问题描述
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,-1)
gray = cv2.resize(img,(100,100))
gray = gray.reshape(-1,100,1)
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),thickness=1)
follow += 25
elif event == cv2.EVENT_RBUTTONDOWN:
img = np.zeros((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 +,-,=
等数学符号创建了一个模型,模型的输入形状是 (100,3)。
当我尝试使用该模型时,它会抛出一个错误,错误在于重塑,这里通过 OpenCV 拍摄了一张图像,并在重塑时对其进行了大小调整和整形,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,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,1)
解决方法
你说
模型的输入形状为(100,100,3)
但是您将形状为 (100,1) 的灰度图像传递给模型。
尝试将图像修改为 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。