firenet-lightweight-network-for-fire-detection's People
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Training results doesn't match the result mentioned in the paper
Hi,
First of all thank you for sharing the code,
i trained the model using the train script and,
When i compare the output results of testing the new trained model , it doesn't match the result mentioned in the paper.
Could you please explain why?
train error
hi
when i train model,run Train.ipynb, error happend follow this:
`
history = model.fit(X, Y, batch_size=32, epochs=100,validation_split=0.3)
model.fit_generator(datagen.flow(X, Y, batch_size=32),
epochs=100,
verbose=1)
ValueError Traceback (most recent call last)
in ()
----> 1 history = model.fit(X, Y, batch_size=32, epochs=100,validation_split=0.3)
2 # model.fit_generator(datagen.flow(X, Y, batch_size=32),
3 # epochs=100,
4 # verbose=1)
/home/lab134/anaconda3/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in _method_wrapper(self, *args, **kwargs)
64 def _method_wrapper(self, *args, **kwargs):
65 if not self._in_multi_worker_mode(): # pylint: disable=protected-access
---> 66 return method(self, *args, **kwargs)
67
68 # Running inside run_distribute_coordinator already.
/home/lab134/anaconda3/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
795 data_adapter.train_validation_split((x, y, sample_weight),
796 validation_split=validation_split,
--> 797 shuffle=False))
798
799 with self.distribute_strategy.scope(), \
/home/lab134/anaconda3/lib/python3.6/site-packages/tensorflow/python/keras/engine/data_adapter.py in train_validation_split(arrays, validation_split, shuffle)
1309 raise ValueError(
1310 "validation_split is only supported for Tensors or NumPy "
-> 1311 "arrays, found: {}".format(arrays))
1312
1313 if all(t is None for t in flat_arrays):
ValueError: validation_split is only supported for Tensors or NumPy arrays, found: (array([[[[0.15686275, 0.21176471, 0. ],
[0.16862745, 0.22352941, 0.01176471],
[0.18431373, 0.24313725, 0. ],
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[0.12941176, 0.09019608, 0.01568627]],
[[0.16862745, 0.21960784, 0. ],
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[0.18431373, 0.23529412, 0. ],
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[0.15294118, 0.12156863, 0.00784314],
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[0.13333333, 0.10196078, 0.01176471]],
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[0.20784314, 0.23921569, 0. ],
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1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1], None)
`
how should i do?
thanks
About the use of performance accelerators?
Have you used any hardware/software accelerators?
how run this project?
hi,
please explain how run this code of project on jupyter notebook?
some line of code has errors........
Labeling the fire
Can this project be edited so that we can have a bounding box around the fire? I want to detect exactly the fire in the frame captured. Can you please provide with the steps to take or the functions to use. I checked on the internet but it seems that there are files that missing. Looking forward to your answer, thank you in advance.
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