![\"enter](\"https://storage.googleapis.com/kaggle-forum-message-attachments/233562/7719/amzon.png\" "\\"\\"")
Per the competition rules, please post external data in this thread.
\n\nPlease refer to the Rules page for additional details.
", "messages": [ { "id": "221288", "postDate": "09/14/2017 17:32:23", "content": "Per the competition rules, please post external data in this thread.
\n\nPlease refer to the Rules page for additional details.
", "rawMarkdown": "Per the competition rules, please post external data in this thread.\n\nAre we allowed to use pre-trained models like thoose avaliable in https://keras.io/applications ?
", "rawMarkdown": "Are we allowed to use pre-trained models like thoose avaliable in https://keras.io/applications ?", "votes": null }, { "id": "221713", "postDate": "09/16/2017 09:04:01", "content": "Torchvision pre-trained models: https://github.com/pytorch/vision
", "rawMarkdown": "Torchvision pre-trained models: https://github.com/pytorch/vision", "votes": null }, { "id": "221723", "postDate": "09/16/2017 09:49:47", "content": "Did you read the post?
\n\n\n", "rawMarkdown": "Did you read the post?\n> Use of publicly available external data is permitted, provided it does not pertain to Cdiscount. For example, you may use pre-trained networks or natural language tools/libraries.", "votes": null }, { "id": "222212", "postDate": "09/18/2017 04:48:38", "content": "Use of publicly available external data is permitted, provided it does not pertain to Cdiscount. For example, you may use pre-trained networks or natural language tools/libraries.
\n
list of Pretrained:
\n\nInceptionV3
", "rawMarkdown": "InceptionV3", "votes": null }, { "id": "222680", "postDate": "09/19/2017 17:35:48", "content": "Keras application: ResNet50, MobileNet
", "rawMarkdown": "[Keras application][1]: ResNet50, MobileNet\n\n\n [1]: https://github.com/fchollet/keras/tree/master/keras/applications", "votes": null }, { "id": "222753", "postDate": "09/19/2017 22:01:24", "content": "Pretrained: InceptionV4 https://github.com/flyyufelix/cnn_finetune
", "rawMarkdown": "Pretrained: InceptionV4 https://github.com/flyyufelix/cnn_finetune", "votes": null }, { "id": "222770", "postDate": "09/20/2017 01:37:14", "content": "I am not sure why people are so specific when declaring Keras pre-trained models.
\n\nAll from https://keras.io/applications/
", "rawMarkdown": "I am not sure why people are so specific when declaring Keras pre-trained models.\n\nAll from https://keras.io/applications/", "votes": null }, { "id": "223983", "postDate": "09/24/2017 15:47:45", "content": "The Models from https://keras.io/applications/
", "rawMarkdown": "The Models from https://keras.io/applications/", "votes": null }, { "id": "224219", "postDate": "09/25/2017 14:57:55", "content": "I am wondering if someone will manually labels the test set. It is kind of evil but feasible.
", "rawMarkdown": "I am wondering if someone will manually labels the test set. It is kind of evil but feasible.", "votes": null }, { "id": "224220", "postDate": "09/25/2017 14:59:53", "content": "That's against the rules.
\n\n\"Submissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.\"
", "rawMarkdown": "That's against the rules.\n\n\"Submissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.\"", "votes": null }, { "id": "224665", "postDate": "09/27/2017 07:04:53", "content": "Hello,\ncould you please clarify if using corporate data that we have rights to is permitted? So we could specify the source of the data, but we can't share the data.
", "rawMarkdown": "Hello,\ncould you please clarify if using corporate data that we have rights to is permitted? So we could specify the source of the data, but we can't share the data.", "votes": null }, { "id": "224710", "postDate": "09/27/2017 12:02:50", "content": "The rules are pretty clear: If your data is not publicly available then you cannot use it for this competition.
", "rawMarkdown": "The rules are pretty clear: If your data is not publicly available then you cannot use it for this competition.", "votes": null }, { "id": "225080", "postDate": "09/28/2017 07:35:13", "content": "All models listed on this page: \nhttps://github.com/tensorflow/models/tree/master/research/slim
", "rawMarkdown": "All models listed on this page: \nhttps://github.com/tensorflow/models/tree/master/research/slim", "votes": null }, { "id": "228339", "postDate": "10/06/2017 13:21:09", "content": "Pre-trained models from https://keras.io/applications/
", "rawMarkdown": "Pre-trained models from https://keras.io/applications/", "votes": null }, { "id": "228512", "postDate": "10/06/2017 22:09:10", "content": "Pre-trained models from https://keras.io/applications/
", "rawMarkdown": "Pre-trained models from https://keras.io/applications/", "votes": null }, { "id": "229832", "postDate": "10/10/2017 15:52:10", "content": "also, Pre-trained models from https://keras.io/applications/
", "rawMarkdown": "also, Pre-trained models from https://keras.io/applications/", "votes": null }, { "id": "230018", "postDate": "10/11/2017 03:39:31", "content": "All models listed on this page.
