Op:__inference_predict_function_82024 error in neural network - deep-learning

Question

i am getting this error when i run a simple neural network model using MNIST dataset.
Heres my model
customNN = Sequential()
# input layer
customNN.add(Dense(4, activation = "relu",input_shape = (28,28)))
# Hidden layer
customNN.add(Dense(16,activation = "relu"))
customNN.add(Dense(32,activation = "relu"))
customNN.add(Dense(64,activation = "relu"))
customNN.add(Dense(100,activation = "relu"))
customNN.add(Dense(128,activation = "relu"))
# flatten() function is used to get a copy of an given array collapsed into one dimension.
customNN.add(Flatten())
# output layer
customNN.add(Dense(10,activation = "softmax"))
when i compile it successfully done with MNIST dataset
customNN.compile(optimizer="adam", loss= "categorical_crossentropy", metrics=["accuracy"])
customNN.fit(xtrain,ytrain, epochs=10)
import cv2
def input_prepare(img):
img = np.asarray(img) # convert to array
img = cv2.resize(img, (28, 28 )) # resize to target shape
img = cv2.bitwise_not(img) # [optional] turned bg to black - {bitwise_not} turns 1's into 0's and 0's into 1's
img = img / 255 # normalize
img = img.reshape(1, 784) # reshape it to input placeholder shape
return img
img = cv2.imread('4.jpg')
orig = img.copy() # save for plotting later on
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # gray scaling
img = input_prepare(img)
pred = customNN.predict(img)
plt.imshow(cv2.cvtColor(orig, cv2.COLOR_BGR2RGB))
plt.title(np.argmax(pred, axis=1))
plt.show()
But when i run this code i am getting the following error
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-29-509e1856bd1e> in <module>
16
17
---> 18 pred = customNN.predict(img)
19 plt.imshow(cv2.cvtColor(orig, cv2.COLOR_BGR2RGB))
20 plt.title(np.argmax(pred, axis=1))
D:\anaconda3\lib\site-packages\keras\utils\traceback_utils.py in error_handler(*args, **kwargs)
68 # To get the full stack trace, call:
69 # `tf.debugging.disable_traceback_filtering()`
---> 70 raise e.with_traceback(filtered_tb) from None
71 finally:
72 del filtered_tb
D:\anaconda3\lib\site-packages\tensorflow\python\eager\execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
51 ctx.ensure_initialized()
52 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
---> 53 inputs, attrs, num_outputs)
54 except core._NotOkStatusException as e:
55 if name is not None:
InvalidArgumentError: Graph execution error:
Detected at node 'sequential/dense/Tensordot/GatherV2_1' defined at (most recent call last):
File "D:\anaconda3\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "D:\anaconda3\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "D:\anaconda3\lib\site-packages\ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\traitlets\config\application.py", line 1041, in launch_instance
app.start()
File "D:\anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 583, in start
self.io_loop.start()
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\platform\asyncio.py", line 215, in start
self.asyncio_loop.run_forever()
File "D:\anaconda3\lib\asyncio\base_events.py", line 541, in run_forever
self._run_once()
File "D:\anaconda3\lib\asyncio\base_events.py", line 1786, in _run_once
handle._run()
File "D:\anaconda3\lib\asyncio\events.py", line 88, in _run
self._context.run(self._callback, *self._args)
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\ioloop.py", line 687, in <lambda>
lambda f: self._run_callback(functools.partial(callback, future))
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\ioloop.py", line 740, in _run_callback
ret = callback()
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\gen.py", line 821, in inner
self.ctx_run(self.run)
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\gen.py", line 782, in run
yielded = self.gen.send(value)
File "D:\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 361, in process_one
yield gen.maybe_future(dispatch(*args))
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\gen.py", line 234, in wrapper
yielded = ctx_run(next, result)
File "D:\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 268, in dispatch_shell
yield gen.maybe_future(handler(stream, idents, msg))
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\gen.py", line 234, in wrapper
yielded = ctx_run(next, result)
File "D:\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 541, in execute_request
user_expressions, allow_stdin,
File "C:\Users\Deadpool\AppData\Roaming\Python\Python37\site-packages\tornado\gen.py", line 234, in wrapper
yielded = ctx_run(next, result)
File "D:\anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 300, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "D:\anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2976, in run_cell
raw_cell, store_history, silent, shell_futures, cell_id
File "D:\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3030, in _run_cell
return runner(coro)
File "D:\anaconda3\lib\site-packages\IPython\core\async_helpers.py", line 78, in _pseudo_sync_runner
coro.send(None)
File "D:\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3258, in run_cell_async
interactivity=interactivity, compiler=compiler, result=result)
File "D:\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3473, in run_ast_nodes
if (await self.run_code(code, result, async_=asy)):
File "D:\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3553, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-29-509e1856bd1e>", line 18, in <module>
pred = customNN.predict(img)
File "D:\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\engine\training.py", line 2350, in predict
tmp_batch_outputs = self.predict_function(iterator)
File "D:\anaconda3\lib\site-packages\keras\engine\training.py", line 2137, in predict_function
return step_function(self, iterator)
File "D:\anaconda3\lib\site-packages\keras\engine\training.py", line 2123, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "D:\anaconda3\lib\site-packages\keras\engine\training.py", line 2111, in run_step
outputs = model.predict_step(data)
File "D:\anaconda3\lib\site-packages\keras\engine\training.py", line 2079, in predict_step
return self(x, training=False)
File "D:\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\engine\training.py", line 561, in __call__
return super().__call__(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\engine\base_layer.py", line 1132, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\engine\sequential.py", line 413, in call
return super().call(inputs, training=training, mask=mask)
File "D:\anaconda3\lib\site-packages\keras\engine\functional.py", line 511, in call
return self._run_internal_graph(inputs, training=training, mask=mask)
File "D:\anaconda3\lib\site-packages\keras\engine\functional.py", line 668, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\engine\base_layer.py", line 1132, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "D:\anaconda3\lib\site-packages\keras\layers\core\dense.py", line 244, in call
outputs = tf.tensordot(inputs, self.kernel, [[rank - 1], [0]])
Node: 'sequential/dense/Tensordot/GatherV2_1'
indices[0] = 2 is not in [0, 2)
[[{{node sequential/dense/Tensordot/GatherV2_1}}]] [Op:__inference_predict_function_82024]
Cannot figure out whats the problem? i am newbie in DL and trying to improve. any help to find out the problem is highly appreciated
thanks
i have tried a new image to detect the handwriting, but shows error