/ image / Tensor Tensor（“ activation_5 / Softmax：0”，shape =（?, 4），dtype = float32）处的ValueError不是此图的元素

Question

我正在构建图像处理分类器，并且此代码是用于预测整个代码正在运行的图像的图像类的API，但此行除外（pred =
model.predict_classes（test_image）），此API在Django框架中进行并且正在使用python 2.7

如果我像往常一样运行此代码（无需制作API），这一点就可以完美运行

def classify_image(request):
if request.method == 'POST' and request.FILES['test_image']:

    fs = FileSystemStorage()
    fs.save(request.FILES['test_image'].name, request.FILES['test_image'])


    test_image = cv2.imread('media/'+request.FILES['test_image'].name)

    if test_image is not None:
        test_image = cv2.resize(test_image, (128, 128))
        test_image = np.array(test_image)
        test_image = test_image.astype('float32')
        test_image /= 255
        print(test_image.shape)
    else:
        print('image didnt load')

    test_image = np.expand_dims(test_image, axis=0)
    print(test_image)
    print(test_image.shape)

    pred = model.predict_classes(test_image)
    print(pred)

return JsonResponse(pred, safe=False)

Answer 1

您的test_image和tensorflow模型的输入不匹配。

# Your image shape is (, , 3)
test_image = cv2.imread('media/'+request.FILES['test_image'].name)

if test_image is not None:
    test_image = cv2.resize(test_image, (128, 128))
    test_image = np.array(test_image)
    test_image = test_image.astype('float32')
    test_image /= 255
    print(test_image.shape)
else:
    print('image didnt load')

# Your image shape is (, , 4)
test_image = np.expand_dims(test_image, axis=0)
print(test_image)
print(test_image.shape)

pred = model.predict_classes(test_image)

以上仅为假设。如果要调试，我想您应该打印图像大小并与模型定义的第一个布局进行比较。并检查尺寸（宽度，高度，深度）是否匹配