def modelConfig(self,network_backbone = "resnet101", num_classes = 1, class_names = ["BG"], batch_size = 1, image_max_dim = 512, image_min_dim = 512, image_resize_mode ="square", gpu_count = 1):
self.config = Config(BACKBONE = network_backbone, NUM_CLASSES = 1 + num_classes, class_names = class_names,
IMAGES_PER_GPU = batch_size, IMAGE_MAX_DIM = image_max_dim, IMAGE_MIN_DIM = image_min_dim, IMAGE_RESIZE_MODE = image_resize_mode,
GPU_COUNT = gpu_count)
if network_backbone == "resnet101":
print("Using resnet101 as network backbone For Mask R-CNN model")
else:
print("Using resnet50 as network backbone For Mask R-CNN model")
def inferConfig(self,
name=None,
network_backbone="resnet101",
num_classes=1,
class_names=["BG"],
batch_size=1,
detection_threshold=0.7,
image_max_dim=512,
image_min_dim=512,
image_resize_mode="square",
gpu_count=1):
self.config = Config(BACKBONE=network_backbone,
NUM_CLASSES=1 + num_classes,
class_names=class_names,
IMAGES_PER_GPU=batch_size,
IMAGE_MAX_DIM=image_max_dim,
IMAGE_MIN_DIM=image_min_dim,
DETECTION_MIN_CONFIDENCE=detection_threshold,
IMAGE_RESIZE_MODE=image_resize_mode,
GPU_COUNT=gpu_count)