", "rawMarkdown": "All models listed on this page.", "votes": null }, { "id": "233555", "postDate": "10/20/2017 14:26:58", "content": "is crawling google web images allowed?
\n\ne.g. if i find there are rare classes like 'xxx' and i use google search to download such images ( filter off images from Cdiscount's website) can they be used?
\n\ni can made such images public to all participants.
", "rawMarkdown": "is crawling google web images allowed?\n\n e.g. if i find there are rare classes like 'xxx' and i use google search to download such images ( filter off images from Cdiscount's website) can they be used?\n\ni can made such images public to all participants.", "votes": null }, { "id": "233562", "postDate": "10/20/2017 14:34:40", "content": "Amazon dataset:
\n\nhttp://jmcauley.ucsd.edu/data/amazon/
\n\nhttp://cseweb.ucsd.edu/~jmcauley/pdfs/sigir15.pdf
\n\n{\n \"asin\": \"0000031852\",\n \"title\": \"Girls Ballet Tutu Zebra Hot Pink\",\n \"price\": 3.17,\n \"imUrl\": \"http://ecx.images-amazon.com/images/I/51fAmVkTbyL._SY300_.jpg\",\n ...\n}\n
@Heng CherKeng, there is no license information for the Amazon dataset.
", "rawMarkdown": "Heng CherKeng, there is no license information for the Amazon dataset.", "votes": null }, { "id": "233590", "postDate": "10/20/2017 16:08:51", "content": "This data can be almost cheating! Books & CD are most difficult ones in this competition, but it is quite normalized in shape. So you can just identify them in cdiscount data and look up those in amazon data. \nBTW, to download the data, you need to contact the author. I'm not sure whether this can be considered as public data.
", "rawMarkdown": "This data can be almost cheating! Books & CD are most difficult ones in this competition, but it is quite normalized in shape. So you can just identify them in cdiscount data and look up those in amazon data. \nBTW, to download the data, you need to contact the author. I'm not sure whether this can be considered as public data.", "votes": null }, { "id": "233854", "postDate": "10/21/2017 15:07:27", "content": "i am writing e-mail to the organizer and ask about license information.
\n\nWhether the data can be used or not, i have to wait for response from the kaggle administrator of this thread.
", "rawMarkdown": "i am writing e-mail to the organizer and ask about license information. \n\nWhether the data can be used or not, i have to wait for response from the kaggle administrator of this thread.", "votes": null }, { "id": "233855", "postDate": "10/21/2017 15:08:28", "content": "https://archive.org/details/audio-covers
\n\none million CD cover data
\n\n![\"enter](\"https://archive.org/download/audio-covers/covers.png\" "\\"\\"")
@inversion
\n\nI would like to confirm if my posted \"one million CD cover data\" and \"Amazon dataset\" can be used or not. Thanks!
", "rawMarkdown": "inversion \n\nI would like to confirm if my posted \"one million CD cover data\" and \"Amazon dataset\" can be used or not. Thanks!", "votes": null }, { "id": "238264", "postDate": "11/01/2017 01:54:58", "content": "i wonder if this can be used?
\n\nhttp://vision.is.tohoku.ac.jp/~kyamagu/research/etsy-dataset/
", "rawMarkdown": "i wonder if this can be used?\n\nhttp://vision.is.tohoku.ac.jp/~kyamagu/research/etsy-dataset/", "votes": null }, { "id": "241462", "postDate": "11/08/2017 21:52:22", "content": "Pre-trained models from Keras: https://keras.io/applications/
", "rawMarkdown": "Pre-trained models from Keras: https://keras.io/applications/", "votes": null }, { "id": "243034", "postDate": "11/13/2017 07:39:13", "content": "Pre-trained models from https://keras.io/applications/ and https://github.com/flyyufelix/DenseNet-Keras + any other pretrained models listed in this thread
", "rawMarkdown": "Pre-trained models from https://keras.io/applications/ and https://github.com/flyyufelix/DenseNet-Keras + any other pretrained models listed in this thread", "votes": null }, { "id": "243372", "postDate": "11/13/2017 22:34:39", "content": "pretrained model l used:
\n\nhttps://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\n\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
\n\nhttps://github.com/mapillary/inplace_abn
", "rawMarkdown": "pretrained model l used:\n\nhttps://github.com/Cadene/pretrained-models.pytorch\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models\n\nhttps://github.com/hujie-frank/SENet\n\nhttps://github.com/shicai/SENet-Caffe\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\n\nhttps://github.com/apache/incubator-mxnet/blob/master/example/image-classification/common/modelzoo.py\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained\n\nhttps://github.com/mapillary/inplace_abn", "votes": null }, { "id": "246575", "postDate": "11/21/2017 10:58:55", "content": "pretrained models supported by the fastai library
", "rawMarkdown": "pretrained models supported by the [fastai][1] library\n\n\n [1]: https://github.com/fastai", "votes": null }, { "id": "246645", "postDate": "11/21/2017 14:05:57", "content": "I use these models\nhttps://github.com/clcarwin/convert_torch_to_pytorch
