Prediction on test set is fine, failed on single image prediction
ttkrpink opened this issue · comments
I followed the sample all the way to the end. Right after the last prediction example. I add the following line. I tried other methods of reading the image file. The results are the same.
Thanks for your help
import PIL, cv2, imageio
filename = "./data/CamVid/test/0001TP_008580.png"
img = imageio.imread(filename) # novel image
img = preprocess_input(img) # use the preprocessing input method
image = np.expand_dims(img, axis=0)
pr_mask = model.predict(image)
This section of code generate an error message:
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
d:\PythonProjects\AI_Segmentation_Models\example.ipynb Cell 22 in <cell line: 8>()
[6](vscode-notebook-cell:/d%3A/PythonProjects/AI_Segmentation_Models/example.ipynb#X30sZmlsZQ%3D%3D?line=5) img = preprocess_input(img) # use the preprocessing input method
[7](vscode-notebook-cell:/d%3A/PythonProjects/AI_Segmentation_Models/example.ipynb#X30sZmlsZQ%3D%3D?line=6) image = np.expand_dims(img, axis=0)
----> [8](vscode-notebook-cell:/d%3A/PythonProjects/AI_Segmentation_Models/example.ipynb#X30sZmlsZQ%3D%3D?line=7) pr_mask = model.predict(image)
File d:\python38\lib\site-packages\keras\utils\traceback_utils.py:67, in filter_traceback.<locals>.error_handler(*args, **kwargs)
65 except Exception as e: # pylint: disable=broad-except
66 filtered_tb = _process_traceback_frames(e.__traceback__)
---> 67 raise e.with_traceback(filtered_tb) from None
68 finally:
69 del filtered_tb
File d:\python38\lib\site-packages\tensorflow\python\eager\execute.py:54, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
52 try:
53 ctx.ensure_initialized()
---> 54 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
55 inputs, attrs, num_outputs)
56 except core._NotOkStatusException as e:
57 if name is not None:
InvalidArgumentError: Graph execution error:
Detected at node 'model_1/decoder_stage0_concat/concat' defined at (most recent call last):
File "C:\Users\chao\AppData\Local\Programs\Python\Python38\lib\runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\Users\chao\AppData\Local\Programs\Python\Python38\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "d:\python38\lib\site-packages\ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "d:\python38\lib\site-packages\traitlets\config\application.py", line 846, in launch_instance
app.start()
File "d:\python38\lib\site-packages\ipykernel\kernelapp.py", line 677, in start
self.io_loop.start()
File "d:\python38\lib\site-packages\tornado\platform\asyncio.py", line 199, in start
self.asyncio_loop.run_forever()
File "C:\Users\chao\AppData\Local\Programs\Python\Python38\lib\asyncio\base_events.py", line 570, in run_forever
self._run_once()
File "C:\Users\chao\AppData\Local\Programs\Python\Python38\lib\asyncio\base_events.py", line 1859, in _run_once
handle._run()
File "C:\Users\chao\AppData\Local\Programs\Python\Python38\lib\asyncio\events.py", line 81, in _run
self._context.run(self._callback, *self._args)
File "d:\python38\lib\site-packages\ipykernel\kernelbase.py", line 473, in dispatch_queue
await self.process_one()
File "d:\python38\lib\site-packages\ipykernel\kernelbase.py", line 462, in process_one
await dispatch(*args)
File "d:\python38\lib\site-packages\ipykernel\kernelbase.py", line 369, in dispatch_shell
await result
File "d:\python38\lib\site-packages\ipykernel\kernelbase.py", line 664, in execute_request
reply_content = await reply_content
File "d:\python38\lib\site-packages\ipykernel\ipkernel.py", line 355, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "d:\python38\lib\site-packages\ipykernel\zmqshell.py", line 532, in run_cell
return super().run_cell(*args, **kwargs)
File "d:\python38\lib\site-packages\IPython\core\interactiveshell.py", line 2854, in run_cell
result = self._run_cell(
File "d:\python38\lib\site-packages\IPython\core\interactiveshell.py", line 2900, in _run_cell
return runner(coro)
File "d:\python38\lib\site-packages\IPython\core\async_helpers.py", line 129, in _pseudo_sync_runner
coro.send(None)
File "d:\python38\lib\site-packages\IPython\core\interactiveshell.py", line 3098, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "d:\python38\lib\site-packages\IPython\core\interactiveshell.py", line 3301, in run_ast_nodes
if await self.run_code(code, result, async_=asy):
File "d:\python38\lib\site-packages\IPython\core\interactiveshell.py", line 3361, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "C:\Users\chao\AppData\Local\Temp\ipykernel_25708\419308408.py", line 8, in <cell line: 8>
pr_mask = model.predict(image)
File "d:\python38\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\engine\training.py", line 2033, in predict
tmp_batch_outputs = self.predict_function(iterator)
File "d:\python38\lib\site-packages\keras\engine\training.py", line 1845, in predict_function
return step_function(self, iterator)
File "d:\python38\lib\site-packages\keras\engine\training.py", line 1834, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "d:\python38\lib\site-packages\keras\engine\training.py", line 1823, in run_step
outputs = model.predict_step(data)
File "d:\python38\lib\site-packages\keras\engine\training.py", line 1791, in predict_step
return self(x, training=False)
File "d:\python38\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\engine\training.py", line 490, in __call__
return super().__call__(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\engine\base_layer.py", line 1014, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "d:\python38\lib\site-packages\keras\utils\traceback_utils.py", line 92, in error_handler
return fn(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\engine\functional.py", line 458, in call
return self._run_internal_graph(
File "d:\python38\lib\site-packages\keras\engine\functional.py", line 596, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\engine\base_layer.py", line 1014, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "d:\python38\lib\site-packages\keras\utils\traceback_utils.py", line 92, in error_handler
return fn(*args, **kwargs)
File "d:\python38\lib\site-packages\keras\layers\merging\base_merge.py", line 178, in call
return self._merge_function(inputs)
File "d:\python38\lib\site-packages\keras\layers\merging\concatenate.py", line 126, in _merge_function
return backend.concatenate(inputs, axis=self.axis)
File "d:\python38\lib\site-packages\keras\backend.py", line 3313, in concatenate
return tf.concat([to_dense(x) for x in tensors], axis)
Node: 'model_1/decoder_stage0_concat/concat'
ConcatOp : Dimension 2 in both shapes must be equal: shape[0] = [1,2048,24,30] vs. shape[1] = [1,1024,23,30]
[[{{node model_1/decoder_stage0_concat/concat}}]] [Op:__inference_predict_function_26153]
Figured out the problem.
Dataset class has cv2 function after imread, you have to do the same operation for the single image prediction.