svm_train.py 文件源码

def hog_single(img):
    samples=[]
    gx = cv2.Sobel(img, cv2.CV_32F, 1, 0)
    gy = cv2.Sobel(img, cv2.CV_32F, 0, 1)
    mag, ang = cv2.cartToPolar(gx, gy)
    bin_n = 16
    bin = np.int32(bin_n*ang/(2*np.pi))
    bin_cells = bin[:100,:100], bin[100:,:100], bin[:100,100:], bin[100:,100:]
    mag_cells = mag[:100,:100], mag[100:,:100], mag[:100,100:], mag[100:,100:]
    hists = [np.bincount(b.ravel(), m.ravel(), bin_n) for b, m in zip(bin_cells, mag_cells)]
    hist = np.hstack(hists)

    # transform to Hellinger kernel
    eps = 1e-7
    hist /= hist.sum() + eps
    hist = np.sqrt(hist)
    hist /= norm(hist) + eps

    samples.append(hist)
    return np.float32(samples)

#using Compute_hog too much time !