", "rawMarkdown": "I use these models\nhttps://github.com/clcarwin/convert_torch_to_pytorch", "votes": null }, { "id": "247289", "postDate": "11/22/2017 18:21:59", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
\n\nhttps://github.com/tianzhi0549/CTPN
\n\nhttps://github.com/AKSHAYUBHAT/CTPN8
\n\nhttps://github.com/meijieru/crnn.pytorch
\n\nhttps://github.com/Bartzi/stn-ocr
\n\nhttps://code.google.com/archive/p/word2vec/
\n\nhttps://nlp.stanford.edu/projects/glove/
\n\nhttps://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md
", "rawMarkdown": "https://github.com/Cadene/pretrained-models.pytorch\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models\n\nhttps://github.com/hujie-frank/SENet\n\nhttps://github.com/shicai/SENet-Caffe\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained\n\nhttps://github.com/tianzhi0549/CTPN\n\nhttps://github.com/AKSHAYUBHAT/CTPN8\n\nhttps://github.com/meijieru/crnn.pytorch\n\nhttps://github.com/Bartzi/stn-ocr\n\nhttps://code.google.com/archive/p/word2vec/ \n\nhttps://nlp.stanford.edu/projects/glove/ \n\nhttps://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md", "votes": null }, { "id": "247466", "postDate": "11/23/2017 05:20:40", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\n\n\nhttps://keras.io/applications/
", "rawMarkdown": "https://github.com/Cadene/pretrained-models.pytorch\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models\n\nhttps://github.com/hujie-frank/SENet\n\nhttps://github.com/shicai/SENet-Caffe\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\n\nhttps://github.com/apache/incubator-mxnet/blob/master/example/image-classification/common/modelzoo.py\n\nhttps://keras.io/applications/", "votes": null }, { "id": "247528", "postDate": "11/23/2017 09:42:44", "content": "list of pretrained models:\nhttps://keras.io/applications/\nhttps://github.com/shicai/SENet-Caffe\nhttps://gist.github.com/flyyufelix
", "rawMarkdown": "list of pretrained models:\nhttps://keras.io/applications/\nhttps://github.com/shicai/SENet-Caffe\nhttps://gist.github.com/flyyufelix", "votes": null }, { "id": "247815", "postDate": "11/24/2017 00:18:00", "content": "https://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/Cadene/pretrained-models.pytorch
", "rawMarkdown": "https://github.com/pytorch/vision/tree/master/torchvision/models\n\nhttps://github.com/Cadene/pretrained-models.pytorch", "votes": null }, { "id": "248129", "postDate": "11/24/2017 22:53:17", "content": "https://github.com/pytorch/vision\nhttps://keras.io/applications/\nhttps://github.com/flyyufelix/DenseNet-Keras
", "rawMarkdown": "https://github.com/pytorch/vision\nhttps://keras.io/applications/\nhttps://github.com/flyyufelix/DenseNet-Keras", "votes": null }, { "id": "248165", "postDate": "11/25/2017 05:14:40", "content": "pretrained InceptionResNetV2 from https://keras.io/applications/\npretrained Inception-V4 ResNet-101 ResNet-152 from https://github.com/flyyufelix/cnn_finetune
", "rawMarkdown": "pretrained InceptionResNetV2 from https://keras.io/applications/\npretrained Inception-V4 ResNet-101 ResNet-152 from https://github.com/flyyufelix/cnn_finetune", "votes": null }, { "id": "248347", "postDate": "11/25/2017 19:27:42", "content": "I will use any of the models listed here atm (+ whenever someone lists something new I might still possibly that as well)\nI will use any data listed here
", "rawMarkdown": "I will use any of the models listed here atm (+ whenever someone lists something new I might still possibly that as well)\nI will use any data listed here", "votes": null }, { "id": "248477", "postDate": "11/26/2017 08:00:12", "content": "Pre-trained Dual Path Network\nhttps://github.com/cypw/DPNs
Pre-trained DenseNet\nhttps://github.com/miraclewkf/DenseNet
Pre-trained ResNet, ResNext\nhttps://github.com/apache/incubator-mxnet/tree/master/example/image-classification#pre-trained-models
Pretrained models from:\n1) https://github.com/hujie-frank/SENet \n2) http://pytorch.org/docs/master/torchvision/models.html
", "rawMarkdown": "Pretrained models from:\n1) https://github.com/hujie-frank/SENet \n2) http://pytorch.org/docs/master/torchvision/models.html", "votes": null }, { "id": "248524", "postDate": "11/26/2017 11:24:13", "content": "Pre-trained models from https://github.com/fchollet/keras/tree/master/keras/applications, https://github.com/flyyufelix/cnn_finetune and https://github.com/taehoonlee/tensornets
", "rawMarkdown": "Pre-trained models from https://github.com/fchollet/keras/tree/master/keras/applications, https://github.com/flyyufelix/cnn_finetune and https://github.com/taehoonlee/tensornets", "votes": null }, { "id": "248640", "postDate": "11/26/2017 17:09:52", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
", "rawMarkdown": "https://github.com/Cadene/pretrained-models.pytorch\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models\n\nhttps://github.com/hujie-frank/SENet\n\nhttps://github.com/shicai/SENet-Caffe\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained", "votes": null }, { "id": "250089", "postDate": "11/29/2017 18:53:51", "content": "Is anyone using external data from this thread? Are they even allowed to be used as this seems not to be clear?
