Loading Inception-v1 model with weights trained using Caffe

[goutham....@gmail.com]

Hi everyone,

I am trying to load the Weights of the Caffe model to the Incepetion model, but was facing a few errors, one of them is below :

py4j.Py4JException: Method loadCaffeModel([class com.intel.analytics.bigdl.nn.Sequential, class java.lang.String]) does not exist

In addition to the above error, I also have the below questions :

1. The link that I am referring for caffe model's weights is :  https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet. Is this right one ? if not please suggest the correct one.

2. I am referring to the documentation at : https://bigdl-project.github.io/0.2.0/#ProgrammingGuide/caffe-support/ ; to load caffe model's weights. But facing an error when using the last parameter 'match_all=True' ( I have tried with matchAll = True as well ). Can you please confirm if the documentation is right ?

I am using BigDL - 0.2.0 and python. Please find the 'InceptionV1 model' notebook that I am using and detailed error logs as attachment.

regards,

goutham.

[Jennie Wang]

There are two methods to load caffe model in python.

If you already create BigDL model, you need to call Model. load_caffe(model, defPath, modelPath, match_all=True, bigdl_type="float")

If you don't define BigDL model, you need to call Model.load_caffe_model(defPath, modelPath, bigdl_type="float").

So in your case, you need to use Model.load_caffe interface. The documentation is not correct in this case, created issue: https://github.com/intel-analytics/BigDL/issues/1552.

Thanks,

Jennie

[goutham....@gmail.com]

Thank you jenny for you reply. That worked.

Now, after loading the weights I am trying to predict the class of an image using this model. When I print the prediction output it does not show any class or index but this : "MapPartitionsRDD[22] at mapPartitions at PythonMLLibAPI.scala:1335 "

The code that I am using to preprocess the image before calling mode.predict_class is :

      input_img = 'cat.jpg'

      img = cv2.imread(input_img) # to read the data into numpy array 

      img_data_rdd = sc.parallelize(img)

      predict_result = model.predict_class(img_data_rdd)

Can you please let me know where I am doing wrong.

regards,

goutham  

[Li, Zhichao]

You need to  predict_result.collect() as the returning result is a RDD.

 

Thanks,

Zhichao

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[goutham....@gmail.com]

Thanks for the quick reply. when I ran "predict_result.collect() " line i got  'Py4JJavaError' error.  Complete trace back of this error message can be found as attachment.

Can you please take a look at this ?

regards,

goutham.

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[Jennie Wang]

Also before you call model.predict_class, you need to preprocess the image and change to RDD[Sample]. You can reference this example (https://github.com/jenniew/BigDL/blob/imagenet/pyspark/dl/models/inception/inception.py)to preprocess image, and then call prediction.

Thanks,

Jennie

On Tuesday, September 12, 2017 at 11:05:06 PM UTC-7, Zhichao Li wrote:

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[goutham....@gmail.com]

Hi Jenny,

For Transforming the pre-processed image to RDD[sample], I am trying to use  ' Sample.from_ndarray(image, label)'.

But since I am just trying to predict only a single unknown image, I am confused on what I have to pass for 'label' parameter.

Can you help me with this ?

I am pre-processing the image using below code:

input_img = 'cat.jpg'

img = cv2.imread(input_img) # to read the data into numpy array 

img_rows = 224

img_cols = 224

transform_input = Transformer([Crop(img_rows, img_cols, "center"), Flip(0.5), ChannelNormalizer(0.485, 0.456, 0.406, 0.229, 0.224, 0.225),

                                                TransposeToTensor(False)])

img_tranx = transform_input(img)

img_to_model = Sample.from_ndarray(img_tranx, ? )

regards,

goutham.

I tried to prep_process the input image using transformer function. 

[Jennie Wang]

You can set label as -1 or np.array(-1).

Thanks,

Jennie

[goutham....@gmail.com]

I tried that, but when I facing java error when trying to predict . I ran "model.predict_class(img_to_model)"  line for class prediction.

The error is :

Py4JError: An error occurred while calling o36.modelPredictClass. Trace:
py4j.Py4JException: Method modelPredictClass([class com.intel.analytics.bigdl.nn.Sequential, class com.intel.analytics.bigdl.python.api.Sample]) does not exist.

Please find the complete error log as attachment. It says' model predict class' is not present  in library. am I missing something ?

code I used :

input_img = 'cat.jpg'

img = cv2.imread(input_img) # to read the data into numpy array 

img_rows = 224

img_cols = 224

transform_input = Transformer([Crop(img_rows, img_cols, "center"), Flip(0.5), ChannelNormalizer(0.485, 0.456, 0.406, 0.229, 0.224, 0.225),

                                                TransposeToTensor(False)])

img_tranx = transform_input(img)

label = np.array(-1)

img_to_model = Sample.from_ndarray(img_tranx, label)

predict_result = model.predict_class(img_to_model)  # to predict

regards

goutham.

[Jennie Wang]

The img_to_model is only one Sample, please change to RDD[Sample] (i.e. sc.parallelize([img_to_model])) and then call model.predict_class

Thanks,

Jennie

[Jason Dai]

You may also refer to the BigDL tutorials (e.g., https://github.com/intel-analytics/BigDL-Tutorials/blob/master/notebooks/neural_networks/cnn.ipynb) for examples on using BigDL.

Thanks,

-Jason

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[goutham....@gmail.com]

Thanks a lot Jennie, That worked. 

regards,

goutham.

[Dave Nielsen]

Nice work Goutham. Thank you Jennie!!

Dave

Dave Nielsen
Technical Program Manager

BigDL - Deep Learning for Spark
Big Data Technologies, DPD, Intel Software

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