mv get_gpu_id func to utility

tools/infer/predict_det.py

@@ -101,7 +101,7 @@ def __init__(self, args):
  if args.benchmark:
  import auto_log
  pid = os.getpid()
- gpu_id = self.get_infer_gpuid()
+ gpu_id = utility.get_infer_gpuid()
  self.autolog = auto_log.AutoLogger(
  model_name="det",
  model_precision=args.precision,
@@ -118,19 +118,6 @@ def __init__(self, args):
  warmup=2,
  logger=logger)
 
- def get_infer_gpuid(self):
- cmd = "nvidia-smi"
- res = os.popen(cmd).readlines()
- if len(res) == 0:
- return None
- cmd = "env | grep CUDA_VISIBLE_DEVICES"
- env_cuda = os.popen(cmd).readlines()
- if len(env_cuda) == 0:
- return 0
- else:
- gpu_id = env_cuda[0].strip().split("=")[1]
- return int(gpu_id[0])
-
  def order_points_clockwise(self, pts):
  """
  reference from: https://github.com/jrosebr1/imutils/blob/master/imutils/perspective.py

tools/infer/utility.py

@@ -280,6 +280,20 @@ def create_predictor(args, mode, logger):
  return predictor, input_tensor, output_tensors, config
 
 
+def get_infer_gpuid():
+ cmd = "nvidia-smi"
+ res = os.popen(cmd).readlines()
+ if len(res) == 0:
+ return None
+ cmd = "env | grep CUDA_VISIBLE_DEVICES"
+ env_cuda = os.popen(cmd).readlines()
+ if len(env_cuda) == 0:
+ return 0
+ else:
+ gpu_id = env_cuda[0].strip().split("=")[1]
+ return int(gpu_id[0])
+
+
 def draw_e2e_res(dt_boxes, strs, img_path):
  src_im = cv2.imread(img_path)
  for box, str in zip(dt_boxes, strs):