Python源码示例：detectron.utils.vis.convert_from_cls_format()
示例1
def run_model_cfg(args, im, check_blobs):
workspace.ResetWorkspace()
model, _ = load_model(args)
with c2_utils.NamedCudaScope(0):
cls_boxes, cls_segms, cls_keyps = test_engine.im_detect_all(
model, im, None, None,
)
boxes, segms, keypoints, classes = vis_utils.convert_from_cls_format(
cls_boxes, cls_segms, cls_keyps)
# sort the results based on score for comparision
boxes, segms, keypoints, classes = _sort_results(
boxes, segms, keypoints, classes)
# write final results back to workspace
def _ornone(res):
return np.array(res) if res is not None else np.array([], dtype=np.float32)
with c2_utils.NamedCudaScope(0):
workspace.FeedBlob(core.ScopedName('result_boxes'), _ornone(boxes))
workspace.FeedBlob(core.ScopedName('result_segms'), _ornone(segms))
workspace.FeedBlob(core.ScopedName('result_keypoints'), _ornone(keypoints))
workspace.FeedBlob(core.ScopedName('result_classids'), _ornone(classes))
# get result blobs
with c2_utils.NamedCudaScope(0):
ret = _get_result_blobs(check_blobs)
return ret
示例2
def run_model_cfg(args, im, check_blobs):
workspace.ResetWorkspace()
model, _ = load_model(args)
with c2_utils.NamedCudaScope(0):
cls_boxes, cls_segms, cls_keyps = test_engine.im_detect_all(
model, im, None, None,
)
boxes, segms, keypoints, classes = vis_utils.convert_from_cls_format(
cls_boxes, cls_segms, cls_keyps)
# sort the results based on score for comparision
boxes, segms, keypoints, classes = _sort_results(
boxes, segms, keypoints, classes)
# write final results back to workspace
def _ornone(res):
return np.array(res) if res is not None else np.array([], dtype=np.float32)
with c2_utils.NamedCudaScope(0):
workspace.FeedBlob(core.ScopedName('result_boxes'), _ornone(boxes))
workspace.FeedBlob(core.ScopedName('result_segms'), _ornone(segms))
workspace.FeedBlob(core.ScopedName('result_keypoints'), _ornone(keypoints))
workspace.FeedBlob(core.ScopedName('result_classids'), _ornone(classes))
# get result blobs
with c2_utils.NamedCudaScope(0):
ret = _get_result_blobs(check_blobs)
return ret
示例3
def run_model_cfg(args, im, check_blobs):
workspace.ResetWorkspace()
model, _ = load_model(args)
with c2_utils.NamedCudaScope(0):
cls_boxes, cls_segms, cls_keyps = test_engine.im_detect_all(
model, im, None, None,
)
boxes, segms, keypoints, classes = vis_utils.convert_from_cls_format(
cls_boxes, cls_segms, cls_keyps)
# sort the results based on score for comparision
boxes, segms, keypoints, classes = _sort_results(
boxes, segms, keypoints, classes)
# write final results back to workspace
def _ornone(res):
return np.array(res) if res is not None else np.array([], dtype=np.float32)
with c2_utils.NamedCudaScope(0):
workspace.FeedBlob(core.ScopedName('result_boxes'), _ornone(boxes))
workspace.FeedBlob(core.ScopedName('result_segms'), _ornone(segms))
workspace.FeedBlob(core.ScopedName('result_keypoints'), _ornone(keypoints))
workspace.FeedBlob(core.ScopedName('result_classids'), _ornone(classes))
# get result blobs
with c2_utils.NamedCudaScope(0):
ret = _get_result_blobs(check_blobs)
return ret
示例4
def run_model_cfg(args, im, check_blobs):
workspace.ResetWorkspace()
model, _ = load_model(args)
with c2_utils.NamedCudaScope(0):
cls_boxes, cls_segms, cls_keyps = test_engine.im_detect_all(
model, im, None, None
)
boxes, segms, keypoints, classes = vis_utils.convert_from_cls_format(
cls_boxes, cls_segms, cls_keyps
)
# sort the results based on score for comparision
boxes, segms, keypoints, classes = _sort_results(boxes, segms, keypoints, classes)
# write final results back to workspace
def _ornone(res):
return np.array(res) if res is not None else np.array([], dtype=np.float32)
with c2_utils.NamedCudaScope(0):
workspace.FeedBlob(core.ScopedName("result_boxes"), _ornone(boxes))
workspace.FeedBlob(core.ScopedName("result_segms"), _ornone(segms))
workspace.FeedBlob(core.ScopedName("result_keypoints"), _ornone(keypoints))
workspace.FeedBlob(core.ScopedName("result_classids"), _ornone(classes))
# get result blobs
with c2_utils.NamedCudaScope(0):
ret = _get_result_blobs(check_blobs)
return ret
示例5
def run_model_cfg(args, im, check_blobs):
workspace.ResetWorkspace()
model, _ = load_model(args)
with c2_utils.NamedCudaScope(0):
cls_boxes, cls_segms, cls_keyps = test_engine.im_detect_all(
model, im, None, None,
)
boxes, segms, keypoints, classes = vis_utils.convert_from_cls_format(
cls_boxes, cls_segms, cls_keyps)
# sort the results based on score for comparision
boxes, segms, keypoints, classes = _sort_results(
boxes, segms, keypoints, classes)
# write final results back to workspace
def _ornone(res):
return np.array(res) if res is not None else np.array([], dtype=np.float32)
with c2_utils.NamedCudaScope(0):
workspace.FeedBlob(core.ScopedName('result_boxes'), _ornone(boxes))
workspace.FeedBlob(core.ScopedName('result_segms'), _ornone(segms))
workspace.FeedBlob(core.ScopedName('result_keypoints'), _ornone(keypoints))
workspace.FeedBlob(core.ScopedName('result_classids'), _ornone(classes))
# get result blobs
with c2_utils.NamedCudaScope(0):
ret = _get_result_blobs(check_blobs)
return ret
示例6
def run_model_cfg(args, im, check_blobs):
workspace.ResetWorkspace()
model, _ = load_model(args)
with c2_utils.NamedCudaScope(0):
cls_boxes, cls_segms, cls_keyps = test_engine.im_detect_all(
model, im, None, None,
)
boxes, segms, keypoints, classes = vis_utils.convert_from_cls_format(
cls_boxes, cls_segms, cls_keyps)
# sort the results based on score for comparision
boxes, segms, keypoints, classes = _sort_results(
boxes, segms, keypoints, classes)
# write final results back to workspace
def _ornone(res):
return np.array(res) if res is not None else np.array([], dtype=np.float32)
with c2_utils.NamedCudaScope(0):
workspace.FeedBlob(core.ScopedName('result_boxes'), _ornone(boxes))
workspace.FeedBlob(core.ScopedName('result_segms'), _ornone(segms))
workspace.FeedBlob(core.ScopedName('result_keypoints'), _ornone(keypoints))
workspace.FeedBlob(core.ScopedName('result_classids'), _ornone(classes))
# get result blobs
with c2_utils.NamedCudaScope(0):
ret = _get_result_blobs(check_blobs)
return ret
