras.io/applications/\n\nI also plan to try Tensorflow pretrained models: https://github.com/tensorflow/models/tree/master/slim#Pretrained\n" }, { "id": 178390, "postDate": "2017-04-27T15:18:18.963Z", "content": "

Keras pretrained models from https://keras.io/applications/\n(i am of course aware that these have been posted before, but im posting since i couldn't find it specified anywhere that i don't need to repost the ones i use)

", "rawMarkdown": "Keras pretrained models from https://keras.io/applications/\n(i am of course aware that these have been posted before, but im posting since i couldn't find it specified anywhere that i don't need to repost the ones i use)" }, { "id": 178203, "postDate": "2017-04-27T00:50:20.070Z", "content": "

I use Inception V3 model pre-trained on ImageNet, from Keras.

", "rawMarkdown": "I use Inception V3 model pre-trained on ImageNet, from Keras." }, { "id": 178114, "postDate": "2017-04-26T17:27:13.107Z", "content": "

I'm using the Keras pretrained models as well : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras pretrained models as well : https://keras.io/applications/" }, { "id": 176792, "postDate": "2017-04-22T00:48:47.420Z", "content": "

Possibly using Keras pre-trained Models (InceptionV3 or VGG16) with batch normalization https://keras.io/applications/

", "rawMarkdown": "Possibly using Keras pre-trained Models (InceptionV3 or VGG16) with batch normalization https://keras.io/applications/" }, { "id": 176647, "postDate": "2017-04-21T09:40:53.740Z", "content": "

using the Keras pretrained models : https://keras.io/applications/\nalso https://github.com/flyyufelix/DenseNet-Keras\nand Resnet152 https://gist.github.com/flyyufelix/7e2eafb149f72f4d38dd661882c554a6

", "rawMarkdown": "using the Keras pretrained models : https://keras.io/applications/\nalso https://github.com/flyyufelix/DenseNet-Keras\nand Resnet152 https://gist.github.com/flyyufelix/7e2eafb149f72f4d38dd661882c554a6" }, { "id": 176623, "postDate": "2017-04-21T08:37:49.257Z", "content": "

Using keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "Using keras pretrained models : https://keras.io/applications/" }, { "id": 175623, "postDate": "2017-04-16T15:15:40.787Z", "content": "

Using vgg16 with batch normalization.

\n\n

Weights for keras model available here http://www.platform.ai/models/vgg16_bn.h5

", "rawMarkdown": "Using vgg16 with batch normalization. \n\nWeights for keras model available here http://www.platform.ai/models/vgg16_bn.h5" }, { "id": 175437, "postDate": "2017-04-15T11:26:54.367Z", "content": "

Might use pre-trained models in Keras

", "rawMarkdown": "Might use pre-trained models in Keras" }, { "id": 175237, "postDate": "2017-04-14T14:26:03.573Z", "content": "

im using models from tensorflow https://github.com/tensorflow/models/tree/master/slim#Pretrained

", "rawMarkdown": "im using models from tensorflow https://github.com/tensorflow/models/tree/master/slim#Pretrained" }, { "id": 174273, "postDate": "2017-04-10T21:25:20.197Z", "content": "

I am using Keras Pre-trained models from Keras Applications

", "rawMarkdown": "I am using Keras Pre-trained models from Keras Applications\n\n\n" }, { "id": 174029, "postDate": "2017-04-10T01:49:11.233Z", "content": "

I'm using Inception V3 model pre-trained on ImageNet, from Keras.

", "rawMarkdown": "I'm using Inception V3 model pre-trained on ImageNet, from Keras." }, { "id": 173973, "postDate": "2017-04-09T17:39:42.920Z", "content": "

I'm using the Keras pretrained models : https://keras.io/applications/

", "rawMarkdown": "I'm using the Keras pretrained models : https://keras.io/applications/" }, { "id": 173748, "postDate": "2017-04-08T11:02:40.833Z", "content": "

I'm using vgg16 with batch normalization, weights can befound here:\nhttp://www.platform.ai/models/

", "rawMarkdown": "I'm using vgg16 with batch normalization, weights can befound here:\nhttp://www.platform.ai/models/", "replies": [ { "id": 176215, "postDate": "2017-04-19T12:33:34.227Z", "content": "

Hey, do you have the model architecture for this in Keras?

", "rawMarkdown": "Hey, do you have the model architecture for this in Keras?" }, { "id": 177624, "postDate": "2017-04-25T11:41:01.123Z", "content": "

I hadn't seen your comments, sorry!\nHere is the Keras architecture:\nhttps://github.com/fastai/courses/blob/master/deeplearning1/nbs/vgg16bn.py

", "rawMarkdown": "I hadn't seen your comments, sorry!\nHere is the Keras architecture:\n[https://github.com/fastai/courses/blob/master/deeplearning1/nbs/vgg16bn.py][1]\n\n\n [1]: https://github.com/fastai/courses/blob/master/deeplearning1/nbs/vgg16bn.py" } ] }, { "id": 172480, "postDate": "2017-04-03T21:22:21.540Z", "content": "

I don't think it counts if I use ResNet50 with random weights, but that's what I might end up doing.

", "rawMarkdown": "I don't think it counts if I use ResNet50 with random weights, but that's what I might end up doing.\n" }, { "id": 172142, "postDate": "2017-04-02T07:03:10.837Z", "content": "

https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py

", "rawMarkdown": "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py" }, { "id": 171929, "postDate": "2017-04-01T00:21:41.437Z", "content": "

Using pretrained models from Caffe model zoo mainly VGG19.

