deeplabv3plus (Google's new algorithm for semantic segmentation) in keras:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
model = deeplabv3_plus()
smooth = 1.
model.compile(optimizer=Adam(lr=1e-4), loss=IOU_calc_loss, metrics=[IOU_calc])
history = model.fit(X_train, y_train, batch_size=1, epochs=50, verbose=1, validation_split=0.1, shuffle=False)
what can i do for this?
Train on 81 samples, validate on 9 samples
Epoch 1/50
i have RGB pictures ,but can not train
Train on 81 samples, validate on 9 samples Epoch 1/50
InvalidArgumentError Traceback (most recent call last) ~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, args) 1326 try: -> 1327 return fn(args) 1328 except errors.OpError as e:
~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata) 1305 feed_dict, fetch_list, target_list, -> 1306 status, run_metadata) 1307
~\Anaconda3\lib\contextlib.py in exit(self, type, value, traceback) 87 try: ---> 88 next(self.gen) 89 except StopIteration:
~\Anaconda3\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status() 465 compat.as_text(pywrap_tensorflow.TF_Message(status)), --> 466 pywrap_tensorflow.TF_GetCode(status)) 467 finally:
InvalidArgumentError: Incompatible shapes: [786432] vs. [5505024] [[Node: loss_6/bilinear_upsampling_24_loss/mul = Mul[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](loss_6/bilinear_upsampling_24_loss/Reshape, loss_6/bilinear_upsampling_24_loss/Reshape_1)]] [[Node: loss_6/mul/_43833 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_79013_loss_6/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)