Traceback (most recent call last):
File "C:\Users\Adarsh\Desktop\FYP\Final-Year-Project-master\AttendanceTaker.py", line 52, in
predictions = ifk_obj.getPrediction('KNN_Classifier_80_TrainingData_92_percent_accurate')
File "C:\Users\Adarsh\Desktop\FYP\Final-Year-Project-master\ImageFeederKNN.py", line 49, in getPrediction
self.predicted_results = self.KNN_classifier.predict(self.array_of_images)
File "C:\Program Files\Python35\lib\site-packages\sklearn\neighbors\classification.py", line 145, in predict
neigh_dist, neigh_ind = self.kneighbors(X)
File "C:\Program Files\Python35\lib\site-packages\sklearn\neighbors\base.py", line 385, in kneighbors
for s in gen_even_slices(X.shape[0], n_jobs)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 779, in call
while self.dispatch_one_batch(iterator):
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 625, in dispatch_one_batch
self._dispatch(tasks)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 588, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib_parallel_backends.py", line 111, in apply_async
result = ImmediateResult(func)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib_parallel_backends.py", line 332, in init
self.results = batch()
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 131, in call
return [func(*args, *kwargs) for func, args, kwargs in self.items]
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 131, in
return [func(args, **kwargs) for func, args, kwargs in self.items]
File "sklearn\neighbors\binary_tree.pxi", line 1294, in sklearn.neighbors.kd_tree.BinaryTree.query
ValueError: query data dimension must match training data dimension
Traceback (most recent call last): File "C:\Users\Adarsh\Desktop\FYP\Final-Year-Project-master\AttendanceTaker.py", line 52, in
predictions = ifk_obj.getPrediction('KNN_Classifier_80_TrainingData_92_percent_accurate')
File "C:\Users\Adarsh\Desktop\FYP\Final-Year-Project-master\ImageFeederKNN.py", line 49, in getPrediction
self.predicted_results = self.KNN_classifier.predict(self.array_of_images)
File "C:\Program Files\Python35\lib\site-packages\sklearn\neighbors\classification.py", line 145, in predict
neigh_dist, neigh_ind = self.kneighbors(X)
File "C:\Program Files\Python35\lib\site-packages\sklearn\neighbors\base.py", line 385, in kneighbors
for s in gen_even_slices(X.shape[0], n_jobs)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 779, in call
while self.dispatch_one_batch(iterator):
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 625, in dispatch_one_batch
self._dispatch(tasks)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 588, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib_parallel_backends.py", line 111, in apply_async
result = ImmediateResult(func)
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib_parallel_backends.py", line 332, in init
self.results = batch()
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 131, in call
return [func(*args, *kwargs) for func, args, kwargs in self.items]
File "C:\Program Files\Python35\lib\site-packages\sklearn\externals\joblib\parallel.py", line 131, in
return [func( args, **kwargs) for func, args, kwargs in self.items]
File "sklearn\neighbors\binary_tree.pxi", line 1294, in sklearn.neighbors.kd_tree.BinaryTree.query
ValueError: query data dimension must match training data dimension