", "rawMarkdown": "Using pretrained models from [Caffe model zoo][1] mainly [VGG19][2].\n\n\n\n [1]: https://github.com/BVLC/caffe/tree/master/models\n [2]: https://gist.github.com/ksimonyan/3785162f95cd2d5fee77#file-readme-md" }, { "id": 169667, "postDate": "2017-03-22T02:11:58.790Z", "content": "

Keras inceptionV3 pre-trained using ImageNet weights.

", "rawMarkdown": "Keras inceptionV3 pre-trained using ImageNet weights." }, { "id": 169242, "postDate": "2017-03-20T08:39:06.277Z", "content": "

I am using Keras Pre-trained models from Keras Applications,\nTensorflow Slim Model Weights from tf-slim, and\nFaster-RCNN, with weights from Faster-RCNN

", "rawMarkdown": "I am using Keras Pre-trained models from [Keras Applications][1],\nTensorflow Slim Model Weights from [tf-slim][2], and\nFaster-RCNN, with weights from [Faster-RCNN][3]\n\n\n [1]: https://keras.io/applications/\n [2]: https://github.com/tensorflow/models/tree/master/slim\n [3]: https://github.com/smallcorgi/Faster-RCNN_TF" }, { "id": 168270, "postDate": "2017-03-16T18:36:05.647Z", "content": "

I'll be using the pre-trained models from here: https://github.com/tensorflow/models/tree/master/slim#pre-trained-models\n(Inception or ResNet, let's see what will work better)

", "rawMarkdown": "I'll be using the pre-trained models from here: https://github.com/tensorflow/models/tree/master/slim#pre-trained-models\n(Inception or ResNet, let's see what will work better)" }, { "id": 167996, "postDate": "2017-03-16T01:18:04.977Z", "content": "

I'm using the Keras pretrained models, https://keras.io/applications/, and the pytorch pretrained models, https://github.com/pytorch/vision/tree/master/torchvision/models

", "rawMarkdown": "I'm using the Keras pretrained models, https://keras.io/applications/, and the pytorch pretrained models, https://github.com/pytorch/vision/tree/master/torchvision/models " }, { "id": 190258, "postDate": "2017-06-07T12:01:59.543Z", "rawMarkdown": "", "isDeleted": true }, { "id": 190212, "postDate": "2017-06-07T10:22:28.623Z", "rawMarkdown": "", "isDeleted": true }, { "id": 189085, "postDate": "2017-06-05T07:15:13.630Z", "rawMarkdown": "", "isDeleted": true }, { "id": 527723, "postDate": "2019-05-06T06:58:48.460Z", "content": "

thank you all..

", "rawMarkdown": "thank you all.." }, { "id": 168142, "postDate": "2017-03-16T11:27:15.567Z", "content": "

Thanks Wendy.

", "rawMarkdown": "Thanks Wendy." } ], "comments": [ { "id": 179659, "author_name": "ZFTurbo", "author_url": "", "post_date": "2017-05-02T12:30:04.413000", "content": "

SqueezeNet: https://github.com/rcmalli/keras-squeezenet

", "votes": 5, "replies": [] }, { "id": 167937, "author_name": "Čeduljko", "author_url": "", "post_date": "2017-03-15T21:06:58.440000", "content": "

From the timeline:

\n\n

\"June 7, 2017 - Pre-trained models posting deadline.\" -- sounds better to non-US ears when month is spelled out.

", "votes": 6, "replies": [ { "id": 168354, "author_name": "Wendy Kan", "author_url": "", "post_date": "2017-03-16T23:02:35.510000", "content": "

Edited. Btw, I'm not from the US either :)

", "votes": 0, "replies": [] } ] }, { "id": 189993, "author_name": "fujisan", "author_url": "", "post_date": "2017-06-07T02:50:41.467000", "content": "

Using keras pretrained models - https://keras.io/applications/\nXception,ResNet50,InceptionV3

", "votes": 1, "replies": [] }, { "id": 186430, "author_name": "李震", "author_url": "", "post_date": "2017-05-28T02:43:59.370000", "content": "

I used caffe model: \nprototxt: https://github.com/soeaver/caffe-model/blob/master/prototxts/inception_resnet_v2_train_test.prototxt\npre-trained model: https://github.com/soeaver/caffe-model\nand\nprototxt: https://gist.github.com/ksimonyan/3785162f95cd2d5fee77#file-readme-md\ncaffemodel: http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_19_layers.caffemodel

", "votes": 1, "replies": [] }, { "id": 177551, "author_name": "PengPai", "author_url": "", "post_date": "2017-04-25T06:43:11.290000", "content": "

I'm using following pre-trained model:\nInceptionV3 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

InceptionV4 from: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.1/inception-v4_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

DenseNet161 from: https://drive.google.com/open?id=0Byy2AcGyEVxfUDZwVjU2cFNidTA

\n\n

ResNet50 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

\n\n

ResNet152 from: https://drive.google.com/file/d/0Byy2AcGyEVxfeXExMzNNOHpEODg/view?usp=sharing

", "votes": 1, "replies": [] }, { "id": 171557, "author_name": "Salsinats", "author_url": "", "post_date": "2017-03-30T14:55:47.180000", "content": "

I am using the pre-trained models from https://www.gradientzoo.com/

", "votes": 1, "replies": [] }, { "id": 186691, "author_name": "Lakshay", "author_url": "", "post_date": "2017-05-29T02:03:53.927000", "content": "

Using keras pretrained models - https://keras.io/applications/

", "votes": 2, "replies": [] }, { "id": 184060, "author_name": "Avant Techno", "author_url": "", "post_date": "2017-05-20T09:30:08.260000", "content": "

I am using the pre-trained models:

\n\n
\n\n

Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .

\n\n

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

\n\n

Inception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .

\n\n

ResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .

\n\n

ResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .

\n\n

VGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .

", "votes": 2, "replies": [] }, { "id": 194324, "author_name": "kuhung ", "author_url": "", "post_date": "2017-06-20T04:33:43.013000", "content": "

Using keras pretrained models - https://keras.io/applications/

\n\n

I learned it yesterday. (´・ω・`)

", "votes": 0, "replies": [] }, { "id": 193856, "author_name": "akshaychawla", "author_url": "", "post_date": "2017-06-18T13:32:36.360000", "content": "

Using keras pretrained model - inception v3 - https://keras.io/applications/

", "votes": 0, "replies": [] }, { "id": 192543, "author_name": "tanya", "author_url": "", "post_date": "2017-06-14T01:13:31.800000", "content": "

We are using the Keras pre-trained models : https://keras.io/applications/#resnet50.

", "votes": 0, "replies": [] }, { "id": 190836, "author_name": "Daniel Burkhardt Cerigo", "author_url": "", "post_date": "2017-06-08T15:50:48.503000", "content": "

Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .

", "votes": 0, "replies": [] }, { "id": 190629, "author_name": "dddd", "author_url": "", "post_date": "2017-06-08T04:49:52.313000", "content": "

Keras pre-trained models - https://keras.io/applications/

", "votes": 0, "replies": [] }, { "id": 190609, "author_name": "Kumar Rohit Malhotra", "author_url": "", "post_date": "2017-06-08T02:59:54.313000", "content": "

using vgg16 pretrained model from https://github.com/fastai/courses/tree/master/deeplearning1/nbs

", "votes": 0, "replies": [] }, { "id": 190593, "author_name": "Katie Li", "author_url": "", "post_date": "2017-06-08T01:34:44.160000", "content": "

I am using keras pretrained model VGG16. May consider others in https://keras.io/applications/

", "votes": 0, "replies": [] }, { "id": 190589, "author_name": "ilyes", "author_url": "", "post_date": "2017-06-08T01:23:33.727000", "content": "

Using keras pretrained models - https://keras.io/applications/

", "votes": 0, "replies": [] }, { "id": 190577, "author_name": "Rob Forgione", "author_url": "", "post_date": "2017-06-08T00:50:00.037000", "content": "

Using keras pretrained models (https://keras.io/applications) as well as vgg16 via vgg16.py and vgg16bn.py located here: https://github.com/fastai/courses/tree/master/deeplearning1/nbs

", "votes": 0, "replies": [] }, { "id": 190576, "author_name": "Kyle Hounslow", "author_url": "", "post_date": "2017-06-08T00:38:33.030000", "content": "

I'm using the Keras pretrained models : https://keras.io/applications/ and TensorFlow-slim models: https://github.com/tensorflow/models/blob/master/inception/inception/slim/README.md

", "votes": 0, "replies": [] }, { "id": 190558, "author_name": "iball41", "author_url": "", "post_date": "2017-06-07T22:49:32.363000", "content": "

Link to Team WolfPack initial model (python-based)!!: https://github.com/iball41/kaggle/blob/master/TPOT_WolfPack.py

", "votes": 0, "replies": [ { "id": 190570, "author_name": "BobHuynh", "author_url": "", "post_date": "2017-06-07T23:43:04.690000", "content": "

Link to Team WolfPack model (Intel Deep Learning Tool-based): https://github.com/bobhuynh/Intel

", "votes": 0, "replies": [] } ] }, { "id": 190548, "author_name": "rmehta1987", "author_url": "", "post_date": "2017-06-07T22:15:21.097000", "content": "

I'm using the caffe pretrained models from Model Zoo.

", "votes": 0, "replies": [] }, { "id": 190537, "author_name": "prasannakumar2012", "author_url": "", "post_date": "2017-06-07T21:11:40.670000", "content": "

I am using keras pretrained models : https://keras.io/applications/

", "votes": 0, "replies": [] }, { "id": 190532, "author_name": "parseltung", "author_url": "", "post_date": "2017-06-07T21:05:32.100000", "content": "

I am using models from\nKeras - https://keras.io/applications/ \nCaffe - https://github.com/BVLC/caffe/wiki/Model-Zoo https://github.com/soeaver/caffe-model

", "votes": 0, "replies": [] }, { "id": 190520, "author_name": "Bill", "author_url": "", "post_date": "2017-06-07T20:33:48.517000", "content": "

We will give a try at the retrained models in Matconvnet

\n\n

http://www.vlfeat.org/matconvnet/pretrained/

", "votes": 0, "replies": [] }, { "id": 190512, "author_name": "Wojtek Rosinski", "author_url": "", "post_date": "2017-06-07T20:16:40.493000", "content": "

Keras pretrained models, Torchvision pretrained models, https://github.com/flyyufelix/DenseNet-Keras & https://github.com/titu1994/DenseNet, https://github.com/yhenon/keras-frcnn, Darknet's YOLO.\nIf a link wasn't provided here, it means that it was already posted in the thread.