\n\nAnd just in case: using pretrained nets from https://github.com/flyyufelix/cnn_finetune and https://keras.io/applications
", "rawMarkdown": "Is anyone using external data from this thread? Are they even allowed to be used as this seems not to be clear?\n\nAnd just in case: using pretrained nets from https://github.com/flyyufelix/cnn_finetune and https://keras.io/applications", "votes": null }, { "id": "251877", "postDate": "12/01/2017 20:43:52", "content": "We are using models from https://github.com/flyyufelix/cnn_finetune, https://keras.io/applications , https://github.com/pytorch/vision
", "rawMarkdown": "We are using models from https://github.com/flyyufelix/cnn_finetune, https://keras.io/applications , https://github.com/pytorch/vision", "votes": null }, { "id": "252142", "postDate": "12/02/2017 10:46:33", "content": "https://keras.io/applications\nhttps://github.com/pytorch/vision
", "rawMarkdown": "https://keras.io/applications\nhttps://github.com/pytorch/vision", "votes": null }, { "id": "252330", "postDate": "12/02/2017 19:01:17", "content": "Pre-trained ResNet models (101, 152) and DenseNet(121, 169, 161) - https://github.com/flyyufelix/cnn_finetune
\n\nAll information contained in the github page.
", "rawMarkdown": "Pre-trained ResNet models (101, 152) and DenseNet(121, 169, 161) - https://github.com/flyyufelix/cnn_finetune\n\nAll information contained in the github page.", "votes": null }, { "id": "253915", "postDate": "12/05/2017 21:18:18", "content": "https://github.com/tensorflow/models/tree/master/research/slim#Pretrained
", "rawMarkdown": "https://github.com/tensorflow/models/tree/master/research/slim#Pretrained", "votes": null }, { "id": "254035", "postDate": "12/06/2017 04:51:03", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
", "rawMarkdown": "https://github.com/Cadene/pretrained-models.pytorch\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\nhttps://github.com/pytorch/vision/tree/master/torchvision/models", "votes": null }, { "id": "254275", "postDate": "12/06/2017 16:50:19", "content": "pre-trained models: https://github.com/pytorch/vision/tree/master/torchvision/models
", "rawMarkdown": "pre-trained models: https://github.com/pytorch/vision/tree/master/torchvision/models", "votes": null }, { "id": "254340", "postDate": "12/06/2017 18:56:34", "content": "Plus all models in this page and in the discussion threads.
", "rawMarkdown": "https://github.com/rbgirshick/py-faster-rcnn\n - https://github.com/Eniac-Xie/faster-rcnn-resnet\n - https://github.com/cypw/DPNs\n - https://github.com/Cadene/pretrained-models.pytorch\n - https://github.com/apache/incubator-mxnet/tree/master/example/image-classification#pre-trained-models\n - https://github.com/miraclewkf/DenseNet\n - https://github.com/hujie-frank/SENet/\n - https://github.com/rksltnl/Deep-Metric-Learning-CVPR16\n\nPlus all models in this page and in the discussion threads.", "votes": null }, { "id": "254522", "postDate": "12/07/2017 05:33:56", "content": "https://keras.io/applications/ \nhttps://github.com/flyyufelix/cnn_finetune\nhttps://github.com/titu1994/Inception-v4\nhttps://github.com/flyyufelix/DenseNet-Keras\nhttps://github.com/argman/EAST\nhttps://github.com/bgshih/crnn
", "rawMarkdown": "https://keras.io/applications/ \nhttps://github.com/flyyufelix/cnn_finetune\nhttps://github.com/titu1994/Inception-v4\nhttps://github.com/flyyufelix/DenseNet-Keras\nhttps://github.com/argman/EAST\nhttps://github.com/bgshih/crnn", "votes": null }, { "id": "254700", "postDate": "12/07/2017 12:53:03", "content": "", "rawMarkdown": "https://keras.io/applications", "votes": null }, { "id": "254811", "postDate": "12/07/2017 17:10:11", "content": "http://pretrained.ml \nhttps://gist.github.com/flyyufelix/7e2eafb149f72f4d38dd661882c554a6 \nhttps://github.com/aaron-xichen/pytorch-playground \nhttps://github.com/Cadene/pretrained-models.pytorch \nhttps://github.com/endymecy/awesome-deeplearning-resources\nhttps://github.com/fchollet/deep-learning-models \nhttps://github.com/fchollet/keras/blob/master/keras/applications/xception.py \nhttps://github.com/kentsommer/keras-inceptionV4 \nhttps://github.com/myutwo150/keras-inception-resnet-v2 \nhttps://github.com/nutszebra/resnext \nhttps://github.com/openimages/dataset \nhttps://github.com/shicai/SENet-Caffe \nhttps://github.com/taehoonlee/tensornets \nhttps://github.com/tensorflow/models/blob/master/slim/README.md\nhttps://github.com/titu1994/MobileNetworks \nhttps://github.com/Zehaos/MobileNet \nhttps://keras.io/applications/ \nhttps://softwaremill.com/counting-objects-with-faster-rcnn/ \nhttps://github.com/mrharicot/monodepth\nhttps://github.com/raulmur/ORB_SLAM2\nhttps://github.com/iro-cp/FCRN-DepthPrediction
\n\nand all models listed on this page
", "rawMarkdown": "http://pretrained.ml \nhttps://gist.github.com/flyyufelix/7e2eafb149f72f4d38dd661882c554a6 \nhttps://github.com/aaron-xichen/pytorch-playground \nhttps://github.com/Cadene/pretrained-models.pytorch \nhttps://github.com/endymecy/awesome-deeplearning-resources\nhttps://github.com/fchollet/deep-learning-models \nhttps://github.com/fchollet/keras/blob/master/keras/applications/xception.py \nhttps://github.com/kentsommer/keras-inceptionV4 \nhttps://github.com/myutwo150/keras-inception-resnet-v2 \nhttps://github.com/nutszebra/resnext \nhttps://github.com/openimages/dataset \nhttps://github.com/shicai/SENet-Caffe \nhttps://github.com/taehoonlee/tensornets \nhttps://github.com/tensorflow/models/blob/master/slim/README.md\nhttps://github.com/titu1994/MobileNetworks \nhttps://github.com/Zehaos/MobileNet \nhttps://keras.io/applications/ \nhttps://softwaremill.com/counting-objects-with-faster-rcnn/ \nhttps://github.com/mrharicot/monodepth\nhttps://github.com/raulmur/ORB_SLAM2\nhttps://github.com/iro-cp/FCRN-DepthPrediction\n\nand all models listed on this page", "votes": null }, { "id": "254965", "postDate": "12/07/2017 23:53:58", "content": "", "rawMarkdown": "[fastai][1]\n\n\n [1]: https://github.com/fastai/fastai", "votes": null }, { "id": "255041", "postDate": "12/08/2017 04:42:52", "content": "https://github.com/rwightman/pytorch-dpn-pretrained
\n\nNasnet, IncResV2: https://github.com/tensorflow/models/tree/master/research/slim/nets
", "rawMarkdown": "https://github.com/rwightman/pytorch-dpn-pretrained\n\nNasnet, IncResV2: https://github.com/tensorflow/models/tree/master/research/slim/nets", "votes": null } ], "comments": [ { "id": 221668, "author_name": "aloisiodn", "author_url": "", "post_date": "09/16/2017 01:40:08", "content": "Are we allowed to use pre-trained models like thoose avaliable in https://keras.io/applications ?
", "votes": null, "replies": [ { "id": 221723, "author_name": "kailicht", "author_url": "", "post_date": "09/16/2017 09:49:47", "content": "Did you read the post?
\n\n\n", "votes": null, "replies": [] } ] }, { "id": 221713, "author_name": "alekseit", "author_url": "", "post_date": "09/16/2017 09:04:01", "content": "Use of publicly available external data is permitted, provided it does not pertain to Cdiscount. For example, you may use pre-trained networks or natural language tools/libraries.
\n
Torchvision pre-trained models: https://github.com/pytorch/vision
", "votes": null, "replies": [] }, { "id": 222212, "author_name": "joexjmmvhm", "author_url": "", "post_date": "09/18/2017 04:48:38", "content": "list of Pretrained:
\n\nInceptionV3
", "votes": null, "replies": [] }, { "id": 222680, "author_name": "nhargan", "author_url": "", "post_date": "09/19/2017 17:35:48", "content": "Keras application: ResNet50, MobileNet
", "votes": null, "replies": [] }, { "id": 222753, "author_name": "woodywang", "author_url": "", "post_date": "09/19/2017 22:01:24", "content": "Pretrained: InceptionV4 https://github.com/flyyufelix/cnn_finetune
", "votes": null, "replies": [] }, { "id": 222770, "author_name": "radustoicescu", "author_url": "", "post_date": "09/20/2017 01:37:14", "content": "I am not sure why people are so specific when declaring Keras pre-trained models.
