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OpenCV 2.3 RC Python SVM: TypeError: <unknown> is not a numpy array

asked 2011-06-26 06:02:23 -0500

Pi Robot gravatar image

updated 2014-01-28 17:09:56 -0500

ngrennan gravatar image

Hello,

I am trying to use the new cv2 SVM (Support Vector Machine) Python binding in OpenCV 2.3 RC. I compiled OpenCV from source under Ubuntu 10.04 and as soon as I execute this function:

svm = cv2.SVM(training_data, responses)

I get the error:

TypeError: <unknown> is not a numpy array

Does anyone know what I am doing wrong or how to fix this?

Here is the full function I am using to train the SVM. The variables self.positive_samples and self.negative_samples are Python lists of SURF feature vectors (64 elements long). The variable self.classes is a Python list of 1's and -1's indicating the class a sample belongs to.

def init_classifier(self):

    n_positive_samples = len(self.positive_samples)
    n_negative_samples = len(self.negative_samples)

    n_samples = n_positive_samples + n_negative_samples

    training_data = cv.CreateMat(n_samples, 64, cv.CV_32FC1)
    responses = cv.CreateMat(n_samples, 1, cv.CV_32FC1)

    for i in range(n_positive_samples):
        cv.Set2D(responses, i, 0, self.classes[i])
        for j in range(64):        
            cv.Set2D(training_data, i, j, self.positive_samples[i][j])

    for i in range(n_positive_samples, n_samples):
        i_negative = i - n_positive_samples
        cv.Set2D(responses, i, 0, self.classes[i_negative])
        for j in range(64):        
            cv.Set2D(training_data, i, j, self.negative_samples[i_negative][j])

    svm = cv2.SVM(training_data, responses)
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answered 2011-06-26 11:57:25 -0500

Pi Robot gravatar image

updated 2011-06-26 11:57:46 -0500

OK, it only took me about 5 hours of trial and error to finally figure this out. Turns out the SVM class requires the training data to be of type numpy.float32. Since my training data was in regular Python arrays, I had to convert them like this:

training_data = np.array(python_training_data, dtype=np.float32)
responses = np.array(python_responses, dtype=np.float32)

Now all is well.

--patrick

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Asked: 2011-06-26 06:02:23 -0500

Seen: 2,907 times

Last updated: Jun 26 '11