", "votes": 0, "replies": [] }, { "id": 190494, "author_name": "Praveen Adepu", "author_url": "", "post_date": "2017-06-07T19:44:06.227000", "content": "

Imagenet pre-trained models from https://keras.io/applications/\nImagenet pre-trained models from https://github.com/flyyufelix/cnn_finetune

", "votes": 0, "replies": [] }, { "id": 190436, "author_name": "Maik Vogt", "author_url": "", "post_date": "2017-06-07T17:27:59.827000", "content": "

Probably using keras pretrained models - https://keras.io/applications/

", "votes": 0, "replies": [] }, { "id": 190428, "author_name": "Gidi Shperber", "author_url": "", "post_date": "2017-06-07T17:15:34.197000", "content": "

i am using https://keras.io/applications/ and https://github.com/rykov8/ssd_keras

", "votes": 0, "replies": [] }, { "id": 190424, "author_name": "Kelwin Fernandes", "author_url": "", "post_date": "2017-06-07T17:09:54.693000", "content": "

My pretrained models https://github.com/fchollet/deep-learning-models

", "votes": 0, "replies": [] }, { "id": 190423, "author_name": "marcinj", "author_url": "", "post_date": "2017-06-07T17:09:02.963000", "content": "

I will be using pre-trained InceptionResnet_V2 from http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz

