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saadwazir / HistoSeg

HistoSeg is an Encoder-Decoder DCNN which utilizes the novel Quick Attention Modules and Multi Loss function to generate segmentation masks from histopathological images with greater accuracy. This repo contains the code to Test and Train the HistoSeg
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Sorry I don't know why my training .npy file does not work, could you please tell me why? or provide .npy file for train? #2

Open DanggoRyo opened 2 years ago

DanggoRyo commented 2 years ago

Sorry I don't know why my training .npy file didn't work, could you please tell me why? Or provide .npy file for train?

The following are the errors that result from training with .npy file：

Traceback (most recent call last): File "e:\HistoSeg\HistoSeg-Tensorflow\HistoSeg_Train.py", line 629, in results=model.fit(X_train, y_train, batch_size=batch_arg, epochs=epochs_arg, callbacks=callbacks, validation_data=(X_test, y_test) , verbose = 1)
File "E:\Users\15199\anaconda3\envs\Histoseg\lib\site-packages\tensorflow\python\keras\engine\training_v1.py", line 793, in fit return func.fit( File "E:\Users\15199\anaconda3\envs\Histoseg\lib\site-packages\tensorflow\python\keras\engine\training_arrays_v1.py", line 644, in fit return fit_loop( File "E:\Users\15199\anaconda3\envs\Histoseg\lib\site-packages\tensorflow\python\keras\engine\training_arrays_v1.py", line 380, in model_iteration
batch_outs = f(ins_batch) File "E:\Users\15199\anaconda3\envs\Histoseg\lib\site-packages\tensorflow\python\keras\backend.py", line 4067, in call fetched = self._callable_fn(*array_vals, File "E:\Users\15199\anaconda3\envs\Histoseg\lib\site-packages\tensorflow\python\client\session.py", line 1483, in call ret = tf_session.TF_SessionRunCallable(self._session._session, tensorflow.python.framework.errors_impl.InvalidArgumentError: 2 root error(s) found. (0) INVALID_ARGUMENT: assertion failed: [labels out of bound] [Condition x < y did not hold element-wise:] [x (metrics/mean_io_u/confusion_matrix/control_dependency:0) = ] [0 0 0...] [y (metrics/mean_io_u/confusion_matrix/Cast_2:0) = ] [2] [[{{function_node metrics_mean_io_u_confusion_matrix_assert_less_Assert_AssertGuard_false_7653}}{{node Assert}}]] [[expanded_conv_11_project_BN/cond/then/_980/FusedBatchNormV3/_6151]] (1) INVALID_ARGUMENT: assertion failed: [labels out of bound] [Condition x < y did not hold element-wise:] [x (metrics/mean_io_u/confusion_matrix/control_dependency:0) = ] [0 0 0...] [y (metrics/mean_io_u/confusion_matrix/Cast_2:0) = ] [2] [[{{function_node metrics_mean_io_u_confusion_matrix_assert_less_Assert_AssertGuard_false_7653}}{{node Assert}}]]

Thanks.

saadwazir commented 2 years ago

try these files HistoSeg_X_train_MoNuSeg_patches.npy HistoSeg_y_train_MoNuSeg_patches.npy

DanggoRyo commented 2 years ago

Thank you, I know why it can't run before, because the grayscale channel value is 1.