SVM TRAINING FOR LICENSE PLATE DETECTION

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I am currently working on License Plate recognition using custom HoG and SVM. I have the features of my image data set extracted and saved in an xml file. Here is the code:

train_list = []
response_list = []

hog = cv2.HOGDescriptor()

for i in range(2,7):
    img = cv2.imread(str(i) + "_.png")
    h = hog.compute(img)
    train_list.append(h)
    response_list.append(i)

model = cv2.SVM()
x = model.train(np.array(train_list), np.array(response_list))
model.save('trained.xml')

However, when I use SVM predict to classify if a certain image is positive or negative, I get the following error:

Input sample must have 32fC1 type in function cvPreparePredictData

Here is my code for using svm predict method:

img = cv2.imread('2.jpg',cv2.IMREAD_COLOR)
img2 = img.ravel() #conversion to a 1D matrix

svm = cv2.SVM()
svm.load('trained.xml')

svm.predict(img2)

Kindly help me resolve the above error.