Thank you for enjoying the article.

For Multi-class classification

Update the myMaskRCNNConfig with the number of classes based on your custom dataset

# number of classes (we would normally add +1 for the background)
# kangaroo + BG

NUM_CLASSES = 1+1

Update the code for load_dataset() to include the different classes in your dataset

# Add classes. We have only one class to add.
self.add_class(“dataset”, 1, “kangaroo”)

Update the code for load_mask() to include the different classes in your dataset

class_ids.append(self.class_names.index(‘kangaroo’))

put the images for different classes in the different folders for train, test and validation datasets

Hope this helps

Loves learning, sharing, and discovering myself. Passionate about Machine Learning and Deep Learning

Loves learning, sharing, and discovering myself. Passionate about Machine Learning and Deep Learning