", "votes": 0, "replies": [] }, { "id": 190416, "author_name": "", "author_url": "", "post_date": "2017-06-07T16:59:23.853000", "content": "", "votes": 0, "replies": [] }, { "id": 190388, "author_name": "", "author_url": "", "post_date": "2017-06-07T15:33:04.947000", "content": "", "votes": 0, "replies": [] }, { "id": 190365, "author_name": "", "author_url": "", "post_date": "2017-06-07T14:53:17.737000", "content": "", "votes": 0, "replies": [] }, { "id": 190362, "author_name": "", "author_url": "", "post_date": "2017-06-07T14:50:21.867000", "content": "", "votes": 0, "replies": [] }, { "id": 190358, "author_name": "", "author_url": "", "post_date": "2017-06-07T14:36:09.643000", "content": "", "votes": 0, "replies": [] }, { "id": 190355, "author_name": "", "author_url": "", "post_date": "2017-06-07T14:32:12.197000", "content": "", "votes": 0, "replies": [] }, { "id": 190352, "author_name": "", "author_url": "", "post_date": "2017-06-07T14:21:54.300000", "content": "", "votes": 0, 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"2017-04-01T00:21:41.437000", "content": "", "votes": 0, "replies": [] }, { "id": 169667, "author_name": "", "author_url": "", "post_date": "2017-03-22T02:11:58.790000", "content": "", "votes": 0, "replies": [] }, { "id": 169242, "author_name": "", "author_url": "", "post_date": "2017-03-20T08:39:06.277000", "content": "", "votes": 0, "replies": [] }, { "id": 168270, "author_name": "", "author_url": "", "post_date": "2017-03-16T18:36:05.647000", "content": "", "votes": 0, "replies": [] }, { "id": 167996, "author_name": "", "author_url": "", "post_date": "2017-03-16T01:18:04.977000", "content": "", "votes": 0, "replies": [] }, { "id": 190258, "author_name": "", "author_url": "", "post_date": "2017-06-07T12:01:59.543000", "content": "", "votes": 0, "replies": [] }, { "id": 190212, "author_name": "", "author_url": "", "post_date": "2017-06-07T10:22:28.623000", "content": "", "votes": 0, "replies": [] }, { "id": 189085, "author_name": "", "author_url": "", "post_date": "2017-06-05T07:15:13.630000", "content": "", "votes": 0, "replies": [] }, { "id": 527723, "author_name": "", "author_url": "", "post_date": "2019-05-06T06:58:48.460000", "content": "", "votes": 0, "replies": [] }, { "id": 168142, "author_name": "", "author_url": "", "post_date": "2017-03-16T11:27:15.567000", "content": "", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "167900": "Please use this thread to share your pre-trained models. Please make sure you do so before June 7, 2017. ", "179659": "SqueezeNet: https://github.com/rcmalli/keras-squeezenet", "167937": "From the timeline:\n\n\"June 7, 2017 - Pre-trained models posting deadline.\" -- sounds better to non-US ears when month is spelled out.", "189993": "Using keras pretrained models - https://keras.io/applications/\nXception,ResNet50,InceptionV3", "186430": "I used caffe model: \nprototxt: https://github.com/soeaver/caffe-model/blob/master/prototxts/inception_resnet_v2_train_test.prototxt\npre-trained model: https://github.com/soeaver/caffe-model\nand\nprototxt: https://gist.github.com/ksimonyan/3785162f95cd2d5fee77#file-readme-md\ncaffemodel: http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_19_layers.caffemodel", "177551": "I'm using following pre-trained model:\nInceptionV3 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nInceptionV4 from: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.1/inception-v4_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nDenseNet161 from: https://drive.google.com/open?id=0Byy2AcGyEVxfUDZwVjU2cFNidTA\n\nResNet50 from: https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nResNet152 from: https://drive.google.com/file/d/0Byy2AcGyEVxfeXExMzNNOHpEODg/view?usp=sharing\n\n", "171557": "I am using the pre-trained models from https://www.gradientzoo.com/", "186691": "Using keras pretrained models - https://keras.io/applications/", "184060": "I am using the pre-trained models:\n\n\n----------\n\n\nInception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .", "194324": "Using keras pretrained models - https://keras.io/applications/\n\nI learned it yesterday. (´・ω・`) ", "193856": "Using keras pretrained model - inception v3 - https://keras.io/applications/", "192543": "We are using the Keras pre-trained models : https://keras.io/applications/#resnet50.", "190836": "Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .", "190629": "Keras pre-trained models - https://keras.io/applications/ ", "190609": "using vgg16 pretrained model from https://github.com/fastai/courses/tree/master/deeplearning1/nbs", "190593": "I am using keras pretrained model VGG16. May consider others in https://keras.io/applications/", "190589": "Using keras pretrained models - https://keras.io/applications/", "190577": "Using keras pretrained models (https://keras.io/applications) as well as vgg16 via vgg16.py and vgg16bn.py located here: https://github.com/fastai/courses/tree/master/deeplearning1/nbs", "190576": "I'm using the Keras pretrained models : https://keras.io/applications/ and TensorFlow-slim models: https://github.com/tensorflow/models/blob/master/inception/inception/slim/README.md ", "190558": "Link to Team WolfPack initial model (python-based)!!: https://github.com/iball41/kaggle/blob/master/TPOT_WolfPack.py\n\n", "190548": "I'm using the caffe pretrained models from Model Zoo. ", "190537": "I am using keras pretrained models : https://keras.io/applications/", "190532": "I am using models from\nKeras - https://keras.io/applications/ \nCaffe - https://github.com/BVLC/caffe/wiki/Model-Zoo https://github.com/soeaver/caffe-model", "190520": "We will give a try at the retrained models in Matconvnet\n\nhttp://www.vlfeat.org/matconvnet/pretrained/", "190512": "Keras pretrained models, Torchvision pretrained models, https://github.com/flyyufelix/DenseNet-Keras & https://github.com/titu1994/DenseNet, https://github.com/yhenon/keras-frcnn, Darknet's YOLO.