thank you for your videos... I am coming from a geospatial background.. I am using your channel to learn image segmentation and object detection for my project.. using deep learning to detect building damages along the shores after Hurricanes ... can you please do a video on how to use the xview2 dataset for image segmentation(buildings)
Approach will be very similar to what I showed using Random Forest. Define your X and Y and split into train and test X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.25, random_state=0) from sklearn.naive_bayes import GaussianNB #Or other NB of your choice gnb = GaussianNB() #Instantiate the classifier y_pred = gnb.fit(X_train, y_train).predict(X_test) #fit the classifier.
It is a band pass filter. I believe I've used Joachim Walter's FFT Filter plugin in imageJ. It removes high spatial frequencies (blurring the image) and low spatial frequencies (similar to subtracting a blurred image). It can also suppress horizontal or vertical stripes that were created by scanning an image line by line.
good explanation of features.. thank you sir
thank you for your videos... I am coming from a geospatial background.. I am using your channel to learn image segmentation and object detection for my project.. using deep learning to detect building damages along the shores after Hurricanes ... can you please do a video on how to use the xview2 dataset for image segmentation(buildings)
Just what I needed. Thank You :)
You're welcome!
Superb tutorials sir!
great video!
Great tutorials sir
Glad you like them!
Great tutorials!!!!
Glad you like them!
how can we use Naive bayes for multi-class classification?
Approach will be very similar to what I showed using Random Forest.
Define your X and Y and split into train and test
X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.25, random_state=0)
from sklearn.naive_bayes import GaussianNB #Or other NB of your choice
gnb = GaussianNB() #Instantiate the classifier
y_pred = gnb.fit(X_train, y_train).predict(X_test) #fit the classifier.
Great
2:00 - What is that filter?
It is a band pass filter. I believe I've used Joachim Walter's FFT Filter plugin in imageJ. It removes high spatial frequencies (blurring the image) and low spatial frequencies (similar to subtracting a blurred image). It can also suppress horizontal or vertical stripes that were created by scanning an image line by line.
What filter did you use at 01:52 ?
Sorry, not sure. Just added a bunch of filters and did not keep track of them. Looks like some sort of band pass filter.