diff --git a/pyproject.toml b/pyproject.toml index ec50902..b5f7e02 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "YOEO" -version = "1.4.1" +version = "1.4.3" description = "A hybrid CNN for object detection and semantic segmentation" authors = ["Florian Vahl ", "Jan Gutsche "] diff --git a/yoeo/detect.py b/yoeo/detect.py index 18ecaf5..d223d2e 100755 --- a/yoeo/detect.py +++ b/yoeo/detect.py @@ -105,8 +105,8 @@ def detect_image(model, DEFAULT_TRANSFORMS, Resize(img_size)])(( image, - np.empty((1, 5)), - np.empty((img_size, img_size), dtype=np.uint8)))[0].unsqueeze(0) + np.zeros((1, 5)), + np.zeros((img_size, img_size), dtype=np.uint8)))[0].unsqueeze(0) if torch.cuda.is_available(): input_img = input_img.to("cuda") diff --git a/yoeo/scripts/convertONNXModelToTVM.py b/yoeo/scripts/convertONNXModelToTVM.py index e39b7de..3dfd70d 100644 --- a/yoeo/scripts/convertONNXModelToTVM.py +++ b/yoeo/scripts/convertONNXModelToTVM.py @@ -26,7 +26,6 @@ def make_parser(): type=int, help="Input image size") parser.add_argument( - "-t", "--trials", default=20000, type=int, @@ -56,7 +55,6 @@ def make_parser(): type=str, help="Path to the tuning records that are created for this optimization") parser.add_argument( - "-t", "--target", default="vulkan -from_device=0", type=str, @@ -89,7 +87,7 @@ def run(): # Build an TVM Compiler model tvmc_model = TVMCModel(mod, params) - + # Tune the model (depending on the hardware and parameters this takes days) if not args.no_tuning: tvmc.tune(