\n\nAll from https://keras.io/applications/
", "votes": null, "replies": [] }, { "id": 223983, "author_name": "ankasor", "author_url": "", "post_date": "09/24/2017 15:47:45", "content": "The Models from https://keras.io/applications/
", "votes": null, "replies": [] }, { "id": 224219, "author_name": "yeyedaren", "author_url": "", "post_date": "09/25/2017 14:57:55", "content": "I am wondering if someone will manually labels the test set. It is kind of evil but feasible.
", "votes": null, "replies": [ { "id": 224220, "author_name": "ndahlquist", "author_url": "", "post_date": "09/25/2017 14:59:53", "content": "That's against the rules.
\n\n\"Submissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.\"
", "votes": null, "replies": [] } ] }, { "id": 224665, "author_name": "hauserquaid", "author_url": "", "post_date": "09/27/2017 07:04:53", "content": "Hello,\ncould you please clarify if using corporate data that we have rights to is permitted? So we could specify the source of the data, but we can't share the data.
", "votes": null, "replies": [ { "id": 224710, "author_name": "humananalog", "author_url": "", "post_date": "09/27/2017 12:02:50", "content": "The rules are pretty clear: If your data is not publicly available then you cannot use it for this competition.
", "votes": null, "replies": [] } ] }, { "id": 225080, "author_name": "shivam6294", "author_url": "", "post_date": "09/28/2017 07:35:13", "content": "All models listed on this page: \nhttps://github.com/tensorflow/models/tree/master/research/slim
", "votes": null, "replies": [] }, { "id": 228339, "author_name": "datasec", "author_url": "", "post_date": "10/06/2017 13:21:09", "content": "Pre-trained models from https://keras.io/applications/
", "votes": null, "replies": [] }, { "id": 228512, "author_name": "jandjenter", "author_url": "", "post_date": "10/06/2017 22:09:10", "content": "Pre-trained models from https://keras.io/applications/
", "votes": null, "replies": [] }, { "id": 229832, "author_name": "menegaz", "author_url": "", "post_date": "10/10/2017 15:52:10", "content": "also, Pre-trained models from https://keras.io/applications/
", "votes": null, "replies": [] }, { "id": 230018, "author_name": "jpmiller", "author_url": "", "post_date": "10/11/2017 03:39:31", "content": "All models listed on this page.
", "votes": null, "replies": [] }, { "id": 233555, "author_name": "hengck23", "author_url": "", "post_date": "10/20/2017 14:26:58", "content": "is crawling google web images allowed?
\n\ne.g. if i find there are rare classes like 'xxx' and i use google search to download such images ( filter off images from Cdiscount's website) can they be used?
\n\ni can made such images public to all participants.
", "votes": null, "replies": [] }, { "id": 233562, "author_name": "hengck23", "author_url": "", "post_date": "10/20/2017 14:34:40", "content": "Amazon dataset:
\n\nhttp://jmcauley.ucsd.edu/data/amazon/
\n\nhttp://cseweb.ucsd.edu/~jmcauley/pdfs/sigir15.pdf
\n\n{\n \"asin\": \"0000031852\",\n \"title\": \"Girls Ballet Tutu Zebra Hot Pink\",\n \"price\": 3.17,\n \"imUrl\": \"http://ecx.images-amazon.com/images/I/51fAmVkTbyL._SY300_.jpg\",\n ...\n}\n
@Heng CherKeng, there is no license information for the Amazon dataset.
", "votes": null, "replies": [] }, { "id": 233590, "author_name": "jandjenter", "author_url": "", "post_date": "10/20/2017 16:08:51", "content": "This data can be almost cheating! Books & CD are most difficult ones in this competition, but it is quite normalized in shape. So you can just identify them in cdiscount data and look up those in amazon data. \nBTW, to download the data, you need to contact the author. I'm not sure whether this can be considered as public data.
", "votes": null, "replies": [] }, { "id": 233854, "author_name": "hengck23", "author_url": "", "post_date": "10/21/2017 15:07:27", "content": "i am writing e-mail to the organizer and ask about license information.
\n\nWhether the data can be used or not, i have to wait for response from the kaggle administrator of this thread.
", "votes": null, "replies": [] } ] }, { "id": 233855, "author_name": "hengck23", "author_url": "", "post_date": "10/21/2017 15:08:28", "content": "https://archive.org/details/audio-covers
\n\none million CD cover data
\n\n
@inversion
\n\nI would like to confirm if my posted \"one million CD cover data\" and \"Amazon dataset\" can be used or not. Thanks!
", "votes": null, "replies": [] } ] }, { "id": 238264, "author_name": "hengck23", "author_url": "", "post_date": "11/01/2017 01:54:58", "content": "i wonder if this can be used?
