Python dummy_datasets.get_coco_dataset方法代碼示例

本文整理匯總了Python中datasets.dummy_datasets.get_coco_dataset方法的典型用法代碼示例。如果您正苦於以下問題：Python dummy_datasets.get_coco_dataset方法的具體用法？Python dummy_datasets.get_coco_dataset怎麽用？Python dummy_datasets.get_coco_dataset使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類datasets.dummy_datasets的用法示例。

在下文中一共展示了dummy_datasets.get_coco_dataset方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: main

# 需要導入模塊: from datasets import dummy_datasets [as 別名]
# 或者: from datasets.dummy_datasets import get_coco_dataset [as 別名]
def main(args):
    logger = logging.getLogger(__name__)
    merge_cfg_from_file(args.cfg)
    cfg.NUM_GPUS = 1
    args.weights = cache_url(args.weights, cfg.DOWNLOAD_CACHE)
    assert_and_infer_cfg(cache_urls=False)
    model = infer_engine.initialize_model_from_cfg(args.weights)
    dummy_coco_dataset = (
        dummy_datasets.get_vg3k_dataset()
        if args.use_vg3k else dummy_datasets.get_coco_dataset())

    if os.path.isdir(args.im_or_folder):
        im_list = glob.iglob(args.im_or_folder + '/*.' + args.image_ext)
    else:
        im_list = [args.im_or_folder]

    for i, im_name in enumerate(im_list):
        out_name = os.path.join(
            args.output_dir, '{}'.format(os.path.basename(im_name) + '.pdf')
        )
        logger.info('Processing {} -> {}'.format(im_name, out_name))
        im = cv2.imread(im_name)
        timers = defaultdict(Timer)
        t = time.time()
        with c2_utils.NamedCudaScope(0):
            cls_boxes, cls_segms, cls_keyps = infer_engine.im_detect_all(
                model, im, None, timers=timers
            )
        logger.info('Inference time: {:.3f}s'.format(time.time() - t))
        for k, v in timers.items():
            logger.info(' | {}: {:.3f}s'.format(k, v.average_time))
        if i == 0:
            logger.info(
                ' \ Note: inference on the first image will be slower than the '
                'rest (caches and auto-tuning need to warm up)'
            )

        vis_utils.vis_one_image(
            im[:, :, ::-1],  # BGR -> RGB for visualization
            im_name,
            args.output_dir,
            cls_boxes,
            cls_segms,
            cls_keyps,
            dataset=dummy_coco_dataset,
            box_alpha=0.3,
            show_class=True,
            thresh=args.thresh,
            kp_thresh=2
        )

開發者ID:ronghanghu，項目名稱:seg_every_thing，代碼行數:52，代碼來源:infer_simple.py

示例2: main

# 需要導入模塊: from datasets import dummy_datasets [as 別名]
# 或者: from datasets.dummy_datasets import get_coco_dataset [as 別名]
def main(args):
    logger = logging.getLogger(__name__)
    dummy_coco_dataset = (
        dummy_datasets.get_vg3k_dataset()
        if args.use_vg3k else dummy_datasets.get_coco_dataset())
    cfg_orig = yaml.load(yaml.dump(cfg))
    im = cv2.imread(args.im_file)

    if args.rpn_pkl is not None:
        proposal_boxes, _proposal_scores = get_rpn_box_proposals(im, args)
        workspace.ResetWorkspace()
    else:
        proposal_boxes = None

    cls_boxes, cls_segms, cls_keyps = None, None, None
    for i in range(0, len(args.models_to_run), 2):
        pkl = args.models_to_run[i]
        yml = args.models_to_run[i + 1]
        cfg.immutable(False)
        merge_cfg_from_cfg(cfg_orig)
        merge_cfg_from_file(yml)
        if len(pkl) > 0:
            weights_file = pkl
        else:
            weights_file = cfg.TEST.WEIGHTS
        cfg.NUM_GPUS = 1
        assert_and_infer_cfg(cache_urls=False)
        model = model_engine.initialize_model_from_cfg(weights_file)
        with c2_utils.NamedCudaScope(0):
            cls_boxes_, cls_segms_, cls_keyps_ = \
                model_engine.im_detect_all(model, im, proposal_boxes)
        cls_boxes = cls_boxes_ if cls_boxes_ is not None else cls_boxes
        cls_segms = cls_segms_ if cls_segms_ is not None else cls_segms
        cls_keyps = cls_keyps_ if cls_keyps_ is not None else cls_keyps
        workspace.ResetWorkspace()

    out_name = os.path.join(
        args.output_dir, '{}'.format(os.path.basename(args.im_file) + '.pdf')
    )
    logger.info('Processing {} -> {}'.format(args.im_file, out_name))

    vis_utils.vis_one_image(
        im[:, :, ::-1],
        args.im_file,
        args.output_dir,
        cls_boxes,
        cls_segms,
        cls_keyps,
        dataset=dummy_coco_dataset,
        box_alpha=0.3,
        show_class=True,
        thresh=args.thresh,
        kp_thresh=2
    )