\nIf a link wasn't provided here, it means that it was already posted in the thread.", "190494": "Imagenet pre-trained models from [https://keras.io/applications/][1]\nImagenet pre-trained models from [https://github.com/flyyufelix/cnn_finetune][2]\n [1]: https://keras.io/applications/\n [2]: https://github.com/flyyufelix/cnn_finetune", "190436": "Probably using keras pretrained models - https://keras.io/applications/\n", "190428": "i am using https://keras.io/applications/ and https://github.com/rykov8/ssd_keras", "190424": "My pretrained models https://github.com/fchollet/deep-learning-models", "190423": "I will be using pre-trained InceptionResnet_V2 from http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz", "190416": "AlexNet, VGG16 and VGG19", "190388": "Keras pretrained models - https://keras.io/applications/\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .", "190365": "Using pretrained darknet models https://pjreddie.com/darknet/yolo/", "190362": "I am using https://keras.io/applications/", "190358": "pretrained model: https://keras.io/applications/\nhttps://github.com/udacity/deep-learning/tree/master/transfer-learning/tensorflow_vgg", "190355": "Checking out:\nhttps://keras.io/applications/\nhttps://github.com/farizrahman4u/keras-contrib/tree/master/keras_contrib/applications\nhttps://github.com/flyyufelix/cnn_finetune\nhttps://github.com/BVLC/caffe/wiki/Model-Zoo\nhttps://github.com/soeaver/caffe-model", "190352": "Pretrained resnet, inception-v3, resnet-inception-v2", "190345": "Using keras pretrained models - https://keras.io/applications/", "190344": "Keras pretrained models - https://keras.io/applications/\n\nSqueezeNet: https://github.com/rcmalli/keras-squeezenet\n\nInception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .\n\nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo\n\nPytorch Vision model - https://github.com/pytorch/vision#models\n\nMxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery\n\nTorch pre-trained Resnet from Facebook - https://github.com/facebook/fb.resnet.torch/tree/master/pretrained", "190290": "Pretrained models from https://keras.io/applications and https://github.com/fchollet/deep-learning-models.", "190285": "We are using pre-trained Models InceptionV3 or VGG16.", "190253": "Using the models from the following libraries:\n\nKeras pre-trained models - https://keras.io/applications/ \nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo ", "190197": "Using Keras pre-trained model : https://keras.io/applications/ + 1\n", "190170": "Using keras pretrained models - https://keras.io/applications/", "190158": "I am using keras pretrained models - https://keras.io/applications/", "190129": "**caffe**: Reference CaffeNet, AlexNet, GoogLeNet, VGG19 http://caffe.berkeleyvision.org/model_zoo.html https://github.com/BVLC/caffe/wiki/Model-Zoo#models-used-by-the-vgg-team-in-ilsvrc-2014\n\n**darknet**: darknet19 448 yolo2 darknet19_448.conv.23 https://pjreddie.com/darknet/imagenet/ https://pjreddie.com/darknet/yolo/ https://pjreddie.com/darknet/imagenet/ \n\n**keras**: https://keras.io/applications/", "190082": "I will be using DenseNet implemented in keras from[https://github.com/flyyufelix/DenseNet-Keras][1] and imagenet models\n\n\n [1]: https://github.com/flyyufelix/DenseNet-Keras", "190077": "I am using keras pretrained models - https://keras.io/applications/\n", "190072": "I am using https://github.com/fchollet/deep-learning-models/blob/master/resnet50.py", "190065": "I am using following pretrained models:\n\n 1. Inception V4: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz\n 2. Inception Resnet V2: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz\n 3. ResNet V2 50: http://download.tensorflow.org/models/resnet_v2_50_2017_04_14.tar.gz\n 4. ResNet V2 101: http://download.tensorflow.org/models/resnet_v2_101_2017_04_14.tar.gz\n 5. VGG 16: https://www.cs.toronto.edu/~frossard/vgg16/vgg16_weights.npz", "190053": "Also using keras pretraind models https://keras.io/applications/", "190029": "PyTorch pretrained models:\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models", "189988": "Mxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery ", "189983": "Using Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .", "189972": "Also using MXNet pretrained models from http://data.dmlc.ml/models", "189921": "I am using keras pretrained models: https://keras.io/applications/", "189855": "based on keras.applications.VGG16", "189802": " - https://github.com/facebookresearch/ResNeXt\n - https://github.com/facebook/fb.resnet.torch", "189759": "Using Keras pre-trained models: https://keras.io/applications/", "189758": "Also using Keras pre-trained models (https://keras.io/applications/)", "189722": "Hey, I'm also using the Keras pre-trained model;\nhttps://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5 ", "189712": "Using Keras pretrained models : https://keras.io/applications/\n", "189711": "Keras models: https://keras.io/applications/", "189696": "Using models:\nXception\nVGG16\nVGG19\nResNet50\nInceptionV3\n\nfrom https://keras.io/applications/", "189685": "I will also try caffe https://github.com/soeaver/caffe-model/blob/master/prototxts/inception_resnet_v2_train_test.prototxt", "189684": "Googlenet | Alexnet | Resnet | Inception | VGG | LeNet\n", "189675": "Using\nKeras - Squeezenet: https://github.com/rcmalli/keras-squeezenet\nPytorch pretrained models: https://github.com/pytorch/vision#models\nKeras pretrained models: https://keras.io/applications/\nFast.ai pretrained models: files.fast.ai\nand some more from here: https://github.com/flyyufelix/cnn_finetune", "189674": "Using keras pretrained models - https://keras.io/applications/", "189621": "Using Keras Pretrained models : https://keras.io/applications/#resnet50", "189600": "I am using the resnet50 model with keras from the keras library:\nhttps://keras.io/applications/ ", "189585": "Using SSD port https://github.com/rykov8/ssd_keras and keras pretrained models - https://keras.io/applications/", "189540": "might use pre-trained models in Keras: https://keras.io/applications/", "189516": "I am using Torch pre-trained models from Facebook: \nhttps://github.com/facebook/fb.resnet.torch/tree/master/pretrained\nhttps://github.com/facebookresearch/ResNeXt", "189475": "I'm using Inception V3, ResNet, VGG, FCN and a slightly modified version of the same", "189469": "I'm using keras pretrained models from applications submodule", "189428": "Using pre-trained models from: \nhttps://github.com/BVLC/caffe/wiki/Model-Zoo \nhttps://github.com/soeaver/caffe-model", "189404": "I'm using the Keras pretrained models as well : https://keras.io/applications/\n", "189366": "using https://keras.io/applications/ :btw do we need to even post this if it is already been posted?\n\nAlso using nets I pretrained myself on ILSVRC2012 imagenet CLS ", "189357": "Inception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .", "189339": "Using keras pretrained models - https://keras.io/applications/", "189269": "I used the Keras pre-trained model: \nhttps://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5", "189215": "Using MXNet pretrained models - http://data.dmlc.ml/models", "189214": "Using MXNet pretrained models - http://data.dmlc.ml/models", "189213": "Using MXNet pretrained models from http://data.dmlc.ml/models", "189212": "Using MXNet pretrained models - http://data.dmlc.ml/models", "189172": " ImageNet Pretrained Weights \n https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_th_dim_ordering_th_kernels.h5\n", "189155": "I'm trying different pre-trained models and I'll select 1 or 2 for the final 2 submitions: \n vgg16 and others from http://files.fast.ai/models/vgg16_bn.h5 http://files.fast.ai/models/vgg16_bn_conv.h5 http://files.fast.ai/models/vgg16.h5\n\n Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .