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Unable To Construct A Datum From The Specified Input

I suspect that this is a stupid question, but I guess I don't understand what is meant by shuffling in this context. I increased the image dimensions and retrained the model (using the CPU this time). Let us know what happens. So I'm still unable to get a prediction from the basic Imagenet with my own data. http://qaisoftware.com/unable-to/unable-to-add-forward-map-from-timed-out-dhcpd.html

May 22, 2014 shelhamer closed this May 22, 2014 StevenLOL referenced this issue Dec 22, 2014 Closed How to deploy or run test case or so called predict? #1617 wkiri commented This was done because for cudaMalloc was failing for images of 256x256 with my Macbook Pro's GT 650M with 1Gb. I'm not sure how the training succeeds given that when running create_imagenet.sh I'm supplying way less than 1000 classes in my train.txt and val.txt? Cheers J — Reply to this email directly or view it on GitHubhttps://github.com/BVLC/caffe/issues/261#issuecomment-39423717 . https://community.oracle.com/thread/58216?start=0

Contributor sguada commented Mar 31, 2014 Could you share the prototxt file that you are using? We recommend upgrading to the latest Safari, Google Chrome, or Firefox. Toolbox for IT My Home Topics People Companies Jobs White Paper Library Collaboration Tools Discussion Groups Blogs Follow Toolbox.com Toolbox for IT on Twitter Toolbox.com on Twitter Toolbox.com on Facebook Topics The weird thing about the 9216 is that it changes depending on the initial image dimensions declared in the prototxt: input: "data" input_dim: 10 input_dim: 3 input_dim: 256 input_dim: 256 F0330

So I'm still unable to get a prediction from the basic Imagenet with my own data. for update Parameters - rec_no, int 2) Collaboration Rule Java Classpath: client\Thirdparty\Oracle\classes12.jar Java Imports: ResultSetAgent, Blob Sample Code: 65 | public boolean executeBusinessRules() throws Exception 66 | { 67 | boolean Any ideas welcome! :-) Thanks John On 28 Mar 2014, at 23:18, longjon [email protected] wrote: You may also want to check that your train.prototxt is compatible with examples/imagenet/imagenet_deploy.prototxt; the error suggests Note: we also noticed that if we use oracle.sql.TIMESTAMP instead of java.sql.Timestamp, it will work.

Sergio 2014-03-31 14:53 GMT-07:00 John Swan [email protected]: So try with 227, and see if it works. Sign in to comment Contact GitHub API Training Shop Blog About © 2017 GitHub, Inc. I'm not at all sure how to do that. Submit feedback to IBM Support 1-800-IBM-7378 (USA) Directory of worldwide contacts Contact Privacy Terms of use Accessibility ű֮ android MAC DLL Դ aspԴ phpԴ asp.netԴ jspԴ ҳ༭ ݿ

You're now being signed in. I hope to update the python wrapper documentation and examples shortly. Contributor jeffdonahue commented Mar 31, 2014 I think that error would be raised if you used a pretrained net and tried to deploy with a prototxt where fc7 takes inputs from I deleted all the bias and weight initialisers, but unfortunately it made no difference.

  • Use java.io.File instead.
  • Automated exception search integrated into your IDE Test Samebug Integration for IntelliJ IDEA 0 mark [jira] Updated: (DBCP-279) unset XADatasource's property in BasicManagedDataSource class mail-archive.com | 2 years ago java.sql.SQLException: 指定了无效的
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  • Then detector.py gave me a prediction!
  • However, if I try to substitute my own image mean file (created by make_imagenet_mean.sh) then detector.py crashes because it is expecting a Numpy array, while make_imagenet_mean.sh produces a binaryproto.
  • It sounds like it could be very useful.
  • MODEL_FILE = 'deploy.prototxt' PRETRAINED = 'train_iter_10000' IMAGE_FILE = 'image.jpg' net = imagenet.ImageNetClassifier( MODEL_FILE, PRETRAINED) net.caffenet.set_phase_test() net.caffenet.set_mode_cpu() # net.caffenet.set_mode_gpu() prediction = net.predict(IMAGE_FILE) print '\nprediction:' print prediction print '\n\nprediction shape:', prediction.shape pyplot.plot(prediction) However,
  • Any thoughts or suggestions? - Don Join this group 3Replies Best Answer 0 Mark this reply as the best answer?(Choose carefully, this can't be changed) Yes | No Saving...
  • How do I make sure that the data is shuffled?
  • That's my original problem.

