1
我想了解MXNet的手寫漢字識別在Python here如何在MXNet
它創建的訓練數據和標籤數據如下所示的代碼確定標籤的指標：
def read_data(label_url, image_url):
with gzip.open(download_data(label_url)) as flbl:
magic, num = struct.unpack(">II", flbl.read(8))
label = np.fromstring(flbl.read(), dtype=np.int8)
with gzip.open(download_data(image_url), 'rb') as fimg:
magic, num, rows, cols = struct.unpack(">IIII", fimg.read(16))
image = np.fromstring(fimg.read(), dtype=np.uint8).reshape(len(label), rows, cols)
return (label, image)
然後，數字用下面的代碼預測：
prob = model.predict(val_img[0:1].astype(np.float32)/255)[0]
assert max(prob) > 0.99, "Low prediction accuracy."
print 'Classified as %d with probability %f' % (prob.argmax(), max(prob))
的輸出 - 被分類爲7的概率爲0.999391。 我的問題是MXNet如何能夠確定由argmax函數返回的索引對應於標籤-7