ValueError：层顺序的输入0与层不兼容（重塑错误）

Question

这是我的代码：

import cv2
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.models import load_model

model=load_model('equation.h5')
############  prediction via paints ##########
### glob
run = False
ix, iy = -1, -1
follow = 25
img = np.zeros((512, 512, 1))

### func
def draw(event, x, y, flag, params):
    global run, ix, iy, img, follow
    if event == cv2.EVENT_LBUTTONDOWN:
        run = True
        ix, iy = x, y
    elif event == cv2.EVENT_MOUSEMOVE:
        if run == True:
            cv2.circle(img, (x, y), 20, (255, 255, 255), -1)

    elif event == cv2.EVENT_LBUTTONUP:
        run = False
        cv2.circle(img, (x, y), 20, (255, 255, 255), -1)
        gray = cv2.resize(img, (100,100))
        gray = gray.reshape(-1,100,100,1)
        result = np.argmax(model.predict(gray))
        result = 'cnn : {}'.format(result)
        file_object = open('sample.txt', 'a')
        # Append 'hello' at the end of file
        file_object.write(result +'\n')
        # Close the file
        file_object.close()
        cv2.putText(img, org=(25, follow), fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=1, text=result,
                    color=(255, 0, 0), thickness=1)
        follow += 25
    elif event == cv2.EVENT_RBUTTONDOWN:
        img = np.zeros((512, 512, 1))
        follow = 25

### param
cv2.namedWindow('image')
cv2.setMouseCallback('image', draw)

while True:
    cv2.imshow("image", img)

    if cv2.waitKey(1) == 27:
        break

cv2.destroyAllWindows()

我使用+,-,=等数学符号创建了 model，model 的输入形状为 (100, 100, 3)。 当我尝试使用 model 时，它会抛出一个错误，错误在于重塑，这里的图像是通过 OpenCV 拍摄的，它在重塑时被调整大小和重塑，它会引发以下错误：

C:\Users\Suganya\PycharmProjects\pythonProject1\venv\Scripts\python.exe C:/Users/Suganya/PycharmProjects/pythonProject1/digit.py
2021-05-02 11:27:53.306670: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2021-05-02 11:27:53.306939: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2021-05-02 11:27:55.277915: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-02 11:27:55.278851: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
2021-05-02 11:27:55.279077: W tensorflow/stream_executor/cuda/cuda_driver.cc:326] failed call to cuInit: UNKNOWN ERROR (303)
2021-05-02 11:27:55.282800: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: LAPTOP-OTIM27TH
2021-05-02 11:27:55.283095: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: LAPTOP-OTIM27TH
2021-05-02 11:27:55.283480: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-05-02 11:27:55.284291: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-02 11:27:57.000628: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
Traceback (most recent call last):
  File "C:/Users/Suganya/PycharmProjects/pythonProject1/digit.py", line 29, in draw
    result = np.argmax(model.predict(gray))
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1629, in predict
    tmp_batch_outputs = self.predict_function(iterator)
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\eager\def_function.py", line 828, in __call__
    result = self._call(*args, **kwds)
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\eager\def_function.py", line 871, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\eager\def_function.py", line 726, in _initialize
    *args, **kwds))
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\eager\function.py", line 2969, in _get_concrete_function_internal_garbage_collected
    graph_function, _ = self._maybe_define_function(args, kwargs)
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\eager\function.py", line 3361, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\eager\function.py", line 3206, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\framework\func_graph.py", line 990, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\eager\def_function.py", line 634, in wrapped_fn
    out = weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\framework\func_graph.py", line 977, in wrapper
    raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\keras\engine\training.py:1478 predict_function  *
        return step_function(self, iterator)
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\keras\engine\training.py:1468 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1259 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2730 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:3417 _call_for_each_replica
        return fn(*args, **kwargs)
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\keras\engine\training.py:1461 run_step  **
        outputs = model.predict_step(data)
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\keras\engine\training.py:1434 predict_step
        return self(x, training=False)
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\keras\engine\base_layer.py:998 __call__
        input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
    C:\Users\Suganya\PycharmProjects\pythonProject1\venv\lib\site-packages\tensorflow\python\keras\engine\input_spec.py:259 assert_input_compatibility
        ' but received input with shape ' + display_shape(x.shape))

    ValueError: Input 0 of layer sequential is incompatible with the layer: expected axis -1 of input shape to have value 3 but received input with shape (None, 100, 100, 1)

Answer 1

你说

model 的输入形状为 (100,100,3)

但是您将形状为 (100,100,1) 的灰度图像传递给 model。

尝试将您的图像修改为 RGB，或者，如果您想使用灰度图像，只需在 3 个通道中的每个通道上使用相同的值。