\n\nhttp://vision.is.tohoku.ac.jp/~kyamagu/research/etsy-dataset/
", "votes": null, "replies": [] }, { "id": 241462, "author_name": "inoueian", "author_url": "", "post_date": "11/08/2017 21:52:22", "content": "Pre-trained models from Keras: https://keras.io/applications/
", "votes": null, "replies": [] }, { "id": 243034, "author_name": "eachshadow", "author_url": "", "post_date": "11/13/2017 07:39:13", "content": "Pre-trained models from https://keras.io/applications/ and https://github.com/flyyufelix/DenseNet-Keras + any other pretrained models listed in this thread
", "votes": null, "replies": [] }, { "id": 243372, "author_name": "hengck23", "author_url": "", "post_date": "11/13/2017 22:34:39", "content": "pretrained model l used:
\n\nhttps://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\n\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
\n\nhttps://github.com/mapillary/inplace_abn
", "votes": null, "replies": [] }, { "id": 246575, "author_name": "radek1", "author_url": "", "post_date": "11/21/2017 10:58:55", "content": "pretrained models supported by the fastai library
", "votes": null, "replies": [] }, { "id": 246645, "author_name": "tereka", "author_url": "", "post_date": "11/21/2017 14:05:57", "content": "I use these models\nhttps://github.com/clcarwin/convert_torch_to_pytorch
", "votes": null, "replies": [] }, { "id": 247289, "author_name": "bestfitting", "author_url": "", "post_date": "11/22/2017 18:21:59", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
\n\nhttps://github.com/tianzhi0549/CTPN
\n\nhttps://github.com/AKSHAYUBHAT/CTPN8
\n\nhttps://github.com/meijieru/crnn.pytorch
\n\nhttps://github.com/Bartzi/stn-ocr
\n\nhttps://code.google.com/archive/p/word2vec/
\n\nhttps://nlp.stanford.edu/projects/glove/
\n\nhttps://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md
", "votes": null, "replies": [] }, { "id": 247466, "author_name": "ajmooch", "author_url": "", "post_date": "11/23/2017 05:20:40", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\n\n\nhttps://keras.io/applications/
", "votes": null, "replies": [] }, { "id": 247528, "author_name": "szywind", "author_url": "", "post_date": "11/23/2017 09:42:44", "content": "list of pretrained models:\nhttps://keras.io/applications/\nhttps://github.com/shicai/SENet-Caffe\nhttps://gist.github.com/flyyufelix
", "votes": null, "replies": [] }, { "id": 247815, "author_name": "pkdn14", "author_url": "", "post_date": "11/24/2017 00:18:00", "content": "https://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/Cadene/pretrained-models.pytorch
", "votes": null, "replies": [] }, { "id": 248129, "author_name": "mmotoki", "author_url": "", "post_date": "11/24/2017 22:53:17", "content": "https://github.com/pytorch/vision\nhttps://keras.io/applications/\nhttps://github.com/flyyufelix/DenseNet-Keras
", "votes": null, "replies": [] }, { "id": 248165, "author_name": "wowfattie", "author_url": "", "post_date": "11/25/2017 05:14:40", "content": "pretrained InceptionResNetV2 from https://keras.io/applications/\npretrained Inception-V4 ResNet-101 ResNet-152 from https://github.com/flyyufelix/cnn_finetune
", "votes": null, "replies": [] }, { "id": 248347, "author_name": "steelrose", "author_url": "", "post_date": "11/25/2017 19:27:42", "content": "I will use any of the models listed here atm (+ whenever someone lists something new I might still possibly that as well)\nI will use any data listed here
", "votes": null, "replies": [] }, { "id": 248477, "author_name": "mwbyeon", "author_url": "", "post_date": "11/26/2017 08:00:12", "content": "Pre-trained Dual Path Network\nhttps://github.com/cypw/DPNs
Pre-trained DenseNet\nhttps://github.com/miraclewkf/DenseNet
Pre-trained ResNet, ResNext\nhttps://github.com/apache/incubator-mxnet/tree/master/example/image-classification#pre-trained-models
Pretrained models from:\n1) https://github.com/hujie-frank/SENet \n2) http://pytorch.org/docs/master/torchvision/models.html
", "votes": null, "replies": [] }, { "id": 248524, "author_name": "creafz", "author_url": "", "post_date": "11/26/2017 11:24:13", "content": "Pre-trained models from https://github.com/fchollet/keras/tree/master/keras/applications, https://github.com/flyyufelix/cnn_finetune and https://github.com/taehoonlee/tensornets
", "votes": null, "replies": [] }, { "id": 248640, "author_name": "lukeeee", "author_url": "", "post_date": "11/26/2017 17:09:52", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
\n\nhttps://github.com/hujie-frank/SENet
\n\nhttps://github.com/shicai/SENet-Caffe
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim
\n\nhttps://github.com/rwightman/pytorch-dpn-pretrained
", "votes": null, "replies": [] }, { "id": 250089, "author_name": "voltaire", "author_url": "", "post_date": "11/29/2017 18:53:51", "content": "Is anyone using external data from this thread? Are they even allowed to be used as this seems not to be clear?