\nGoogleNet and Caffe from Intel sdk tool", "189140": "and also the Keras pretrained models : https://keras.io/applications/", "189116": "Using keras pretrained models - https://keras.io/applications/", "189040": "Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nInception V4. FROM: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .", "189007": "Using: https://keras.io/applications/\nOr/And: https://github.com/titu1994/DenseNet\nhttps://github.com/rcmalli/keras-squeezenet", "188888": "Using various pre-trained models from :\n[https://github.com/syeddanish41/cnn_finetune][1]\n\n\n [1]: https://github.com/syeddanish41/cnn_finetune", "188881": "Using keras pretrained models - https://keras.io/applications/", "188837": "Original vgg16, vgg16 with batch normalization, and vgg19", "188830": "Using keras pretrained models - https://keras.io/applications/\nAnd fast.ai pretrained models - http://files.fast.ai/models/", "188828": "I am using the models from following libraries: \n\nKeras pre-trained models - https://keras.io/applications/ \nCaffe pre-trained models - https://github.com/BVLC/caffe/wiki/Model-Zoo \nPytorch Vision model - https://github.com/pytorch/vision#models \nMxnet pre-trained models - https://github.com/dmlc/mxnet-model-gallery \nTorch pre-trained Resnet from Facebook - https://github.com/facebook/fb.resnet.torch/tree/master/pretrained \n\n", "188799": "Keras pretrained models: https://keras.io/applications/\n\nKeras 2 Inception V4: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.1/\n\nKeras 1 Inception V4: https://github.com/kentsommer/keras-inceptionV4/releases/download/2.0/\n", "188784": "Using Keras pretrained models: https://keras.io/applications/", "188638": "I am using keras pre-trained models vgg16 or vgg19 from Keras Applications", "188628": "Using keras pretrained models - https://keras.io/applications/", "188447": "I am using Pre-trained models:\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nInception V2. FROM: http://download.tensorflow.org/models/inception_v2_2016_08_28.tar.gz .\n\nInception V4. FROM: http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz .\n", "188413": "using vgg-* resnet-* pretrained from keras: https://keras.io/applications\n\n\nvgg-* resnet-* inception-v3 densenet-*\nfrom pytorch https://github.com/pytorch/vision/tree/master/torchvision/models\n", "188399": "torch pretrained\nhttps://github.com/facebook/fb.resnet.torch/tree/master/pretrained\n\nLasagne model zoo\nhttps://github.com/Lasagne/Recipes/tree/master/modelzoo\n", "188295": "Keras models: https://keras.io/applications/", "188274": "I am using the VGG19 model among others from Keras https://keras.io/applications/", "188225": "We are using Keras pretrained models with imagenet weights: https://keras.io/applications/", "188147": "**From Microsoft CNTK:**\n\nResNet 101: https://migonzastorage.blob.core.windows.net/deep-learning/models/cntk/imagenet/ResNet_101.model\n\nResNet 152: https://migonzastorage.blob.core.windows.net/deep-learning/models/cntk/imagenet/ResNet_152.model\n\n\n**From Keras:**\n\nResNet 50: https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nVGG 16: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nVGG 19: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nInceptionV3: https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n\nXception: https://github.com/fchollet/deep-learning-models/releases/download/v0.4/xception_weights_tf_dim_ordering_tf_kernels_notop.h5\n\n", "188101": "I used caffe model : [bvlc_googlenet][1]\n\n\n [1]: https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet", "188096": "using ResNet-50 from https://onedrive.live.com/?authkey=%21AAFW2-FVoxeVRck&id=4006CBB8476FF777%2117887&cid=4006CBB8476FF777", "188082": "DenseNet for Keras: https://github.com/flyyufelix/DenseNet-Keras", "188081": "I'm using the Keras pretrained models : https://keras.io/applications/", "188073": "I use Keras' pretrained models : https://keras.io/applications\n", "188059": "I'm using some of the caffe standard models: resnet-50, google1, vgg-19, squeezenet, ...", "187594": "Hi, I am using vgg16 from http://files.fast.ai/models/vgg16_bn.h5, http://files.fast.ai/models/vgg16_bn_conv.h5 , and Keras pretrained models : https://keras.io/applications/ ", "187393": "I am using the model from https://github.com/pertusa/InceptionBN-21K-for-Caffe", "187380": "I used Res-152-model.caffemodel , Res-101-model.caffemodel , Res-50-model.caffemodel \n\ndownload model from url : https://onedrive.live.com/?authkey=%21AAFW2-FVoxeVRck&id=4006CBB8476FF777%2117887&cid=4006CBB8476FF777\n", "187334": "I am using the model from \n1. https://github.com/soeaver/caffe-model \n2. https://github.com/KaimingHe/deep-residual-networks \n3. https://github.com/pertusa/InceptionBN-21K-for-Caffe \n4. https://github.com/DeepScale/SqueezeNet", "187133": "Not sure if everyone needs to comment, but in case we do I am using the Keras pretrained models like many others are: https://keras.io/applications/", "186932": "I'm using the Keras pretrained models : https://keras.io/applications/", "186821": "VGG16 from caffe model ZOO https://gist.github.com/ksimonyan/211839e770f7b538e2d8\nResnets from https://drive.google.com/drive/folders/0B9IPQTvr2BBkTXBlZmh1cmlnQ0k\nKeras pretrained models : https://keras.io/applications/\nModels from tensorflow slim: https://github.com/tensorflow/models/tree/master/slim#Pretrained", "186790": "I am using the pre-trained models: \nhttps://keras.io/applications/", "186754": "using keras pre-trained models - https://keras.io/applications/", "186746": "Using keras pretrained models - https://keras.io/applications/", "186576": "Starting with the Keras models: https://keras.io/applications/", "186494": "Also attempting various models starting with vgg16 and others from http://files.fast.ai/models/vgg16_bn.h5 http://files.fast.ai/models/vgg16_bn_conv.h5 http://files.fast.ai/models/vgg16.h5\n\nWill consider others as part of ensemble Inception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .", "186314": "Also I am using the pre-trained model:\nInception V2. FROM: http://download.tensorflow.org/models/inception_v2_2016_08_28.tar.gz", "186265": "Keras models: https://keras.io/applications/", "186211": "Will be using one of those models\nvgg16 and others \nhttp://files.fast.ai/models/vgg16_bn.h5\nhttp://files.fast.ai/models/vgg16_bn_conv.h5\nhttp://files.fast.ai/models/vgg16.h5\n\nWill consider others as part of ensemble\nInception V1. FROM: http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz .