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)