random_seed: 42
enc_key: "<your_enc_key>"
verbose: True
network_config {
	input_image_config {
		image_type: RGB
		image_channel_order: 'bgr'
		size_min {
			min:736
		}
		image_channel_mean {
			key: 'b'
			value: 103.939
		}
		image_channel_mean {
			key: 'g'
			value: 116.779
		}
		image_channel_mean {
			key: 'r'
			value: 123.68
		}
		image_scaling_factor: 1.0
        }
	feature_extractor: "mobilenet_v2"
	anchor_box_config {
		scale: 128.0
		scale: 256.0
		scale: 512.0
		ratio: 1.0
		ratio: 0.5
		ratio: 2.0
	}
	freeze_bn: True
	freeze_blocks: 1
	freeze_blocks: 2
	roi_mini_batch: 256
	rpn_stride: 16
	conv_bn_share_bias: True
	roi_pooling_config {
		pool_size: 7
		pool_size_2x: True
	}
}

training_config {
	kitti_data_config {
		images_dir: '/workspace/tlt-experiments/FasterRCNN_18/data/train/images'
		labels_dir: '/workspace/tlt-experiments/FasterRCNN_18/data/train/labels'
	}
	training_data_parser: 'raw_kitti'
	data_augmentation {
		use_augmentation: False
		spatial_augmentation {
			hflip_probability: 0.0
			vflip_probability: 0.0
			zoom_min: 1.0
			zoom_max: 1.0
			translate_max_x: 0
			translate_max_y: 0
		}
		color_augmentation {
			color_shift_stddev: 0.0
			hue_rotation_max: 0.0
			saturation_shift_max: 0.0
			contrast_scale_max: 0.0
			contrast_center: 0.5
		}
	}
	num_epochs: 7
	class_mapping {
		key: 'plate'
		value: 0
	}
	class_mapping {
		key: "textline"
		value: 1
	}
	class_mapping {
		key: "background"
		value: 2
	}

	pretrained_model: ""
	pretrained_weights: "/workspace/tlt-experiments/FasterRCNN_18/mobilenet_v2.h5"
	output_weights: "/workspace/tlt-experiments/FasterRCNN_18/mobilenetv2_weight.tltw"
	output_model: "/workspace/tlt-experiments/FasterRCNN_18/mobilenetv2_model.tlt"
	rpn_min_overlap: 0.3
	rpn_max_overlap: 0.7
	classifier_min_overlap: 0.0
	classifier_max_overlap: 0.5
	gt_as_roi: True
	std_scaling: 1.0
	classifier_regr_std {
		key: 'x'
		value: 10.0
	}
	classifier_regr_std {
		key: 'y'
		value: 10.0
	}
	classifier_regr_std {
		key: 'w'
		value: 5.0
	}
	classifier_regr_std {
		key: 'h'
		value: 5.0
	}
	rpn_mini_batch: 256
	rpn_pre_nms_top_N: 12000
	rpn_nms_max_boxes: 2000
	rpn_nms_overlap_threshold: 0.7
	reg_config {
		reg_type: 'L2'
		weight_decay: 1e-4
	}
	optimizer {
		adam {
			lr: 0.0001
			beta_1: 0.9
			beta_2: 0.999
			decay: 0.0
		}
	}
	lr_scheduler {
		step {
			base_lr: 0.001
			gamma: 1.0
			step_size: 30
		}
	}
	lambda_rpn_regr: 1.0
	lambda_rpn_class: 1.0
	lambda_cls_regr: 1.0
	lambda_cls_class: 1.0
	inference_config {
		images_dir: '/workspace/tlt-experiments/FasterRCNN_18/data/infer/images'
		model: '/workspace/tlt-experiments/FasterRCNN_18/mobilenetv2_model.epoch7.tlt'
		detection_image_output_dir: '/workspace/tlt-experiments/FasterRCNN_18/data/infer/outputs/images'
		labels_dump_dir: '/workspace/tlt-experiments/FasterRCNN_18/data/infer/outputs/labels'
		rpn_pre_nms_top_N: 6000
		rpn_nms_max_boxes: 300
		rpn_nms_overlap_threshold: 0.7
		bbox_visualize_threshold: 0.6
		classifier_nms_max_boxes: 300
		classifier_nms_overlap_threshold: 0.3
	}

	evaluation_config {
		dataset {
			images_dir : '/workspace/tlt-experiments/FasterRCNN_18/data/eval/images'
			labels_dir: '/workspace/tlt-experiments/FasterRCNN_18/data/eval/labels'
		}
		data_parser: 'raw_kitti'
		model: '/workspace/tlt-experiments/FasterRCNN_18/mobilenetv2_model.epoch7.tlt'
		labels_dump_dir: '/workspace/tlt-experiments/FasterRCNN_18/data/eval/outputs'
		rpn_pre_nms_top_N: 6000
		rpn_nms_max_boxes: 300
		rpn_nms_overlap_threshold: 0.7
		classifier_nms_max_boxes: 300
		classifier_nms_overlap_threshold: 0.3
		object_confidence_thres: 0.0001
		use_voc07_11point_metric:True
	}
}