\n\nInception V3. FROM: http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz .\n\nInception-ResNet-v2. FROM: http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz .\n\nResNet 50. FROM: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz .\n\nResNet 101. FROM: http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz .\n\nVGG 19. FROM: http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz .\n", "186061": "I am using pytorch pretrained models: https://github.com/pytorch/vision/tree/master/torchvision/models\n\nResNet models :\n\nresnet50: https://download.pytorch.org/models/resnet50-19c8e357.pth\n\nresnet101: https://download.pytorch.org/models/resnet101-5d3b4d8f.pth\n\nresnet152: https://download.pytorch.org/models/resnet152-b121ed2d.pth\n\nDenseNet models:\n \ndensenet121: https://download.pytorch.org/models/densenet121-241335ed.pth\n\ndensenet169: https://download.pytorch.org/models/densenet169-6f0f7f60.pth\n\ndensenet201: https://download.pytorch.org/models/densenet201-4c113574.pth\n\ndensenet161: https://download.pytorch.org/models/densenet161-17b70270.pth\n\nInceptionV3: https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth\n\nVGG Models:\n \nvgg16_bn: https://download.pytorch.org/models/vgg16_bn-6c64b313.pth\n\nvgg19_bn: https://download.pytorch.org/models/vgg19_bn-c79401a0.pth\n\n", "186034": " I use [keras applications](https://keras.io/applications/) and [SqueezeNet](https://github.com/rcmalli/keras-squeezenet)\n", "186015": "I'm using the Keras pretrained models : https://keras.io/applications/", "185582": "Using Keras pretrained models : https://keras.io/applications/", "184597": "I'm using the Keras pretrained models. (VGG16, ResNet50, InceptionV3, Xception).", "184371": "We are using the pre-trained models available from PyTorch: https://github.com/pytorch/vision", "184087": "Trying models from https://keras.io/applications/ as well", "184079": "I'm using the Keras pretrained models.\n(InceptionV3, Xception, ResNet50)", "183994": "using pretrained models from https://keras.io/applications/", "183909": "Keras pretrained models with imagenet weights: https://keras.io/applications/", "183350": "I'm using inceptionv3 pre-trained on imagenet from keras", "183327": "Keras for me as well.", "183250": "I am using the Keras pretrained models (https://keras.io/applications/) and the models from Caffe Model Zoo (https://github.com/BVLC/caffe/wiki/Model-Zoo).", "183129": "I am using the model from ", "182968": "I'm using the Keras Xception model : https://keras.io/applications/", "182762": "I'm using VGG_16 with weights from https://github.com/tensorflow/models/blob/master/slim/README.md#Pretrained", "182344": "I'd be using the keras pretrained models: https://keras.io/applications/", "182198": "VGG16 with batch normalization:\nhttp://files.fast.ai/models/vgg16_bn.h5\n", "182008": "I m using models from tensorflow https://github.com/tensorflow/models/tree/master/slim#Pretrained", "181605": "I am using VGG16 pre-trained on 'imagenet', using keras.", "181305": "I'm using the Keras pretrained models : https://keras.io/applications/", "181233": "I am using the Keras pretrained models : https://keras.io/applications/", "181227": "Using Keras pretrianed.", "180907": "I'm also using the Keras pretrained models : https://keras.io/applications/", "180656": "PyTorch pre-trained models: https://github.com/pytorch/vision#models, https://github.com/pytorch/vision/tree/master/torchvision/models", "179784": "Starting with Keras pretrained models as well.", "179562": "Using pre-trained models from official pytorch models: https://github.com/pytorch/vision#models", "179010": "Trying models in https://github.com/tensorflow/models", "178888": "Using Keras pretrained models : https://keras.io/applications/", "178848": "I'm also using the Keras pretrained models : https://keras.io/applications/\n\nI also plan to try Tensorflow pretrained models: https://github.com/tensorflow/models/tree/master/slim#Pretrained\n", "178390": "Keras pretrained models from https://keras.io/applications/\n(i am of course aware that these have been posted before, but im posting since i couldn't find it specified anywhere that i don't need to repost the ones i use)", "178203": "I use Inception V3 model pre-trained on ImageNet, from Keras.", "178114": "I'm using the Keras pretrained models as well : https://keras.io/applications/", "176792": "Possibly using Keras pre-trained Models (InceptionV3 or VGG16) with batch normalization https://keras.io/applications/", "176647": "using the Keras pretrained models : https://keras.io/applications/\nalso https://github.com/flyyufelix/DenseNet-Keras\nand Resnet152 https://gist.github.com/flyyufelix/7e2eafb149f72f4d38dd661882c554a6", "176623": "Using keras pretrained models : https://keras.io/applications/", "175623": "Using vgg16 with batch normalization. \n\nWeights for keras model available here http://www.platform.ai/models/vgg16_bn.h5", "175437": "Might use pre-trained models in Keras", "175237": "im using models from tensorflow https://github.com/tensorflow/models/tree/master/slim#Pretrained", "174273": "I am using Keras Pre-trained models from Keras Applications\n\n\n", "174029": "I'm using Inception V3 model pre-trained on ImageNet, from Keras.", "173973": "I'm using the Keras pretrained models : https://keras.io/applications/", "173748": "I'm using vgg16 with batch normalization, weights can befound here:\nhttp://www.platform.ai/models/", "172480": "I don't think it counts if I use ResNet50 with random weights, but that's what I might end up doing.\n", "172142": "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py", "171929": "Using pretrained models from [Caffe model zoo][1] mainly [VGG19][2].\n\n\n\n [1]: https://github.com/BVLC/caffe/tree/master/models\n [2]: https://gist.github.com/ksimonyan/3785162f95cd2d5fee77#file-readme-md", "169667": "Keras inceptionV3 pre-trained using ImageNet weights.", "169242": "I am using Keras Pre-trained models from [Keras Applications][1],\nTensorflow Slim Model Weights from [tf-slim][2], and\nFaster-RCNN, with weights from [Faster-RCNN][3]\n\n\n [1]: https://keras.io/applications/\n [2]: https://github.com/tensorflow/models/tree/master/slim\n [3]: https://github.com/smallcorgi/Faster-RCNN_TF", "168270": "I'll be using the pre-trained models from here: https://github.com/tensorflow/models/tree/master/slim#pre-trained-models\n(Inception or ResNet, let's see what will work better)", "167996": "I'm using the Keras pretrained models, https://keras.io/applications/, and the pytorch pretrained models, https://github.com/pytorch/vision/tree/master/torchvision/models ", "190258": "", "190212": "", "189085": "", "527723": "thank you all..", "168142": "Thanks Wendy." } }