def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.model_manager = ModelManager(configer) self.test_loader = TestDataLoader(configer) self.device = torch.device('cpu' if self.configer.get('gpu') is None else 'cuda') self.gan_net = None self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.seg_visualizer = SegVisualizer(configer) self.seg_parser = SegParser(configer) self.seg_model_manager = SegModelManager(configer) self.seg_data_loader = DataLoader(configer) self.device = torch.device('cpu' if self.configer.get('gpu') is None else 'cuda') self.seg_net = None self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.pose_vis = PoseVisualizer(configer) self.pose_model_manager = PoseModelManager(configer) self.pose_data_loader = DataLoader(configer) self.heatmap_generator = HeatmapGenerator(configer) self.device = torch.device('cpu' if self.configer.get('gpu') is None else 'cuda') self.pose_net = None self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.det_visualizer = DetVisualizer(configer) self.det_parser = DetParser(configer) self.det_model_manager = ModelManager(configer) self.det_data_loader = DataLoader(configer) self.ssd_priorbox_layer = SSDPriorBoxLayer(configer) self.ssd_target_generator = SSDTargetGenerator(configer) self.device = torch.device('cpu' if self.configer.get('gpu') is None else 'cuda') self.det_net = None self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.det_visualizer = DetVisualizer(configer) self.det_parser = DetParser(configer) self.det_model_manager = ModelManager(configer) self.det_data_loader = DataLoader(configer) self.yolo_target_generator = YOLOTargetGenerator(configer) self.yolo_detection_layer = YOLODetectionLayer(configer) self.device = torch.device( 'cpu' if self.configer.get('gpu') is None else 'cuda') self.det_net = None self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.det_visualizer = DetVisualizer(configer) self.det_parser = DetParser(configer) self.det_model_manager = ModelManager(configer) self.test_loader = TestDataLoader(configer) self.roi_sampler = FRROISampler(configer) self.rpn_target_generator = RPNTargetAssigner(configer) self.fr_priorbox_layer = FRPriorBoxLayer(configer) self.fr_roi_generator = FRROIGenerator(configer) self.device = torch.device('cpu' if self.configer.get('gpu') is None else 'cuda') self.det_net = None self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.pose_visualizer = PoseVisualizer(configer) self.pose_parser = PoseParser(configer) self.pose_model_manager = PoseModelManager(configer) self.pose_data_loader = PoseDataLoader(configer) self.module_utilizer = ModuleUtilizer(configer) self.heatmap_generator = HeatmapGenerator(configer) self.paf_generator = PafGenerator(configer) self.data_transformer = DataTransformer(configer) self.device = torch.device( 'cpu' if self.configer.get('gpu') is None else 'cuda') self.pose_net = None self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.cls_model_manager = ClsModelManager(configer) self.cls_data_loader = ClsDataLoader(configer) self.module_utilizer = ModuleUtilizer(configer) self.cls_parser = ClsParser(configer) self.device = torch.device('cpu' if self.configer.get('gpu') is None else 'cuda') self.cls_net = None if self.configer.get('dataset') == 'imagenet': with open(os.path.join(self.configer.get('project_dir'), 'datasets/cls/imagenet/imagenet_class_index.json')) as json_stream: name_dict = json.load(json_stream) name_seq = [name_dict[str(i)][1] for i in range(self.configer.get('data', 'num_classes'))] self.configer.add_key_value(['details', 'name_seq'], name_seq) self._init_model()
def __init__(self, configer): self.configer = configer self.blob_helper = BlobHelper(configer) self.det_visualizer = DetVisualizer(configer) self.det_parser = DetParser(configer) self.det_model_manager = DetModelManager(configer) self.det_data_loader = DetDataLoader(configer) self.roi_sampler = FRRoiSampleLayer(configer) self.module_utilizer = ModuleUtilizer(configer) self.rpn_target_generator = RPNTargetGenerator(configer) self.fr_priorbox_layer = FRPriorBoxLayer(configer) self.fr_roi_generator = FRRoiGenerator(configer) self.data_transformer = DataTransformer(configer) self.device = torch.device( 'cpu' if self.configer.get('gpu') is None else 'cuda') self.det_net = None self._init_model()