開發者ID:ronghanghu，項目名稱:seg_every_thing，代碼行數:56，代碼來源:infer.py

示例3: main

# 需要導入模塊: from datasets import dummy_datasets [as 別名]
# 或者: from datasets.dummy_datasets import get_coco_dataset [as 別名]
def main(args):
    logger = logging.getLogger(__name__)
    merge_cfg_from_file(args.cfg)
    cfg.TEST.WEIGHTS = args.weights
    cfg.NUM_GPUS = 1
    assert_and_infer_cfg()
    model = infer_engine.initialize_model_from_cfg()
    dummy_coco_dataset = dummy_datasets.get_coco_dataset()

    if os.path.isdir(args.im_or_folder):
        im_list = glob.iglob(args.im_or_folder + '/*.' + args.image_ext)
    else:
        im_list = [args.im_or_folder]

    for i, im_name in enumerate(im_list):
        out_name = os.path.join(
            args.output_dir, '{}'.format(os.path.basename(im_name) + '.pdf')
        )
        logger.info('Processing {} -> {}'.format(im_name, out_name))
        im = cv2.imread(im_name)
        timers = defaultdict(Timer)
        t = time.time()
        with c2_utils.NamedCudaScope(0):
            cls_boxes, cls_segms, cls_keyps = infer_engine.im_detect_all(
                model, im, None, timers=timers
            )
        logger.info('Inference time: {:.3f}s'.format(time.time() - t))
        for k, v in timers.items():
            logger.info(' | {}: {:.3f}s'.format(k, v.average_time))
        if i == 0:
            logger.info(
                ' \ Note: inference on the first image will be slower than the '
                'rest (caches and auto-tuning need to warm up)'
            )

        vis_utils.vis_one_image(
            im[:, :, ::-1],  # BGR -> RGB for visualization
            im_name,
            args.output_dir,
            cls_boxes,
            cls_segms,
            cls_keyps,
            dataset=dummy_coco_dataset,
            box_alpha=0.3,
            show_class=True,
            thresh=0.7,
            kp_thresh=2
        )

開發者ID:lvpengyuan，項目名稱:masktextspotter.caffe2，代碼行數:50，代碼來源:infer_simple.py

示例4: main

# 需要導入模塊: from datasets import dummy_datasets [as 別名]
# 或者: from datasets.dummy_datasets import get_coco_dataset [as 別名]
def main(args):
    dummy_coco_dataset = dummy_datasets.get_coco_dataset()
    cfg_orig = yaml.load(yaml.dump(cfg))
    im = cv2.imread(args.im_file)

    if args.rpn_pkl is not None:
        proposal_boxes, _proposal_scores = get_rpn_box_proposals(im, args)
        workspace.ResetWorkspace()
    else:
        proposal_boxes = None

    cls_boxes, cls_segms, cls_keyps = None, None, None
    for i in range(0, len(args.models_to_run), 2):
        pkl = args.models_to_run[i]
        yml = args.models_to_run[i + 1]
        merge_cfg_from_cfg(cfg_orig)
        merge_cfg_from_file(yml)
        if len(pkl) > 0:
            cfg.TEST.WEIGHTS = pkl
        cfg.NUM_GPUS = 1
        assert_and_infer_cfg()
        model = model_engine.initialize_model_from_cfg()
        with c2_utils.NamedCudaScope(0):
            cls_boxes_, cls_segms_, cls_keyps_ = \
                model_engine.im_detect_all(model, im, proposal_boxes)
        cls_boxes = cls_boxes_ if cls_boxes_ is not None else cls_boxes
        cls_segms = cls_segms_ if cls_segms_ is not None else cls_segms
        cls_keyps = cls_keyps_ if cls_keyps_ is not None else cls_keyps
        workspace.ResetWorkspace()

    vis_utils.vis_one_image(
        im[:, :, ::-1],
        args.im_file,
        args.output_dir,
        cls_boxes,
        cls_segms,
        cls_keyps,
        dataset=dummy_coco_dataset,
        box_alpha=0.3,
        show_class=True,
        thresh=0.7,
        kp_thresh=2
    )

開發者ID:lvpengyuan，項目名稱:masktextspotter.caffe2，代碼行數:45，代碼來源:infer.py

注：本文中的datasets.dummy_datasets.get_coco_dataset方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。