Reputation: 41
How can I improve the mask prediction by Mask RCNN model? Bounding box and class prediction seems to be okay in my case. Masks are kind of acceptable for small objects but not for big objects. The story is similar for other images as well. Here's my configurations:
RPN_ANCHOR_SCALES = (16, 32, 64, 128, 256)
TRAIN_ROIS_PER_IMAGE = 64
MAX_GT_INSTANCES = 50
POST_NMS_ROIS_INFERENCE = 500
POST_NMS_ROIS_TRAINING = 1000
USE_MINI_MASK True
MASK_SHAPE [28, 28]
MINI MASK_SHAPE [56, 56]
LEARNING_RATE = 0.001
LEARNING_MOMENTUM = 0.9
WEIGHT_DECAY = 0.0001
EPOCHS = 500
Any suggestions would be great!
Upvotes: 1
Views: 1109
Reputation: 41
Wanted to give an update to my post. I improved my accuracy by changing default mask_shape to [56, 56]. In order to be able to change the config, an extra conv2dtranspose layer should be added in model.train py
Upvotes: 1