I encountered with following error
C:\ProgramData\Anaconda3\envs\human-detector\python.exe "D:/Campus/FYP/Implementations/Codes From Github/human_detection_using_hog/human-detector/object_detector/detector.py" C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\sklearn\base.py:253: UserWarning: Trying to unpickle estimator LinearSVC from version pre-0.18 when using version 0.20.4. This might lead to breaking code or invalid results. Use at your own risk. UserWarning) C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\skimage\feature\_hog.py:150: skimage_deprecation: Default value of block_norm==L1is deprecated and will be changed toL2-Hysin v0.15. To supress this message specify explicitly the normalization method. skimage_deprecation) Traceback (most recent call last): File "D:/human_detection_using_hog/human-detector/object_detector/detector.py", line 104, in <module> test_folder(foldername) File "D:/human_detection_using_hog/human-detector/object_detector/detector.py", line 100, in test_folder detector(filename) File "D:/human_detection_using_hog/human-detector/object_detector/detector.py", line 58, in detector pred = clf.predict(fd) File "C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\sklearn\linear_model\base.py", line 281, in predict scores = self.decision_function(X) File "C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\sklearn\linear_model\base.py", line 262, in decision_function % (X.shape[1], n_features)) ValueError: X has 100620 features per sample; expecting 6480
any guesses on how to solve this?
I encountered with following error
C:\ProgramData\Anaconda3\envs\human-detector\python.exe "D:/Campus/FYP/Implementations/Codes From Github/human_detection_using_hog/human-detector/object_detector/detector.py" C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\sklearn\base.py:253: UserWarning: Trying to unpickle estimator LinearSVC from version pre-0.18 when using version 0.20.4. This might lead to breaking code or invalid results. Use at your own risk. UserWarning) C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\skimage\feature\_hog.py:150: skimage_deprecation: Default value ofblock_norm==L1is deprecated and will be changed toL2-Hysin v0.15. To supress this message specify explicitly the normalization method. skimage_deprecation) Traceback (most recent call last): File "D:/human_detection_using_hog/human-detector/object_detector/detector.py", line 104, in <module> test_folder(foldername) File "D:/human_detection_using_hog/human-detector/object_detector/detector.py", line 100, in test_folder detector(filename) File "D:/human_detection_using_hog/human-detector/object_detector/detector.py", line 58, in detector pred = clf.predict(fd) File "C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\sklearn\linear_model\base.py", line 281, in predict scores = self.decision_function(X) File "C:\ProgramData\Anaconda3\envs\human-detector\lib\site-packages\sklearn\linear_model\base.py", line 262, in decision_function % (X.shape[1], n_features)) ValueError: X has 100620 features per sample; expecting 6480any guesses on how to solve this?