Issues related to the code for ROI pooling from the feature map
I am trying to do ROI pooling on the feature map obtained from the VGG layers but I don't know how to code this layers. Can anybody help me out?
Here is my VGG layers:
model=Sequential()
model.add(ZeroPadding2D((1,1),input_shape=(3,112,112)))
model.add(Convolution2D(64, 3, 3, activation='relu'))
model.add(BatchNormalization(momentum=0.99))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(64, 3, 3, activation='relu'))
model.add(BatchNormalization(momentum=0.99))
model.add(MaxPooling2D((2,2), strides=(2,2), dim_ordering="th"))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(128, 3, 3, activation='relu'))
model.add(BatchNormalization(momentum=0.99))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(128, 3, 3, activation='relu'))
model.add(BatchNormalization(momentum=0.99))
model.add(MaxPooling2D((2,2), strides=(2,2), dim_ordering="th"))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(256, 3, 3, activation='relu'))
`
The corresponding model is described in the picture below:
Topic object-detection generative-models gan keras neural-network
Category Data Science