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 | 1 | initial version |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
| | 2 | No.2 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
| | 3 | No.3 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
| | 4 | No.4 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network inputC:\fakepath\tulip.jpg
| | 5 | No.5 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error:
http://193.87.95.129/inf_predn/final_graph.pb
| | 6 | No.6 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error:
error: input image C:\fakepath\tulip.jpg
optimized and trasformed model http://193.87.95.129/inf_predn/final_graph.pb
c++ example http://193.87.95.129/inf_predn/opencv.cpp
| | 7 | No.7 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error: input image C:\fakepath\tulip.jpg
optimized and trasformed model http://193.87.95.129/inf_predn/final_graph.pb
c++ example http://193.87.95.129/inf_predn/opencv.cpp
used tensorflow 1.7 gpu gtx 1050 for retrain
| | 8 | No.8 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error: input image C:\fakepath\tulip.jpg
optimized and trasformed model http://193.87.95.129/inf_predn/final_graph.pb
c++ example http://193.87.95.129/inf_predn/opencv.cpp
retrained model output_graph.ph is OK but optimized and transformed graph final_graph not working good in C++ opencv
used tensorflow 1.7 gpu gtx 1050 for retrain
| | 9 | No.9 Revision |
conversion working but wrong output :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error: input image C:\fakepath\tulip.jpg
optimized and trasformed model http://193.87.95.129/inf_predn/final_graph.pb
c++ example http://193.87.95.129/inf_predn/opencv.cpp
retrained model output_graph.ph output_graph.pb is OK but optimized and transformed graph final_graph not working good in C++ opencvpython_label tested
retrained model final_graph.pb is OK python_label tested
some problem to reading model by C++?
used tensorflow 1.7 gpu gtx 1050 for retrain
| | 10 | No.10 Revision |
conversion working but wrong output from C++ opencv :-(
result from opencv c++ read
daisy 9.26857e-06 dandelion 0.000130691 roses 0.99399 sun0.00144483 tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error: input image C:\fakepath\tulip.jpg
optimized and trasformed model http://193.87.95.129/inf_predn/final_graph.pb
c++ example http://193.87.95.129/inf_predn/opencv.cpp
retrained -retrained model output_graph.pb is OK python_label tested
retrained -retrained model final_graph.pb is OK python_label tested
some problem to reading model by C++?
used tensorflow 1.7 gpu gtx 1050 for retrain
| | 11 | No.11 Revision |
conversion working but wrong cca lower accurency 20% down output from C++ opencv :-(
result from opencv c++ read
daisy 9.26857e-06
dandelion 0.000130691
Probability: 75.1135% daisy6.75558e-06,dan0.000468269,ros0.2483,sun9.00434e-05,roses 0.99399tul0.751135
sun0.00144483
tul0.00442559
used function -> Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false);
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error: input image C:\fakepath\tulip.jpg
optimized and trasformed model http://193.87.95.129/inf_predn/final_graph.pb
c++ example http://193.87.95.129/inf_predn/opencv.cpp
-retrained model output_graph.pb is OK python_label tested
-retrained model final_graph.pb is OK python_label tested
some problem to reading model by C++?C++ with same precission?
used tensorflow 1.7 gpu gtx 1050 for retrain
| | 12 | No.12 Revision |
conversion working but wrong cca lower accurency 20% down output from C++ opencv :-(
result from opencv c++ read
Probability: 75.1135% daisy6.75558e-06,dan0.000468269,ros0.2483,sun9.00434e-05,tul0.751135
result from standard label function from tensorflow for tulip image is OK tulips 0.9127952 roses 0.0797129 sunflowers 0.0060887286 daisy 0.0010076686 dandelion 0.00039551986
maybee is something wrong with read blob I use modified googlenet c++ source, I only changed resolution from 224,244 to 299, 299.
Mat inputBlob = blobFromImage(img, 1.0f, Size(299, 299), Scalar(), true, false); //Convert Mat to batch
inputBlob -= 117.0;
//! [Set input blob]
net.setInput(inputBlob, inBlobName); //set the network input
files used if you want to reproduce, this error: input image C:\fakepath\tulip.jpg
optimized and trasformed model http://193.87.95.129/inf_predn/final_graph.pb
c++ example http://193.87.95.129/inf_predn/opencv.cpp
-retrained model output_graph.pb is OK python_label tested -retrained model final_graph.pb is OK python_label tested some problem to reading model by C++ with same precission?
used tensorflow 1.7 gpu gtx 1050 for retrain