\n\nAnd just in case: using pretrained nets from https://github.com/flyyufelix/cnn_finetune and https://keras.io/applications
", "votes": null, "replies": [] }, { "id": 251877, "author_name": "rteja1113", "author_url": "", "post_date": "12/01/2017 20:43:52", "content": "We are using models from https://github.com/flyyufelix/cnn_finetune, https://keras.io/applications , https://github.com/pytorch/vision
", "votes": null, "replies": [] }, { "id": 252142, "author_name": "johnfarrell", "author_url": "", "post_date": "12/02/2017 10:46:33", "content": "https://keras.io/applications\nhttps://github.com/pytorch/vision
", "votes": null, "replies": [] }, { "id": 252330, "author_name": "anmoljoshi", "author_url": "", "post_date": "12/02/2017 19:01:17", "content": "Pre-trained ResNet models (101, 152) and DenseNet(121, 169, 161) - https://github.com/flyyufelix/cnn_finetune
\n\nAll information contained in the github page.
", "votes": null, "replies": [] }, { "id": 253915, "author_name": "pavelboyko", "author_url": "", "post_date": "12/05/2017 21:18:18", "content": "https://github.com/tensorflow/models/tree/master/research/slim#Pretrained
", "votes": null, "replies": [] }, { "id": 254035, "author_name": "owruby", "author_url": "", "post_date": "12/06/2017 04:51:03", "content": "https://github.com/Cadene/pretrained-models.pytorch
\n\nhttps://github.com/tensorflow/models/tree/master/research/slim\nhttps://github.com/pytorch/vision/tree/master/torchvision/models
", "votes": null, "replies": [] }, { "id": 254275, "author_name": "xinbangzhang", "author_url": "", "post_date": "12/06/2017 16:50:19", "content": "pre-trained models: https://github.com/pytorch/vision/tree/master/torchvision/models
", "votes": null, "replies": [] }, { "id": 254340, "author_name": "ymarzougui", "author_url": "", "post_date": "12/06/2017 18:56:34", "content": "Plus all models in this page and in the discussion threads.
", "votes": null, "replies": [] }, { "id": 254522, "author_name": "lamdang", "author_url": "", "post_date": "12/07/2017 05:33:56", "content": "https://keras.io/applications/ \nhttps://github.com/flyyufelix/cnn_finetune\nhttps://github.com/titu1994/Inception-v4\nhttps://github.com/flyyufelix/DenseNet-Keras\nhttps://github.com/argman/EAST\nhttps://github.com/bgshih/crnn
", "votes": null, "replies": [] }, { "id": 254700, "author_name": "firenero", "author_url": "", "post_date": "12/07/2017 12:53:03", "content": "", "votes": null, "replies": [] }, { "id": 254811, "author_name": "hiromichinomata", "author_url": "", "post_date": "12/07/2017 17:10:11", "content": "http://pretrained.ml \nhttps://gist.github.com/flyyufelix/7e2eafb149f72f4d38dd661882c554a6 \nhttps://github.com/aaron-xichen/pytorch-playground \nhttps://github.com/Cadene/pretrained-models.pytorch \nhttps://github.com/endymecy/awesome-deeplearning-resources\nhttps://github.com/fchollet/deep-learning-models \nhttps://github.com/fchollet/keras/blob/master/keras/applications/xception.py \nhttps://github.com/kentsommer/keras-inceptionV4 \nhttps://github.com/myutwo150/keras-inception-resnet-v2 \nhttps://github.com/nutszebra/resnext \nhttps://github.com/openimages/dataset \nhttps://github.com/shicai/SENet-Caffe \nhttps://github.com/taehoonlee/tensornets \nhttps://github.com/tensorflow/models/blob/master/slim/README.md\nhttps://github.com/titu1994/MobileNetworks \nhttps://github.com/Zehaos/MobileNet \nhttps://keras.io/applications/ \nhttps://softwaremill.com/counting-objects-with-faster-rcnn/ \nhttps://github.com/mrharicot/monodepth\nhttps://github.com/raulmur/ORB_SLAM2\nhttps://github.com/iro-cp/FCRN-DepthPrediction
\n\nand all models listed on this page
", "votes": null, "replies": [] }, { "id": 254965, "author_name": "roebius", "author_url": "", "post_date": "12/07/2017 23:53:58", "content": "", "votes": null, "replies": [] }, { "id": 255041, "author_name": "rwightman", "author_url": "", "post_date": "12/08/2017 04:42:52", "content": "https://github.com/rwightman/pytorch-dpn-pretrained
\n\nNasnet, IncResV2: https://github.com/tensorflow/models/tree/master/research/slim/nets
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "221288": "Per the competition rules, please post external data in this thread.\n\n