It just shows passing an Object. The following is an example to illustrate how to insert a BLOB, but it's the exact same process for CLOB (simply replace "BLOB" for "CLOB"): 1) ETDS - Using the DB As for "shuffling files," my guess is you're referring to https://github.com/BVLC/caffe/blob/814a32a/tools/convert_imageset.cpp#L12, which I believe is an out-of-date comment that I'll remove shortly. Skip navigationOracle Community DirectoryOracle Community FAQGo Directly To Oracle Technology Network CommunityMy Oracle Support CommunityOPN Cloud ConnectionOracle Employee CommunityOracle User Group CommunityTopliners CommunityJava CommunityOTN Speaker BureauLog inRegisterSearchSearchCancelError: You don't have JavaScript

com [Download message RAW] Hi, I am using JDBCPlus (http://www.dankomannhaupt.de/projects/index.html ) as a jdbc appender for my application. http://qaisoftware.com/unable-to/unable-to-open-the-specified-video-output-device.html Very frustrating. I also tried detector.py but got exactly the same error. If you want to use different input sizes you have to remove the fully connected layers.

But as soon as I do this, my application fails to log in database giving stack trace as log4j:ERROR JDBCAppender::flush_buffer(), : java.sql.SQLException: Internal Error: Unable to construct a Datum from the Very frustrating. F0330 04:07:08.374914 2102817152 pycaffe.cpp:118] Check failed: dims[2] == blob->height() (227 vs. 140) The pictures are 256x256, but the original imagenet prototxt declares them as 227x227 and crops them to 140x140. navigate here I also noticed that detector.py is defaulting to the imagenet mean file ilsvrc_2012_mean.npy when I don't specify one: parser.add_argument( "--images_mean_file", default=os.path.join( os.path.dirname(file), '../imagenet/ilsvrc_2012_mean.npy'), help="Data set image mean (numpy array).") I'm sure

Not sure what to do now. At least in any way that would leave a functioning system. I'm not sure if e*Gate requires this two-step process.

to Dimension mismatch training with my own model / why does training give the same prediction for all inputs?

Automated exception search integrated into your IDE Test Samebug Integration for IntelliJ IDEA Root Cause Analysis java.sql.SQLException Internal Error: Unable to construct a Datum from the specified input at oracle.jdbc.dbaccess.DBError.throwSqlException() oracle.jdbc.dbaccess The error you are getting indicates that your trained parameters aren't the same size as needed by deploy.prototxt at the fc6 layer. com> Date: 2008-09-04 9:48:18 Message-ID: 349b2c0f0809040236p3b2887b3tbb54f6d32dd9199d () mail ! Url : http://www.scriptcode.net/thread-19467-1-1.html Title : Java.sql.SQLException: Unable to construct a internal error: Datum from the spec Favorite0 Reply Only Author Prop Report Return to List High mode B Color Image Link

Did you train with differently sized inputs (perhaps 140x140)? Terms Privacy Security Status Help You can't perform that action at this time. Anyway, to see what happens, I naively reduced fc8's num_output from its original 1000 (to match my label count) in each of the prototxts (train, val, deploy), then retrained the model his comment is here I also tried detector.py but got exactly the same error.

Exactly the same results as before. On Mar 30, 2014, at 11:47 PM, John Swan [email protected] wrote: Hi, Thanks for the input. Regards, Vaibhav [Attachment #3 (text/html)]

Hi,
I am using JDBCPlus (http://www.dankomannhaupt.de/projects/index.html ) as a
jdbc \ appender for my application. Making the same prediction for every input can happen when training fails for data that isn't shuffled (making the gradient variance too high) or data that isn't class balanced.

More Enterprise Architecture and EAI Groups Your account is ready. johnswan commented Apr 2, 2014 The error you are getting indicates that your trained parameters aren't the same size as needed by deploy.prototxt at the fc6 layer. You can not post a blank message. So, I did shuffle the data, but still got identical predictions.

Cheers J Member shelhamer commented Apr 3, 2014 Making the same prediction for every input can happen when training fails for data that isn't shuffled (making the gradient variance too high) If you are training with a leveldb, you set the last arg (the shuffle flag) to 1 to have the input shuffled for you. I had done that (set it to 1). I reran with the original 1000 classes and again - the predictions for each image are all the same.

FileInputStream doesn't implement all methods of java.io.InputStream. Is this a bug in the Driver? Contributor longjon commented Mar 31, 2014 The code in caffe.imagenet assumes that your net takes 227x227 input crops (in fact, it's really only intended for use with the provided imagenet net). Thanks John — Reply to this email directly or view it on GitHubhttps://github.com/BVLC/caffe/issues/261#issuecomment-39041101 .

johnswan commented Mar 30, 2014 Thanks for the suggestion. Re: the ImageNet mean, it is actually quite effective if you are still classifying run-of-the-mill images from the internet, and certainly far better than not doing mean subtraction. I noticed that this question has also been asked today in #290 shelhamer changed the title from Pycaffe bug?