diff --git a/README.md b/README.md index fbb74d4c..72c72144 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # [YOLOv10: Real-Time End-to-End Object Detection](https://arxiv.org/abs/2405.14458) -Official PyTorch implementation of **YOLOv10**. +Official PyTorch implementation of **YOLOv10**. NeurIPS 2024.

diff --git a/docker/Dockerfile b/docker/Dockerfile index b96173ee..f6ef8b45 100644 --- a/docker/Dockerfile +++ b/docker/Dockerfile @@ -14,7 +14,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \ # Install linux packages # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package RUN apt update \ - && apt install --no-install-recommends -y gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 + && apt install --no-install-recommends -y gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 build-essential # Security updates # https://security.snyk.io/vuln/SNYK-UBUNTU1804-OPENSSL-3314796 diff --git a/docs/en/modes/export.md b/docs/en/modes/export.md index 5859b18b..1b0827ad 100644 --- a/docs/en/modes/export.md +++ b/docs/en/modes/export.md @@ -83,7 +83,7 @@ This table details the configurations and options available for exporting YOLO m | `half` | `bool` | `False` | Enables FP16 (half-precision) quantization, reducing model size and potentially speeding up inference on supported hardware. | | `int8` | `bool` | `False` | Activates INT8 quantization, further compressing the model and speeding up inference with minimal accuracy loss, primarily for edge devices. | | `dynamic` | `bool` | `False` | Allows dynamic input sizes for ONNX and TensorRT exports, enhancing flexibility in handling varying image dimensions. | -| `simplify` | `bool` | `False` | Simplifies the model graph for ONNX exports, potentially improving performance and compatibility. | +| `simplify` | `bool` | `False` | Simplifies the model graph for ONNX exports with `onnxsim`, potentially improving performance and compatibility. | | `opset` | `int` | `None` | Specifies the ONNX opset version for compatibility with different ONNX parsers and runtimes. If not set, uses the latest supported version. | | `workspace` | `float` | `4.0` | Sets the maximum workspace size in GB for TensorRT optimizations, balancing memory usage and performance. | | `nms` | `bool` | `False` | Adds Non-Maximum Suppression (NMS) to the CoreML export, essential for accurate and efficient detection post-processing. | diff --git a/requirements.txt b/requirements.txt index 680357a7..019d1ae4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -5,7 +5,7 @@ onnxruntime==1.15.1 pycocotools==2.0.7 PyYAML==6.0.1 scipy==1.13.0 -onnxsim==0.4.36 +onnxslim==0.1.31 gradio==4.31.5 opencv-python==4.9.0.80 psutil==5.9.8 diff --git a/ultralytics/cfg/default.yaml b/ultralytics/cfg/default.yaml index bc64897e..bd074b10 100644 --- a/ultralytics/cfg/default.yaml +++ b/ultralytics/cfg/default.yaml @@ -82,7 +82,7 @@ keras: False # (bool) use Kera=s optimize: False # (bool) TorchScript: optimize for mobile int8: False # (bool) CoreML/TF INT8 quantization dynamic: False # (bool) ONNX/TF/TensorRT: dynamic axes -simplify: False # (bool) ONNX: simplify model +simplify: False # (bool) ONNX: simplify model using `onnxslim` opset: # (int, optional) ONNX: opset version workspace: 4 # (int) TensorRT: workspace size (GB) nms: False # (bool) CoreML: add NMS diff --git a/ultralytics/engine/exporter.py b/ultralytics/engine/exporter.py index 1fa3f2e1..6ac170c5 100644 --- a/ultralytics/engine/exporter.py +++ b/ultralytics/engine/exporter.py @@ -355,9 +355,7 @@ class Exporter: """YOLOv8 ONNX export.""" requirements = ["onnx>=1.12.0"] if self.args.simplify: - requirements += ["onnxsim>=0.4.33", "onnxruntime-gpu" if torch.cuda.is_available() else "onnxruntime"] - if ARM64: - check_requirements("cmake") # 'cmake' is needed to build onnxsim on aarch64 + requirements += ["onnxslim==0.1.31", "onnxruntime" + ("-gpu" if torch.cuda.is_available() else "")] check_requirements(requirements) import onnx # noqa @@ -394,14 +392,17 @@ class Exporter: # Simplify if self.args.simplify: try: - import onnxsim + import onnxslim - LOGGER.info(f"{prefix} simplifying with onnxsim {onnxsim.__version__}...") - # subprocess.run(f'onnxsim "{f}" "{f}"', shell=True) - model_onnx, check = onnxsim.simplify(model_onnx) - assert check, "Simplified ONNX model could not be validated" + LOGGER.info(f"{prefix} simplifying with onnxslim {onnxslim.__version__}...") + model_onnx = onnxslim.slim(model_onnx) + + # ONNX Simplifier (deprecated as must be compiled with 'cmake' in aarch64 and Conda CI environments) + # import onnxsim + # model_onnx, check = onnxsim.simplify(model_onnx) + # assert check, "Simplified ONNX model could not be validated" except Exception as e: - LOGGER.info(f"{prefix} simplifier failure: {e}") + LOGGER.warning(f"{prefix} simplifier failure: {e}") # Metadata for k, v in self.metadata.items(): @@ -656,7 +657,7 @@ class Exporter: def export_engine(self, prefix=colorstr("TensorRT:")): """YOLOv8 TensorRT export https://developer.nvidia.com/tensorrt.""" assert self.im.device.type != "cpu", "export running on CPU but must be on GPU, i.e. use 'device=0'" - f_onnx, _ = self.export_onnx() # run before trt import https://github.com/ultralytics/ultralytics/issues/7016 + f_onnx, _ = self.export_onnx() # run before TRT import https://github.com/ultralytics/ultralytics/issues/7016 try: import tensorrt as trt # noqa @@ -741,7 +742,7 @@ class Exporter: "onnx>=1.12.0", "onnx2tf>=1.15.4,<=1.17.5", "sng4onnx>=1.0.1", - "onnxsim>=0.4.33", + "onnxslim==0.1.31", "onnx_graphsurgeon>=0.3.26", "tflite_support", "flatbuffers>=23.5.26,<100", # update old 'flatbuffers' included inside tensorflow package diff --git a/ultralytics/nn/modules/__init__.py b/ultralytics/nn/modules/__init__.py index 4a99bf59..7f4c4fed 100644 --- a/ultralytics/nn/modules/__init__.py +++ b/ultralytics/nn/modules/__init__.py @@ -13,7 +13,7 @@ Example: m = Conv(128, 128) f = f'{m._get_name()}.onnx' torch.onnx.export(m, x, f) - os.system(f'onnxsim {f} {f} && open {f}') + os.system(f'onnxslim {f} {f} && open {f}') # pip install onnxslim ``` """ diff --git a/ultralytics/utils/benchmarks.py b/ultralytics/utils/benchmarks.py index 3bc63510..02869906 100644 --- a/ultralytics/utils/benchmarks.py +++ b/ultralytics/utils/benchmarks.py @@ -323,6 +323,8 @@ class ProfileModels: input_tensor = sess.get_inputs()[0] input_type = input_tensor.type + dynamic = not all(isinstance(dim, int) and dim >= 0 for dim in input_tensor.shape) # dynamic input shape + input_shape = (1, 3, self.imgsz, self.imgsz) if dynamic else input_tensor.shape # Mapping ONNX datatype to numpy datatype if "float16" in input_type: @@ -338,7 +340,7 @@ class ProfileModels: else: raise ValueError(f"Unsupported ONNX datatype {input_type}") - input_data = np.random.rand(*input_tensor.shape).astype(input_dtype) + input_data = np.random.rand(*input_shape).astype(input_dtype) input_name = input_tensor.name output_name = sess.get_outputs()[0].name