ultralytics 8.3.11 suppress onnx2tf INT8-FP16 act error (#16874)
Signed-off-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher
GitHub
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2 changed files with 48 additions and 51 deletions
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@ -1,6 +1,6 @@
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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__version__ = "8.3.10"
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__version__ = "8.3.11"
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import os
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@ -1,52 +1,52 @@
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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"""
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Export a YOLOv8 PyTorch model to other formats. TensorFlow exports authored by https://github.com/zldrobit.
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Export a YOLO PyTorch model to other formats. TensorFlow exports authored by https://github.com/zldrobit.
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Format | `format=argument` | Model
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--- | --- | ---
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PyTorch | - | yolov8n.pt
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TorchScript | `torchscript` | yolov8n.torchscript
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ONNX | `onnx` | yolov8n.onnx
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OpenVINO | `openvino` | yolov8n_openvino_model/
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TensorRT | `engine` | yolov8n.engine
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CoreML | `coreml` | yolov8n.mlpackage
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TensorFlow SavedModel | `saved_model` | yolov8n_saved_model/
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TensorFlow GraphDef | `pb` | yolov8n.pb
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TensorFlow Lite | `tflite` | yolov8n.tflite
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TensorFlow Edge TPU | `edgetpu` | yolov8n_edgetpu.tflite
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TensorFlow.js | `tfjs` | yolov8n_web_model/
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PaddlePaddle | `paddle` | yolov8n_paddle_model/
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NCNN | `ncnn` | yolov8n_ncnn_model/
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PyTorch | - | yolo11n.pt
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TorchScript | `torchscript` | yolo11n.torchscript
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ONNX | `onnx` | yolo11n.onnx
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OpenVINO | `openvino` | yolo11n_openvino_model/
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TensorRT | `engine` | yolo11n.engine
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CoreML | `coreml` | yolo11n.mlpackage
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TensorFlow SavedModel | `saved_model` | yolo11n_saved_model/
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TensorFlow GraphDef | `pb` | yolo11n.pb
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TensorFlow Lite | `tflite` | yolo11n.tflite
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TensorFlow Edge TPU | `edgetpu` | yolo11n_edgetpu.tflite
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TensorFlow.js | `tfjs` | yolo11n_web_model/
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PaddlePaddle | `paddle` | yolo11n_paddle_model/
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NCNN | `ncnn` | yolo11n_ncnn_model/
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Requirements:
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$ pip install "ultralytics[export]"
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Python:
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from ultralytics import YOLO
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model = YOLO('yolov8n.pt')
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model = YOLO('yolo11n.pt')
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results = model.export(format='onnx')
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CLI:
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$ yolo mode=export model=yolov8n.pt format=onnx
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$ yolo mode=export model=yolo11n.pt format=onnx
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Inference:
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$ yolo predict model=yolov8n.pt # PyTorch
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yolov8n.torchscript # TorchScript
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yolov8n.onnx # ONNX Runtime or OpenCV DNN with dnn=True
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yolov8n_openvino_model # OpenVINO
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yolov8n.engine # TensorRT
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yolov8n.mlpackage # CoreML (macOS-only)
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yolov8n_saved_model # TensorFlow SavedModel
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yolov8n.pb # TensorFlow GraphDef
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yolov8n.tflite # TensorFlow Lite
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yolov8n_edgetpu.tflite # TensorFlow Edge TPU
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yolov8n_paddle_model # PaddlePaddle
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yolov8n_ncnn_model # NCNN
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$ yolo predict model=yolo11n.pt # PyTorch
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yolo11n.torchscript # TorchScript
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yolo11n.onnx # ONNX Runtime or OpenCV DNN with dnn=True
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yolo11n_openvino_model # OpenVINO
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yolo11n.engine # TensorRT
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yolo11n.mlpackage # CoreML (macOS-only)
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yolo11n_saved_model # TensorFlow SavedModel
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yolo11n.pb # TensorFlow GraphDef
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yolo11n.tflite # TensorFlow Lite
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yolo11n_edgetpu.tflite # TensorFlow Edge TPU
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yolo11n_paddle_model # PaddlePaddle
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yolo11n_ncnn_model # NCNN
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TensorFlow.js:
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$ cd .. && git clone https://github.com/zldrobit/tfjs-yolov5-example.git && cd tfjs-yolov5-example
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$ npm install
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$ ln -s ../../yolov5/yolov8n_web_model public/yolov8n_web_model
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$ ln -s ../../yolo11n_web_model public/yolo11n_web_model
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$ npm start
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"""
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@ -124,7 +124,7 @@ def gd_outputs(gd):
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def try_export(inner_func):
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"""YOLOv8 export decorator, i.e. @try_export."""
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"""YOLO export decorator, i.e. @try_export."""
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inner_args = get_default_args(inner_func)
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def outer_func(*args, **kwargs):
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@ -378,7 +378,7 @@ class Exporter:
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@try_export
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def export_torchscript(self, prefix=colorstr("TorchScript:")):
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"""YOLOv8 TorchScript model export."""
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"""YOLO TorchScript model export."""
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LOGGER.info(f"\n{prefix} starting export with torch {torch.__version__}...")
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f = self.file.with_suffix(".torchscript")
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@ -395,7 +395,7 @@ class Exporter:
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@try_export
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def export_onnx(self, prefix=colorstr("ONNX:")):
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"""YOLOv8 ONNX export."""
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"""YOLO ONNX export."""
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requirements = ["onnx>=1.12.0"]
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if self.args.simplify:
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requirements += ["onnxslim==0.1.34", "onnxruntime" + ("-gpu" if torch.cuda.is_available() else "")]
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@ -452,7 +452,7 @@ class Exporter:
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@try_export
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def export_openvino(self, prefix=colorstr("OpenVINO:")):
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"""YOLOv8 OpenVINO export."""
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"""YOLO OpenVINO export."""
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check_requirements(f'openvino{"<=2024.0.0" if ARM64 else ">=2024.0.0"}') # fix OpenVINO issue on ARM64
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import openvino as ov
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@ -466,7 +466,7 @@ class Exporter:
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def serialize(ov_model, file):
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"""Set RT info, serialize and save metadata YAML."""
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ov_model.set_rt_info("YOLOv8", ["model_info", "model_type"])
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ov_model.set_rt_info("YOLO", ["model_info", "model_type"])
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ov_model.set_rt_info(True, ["model_info", "reverse_input_channels"])
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ov_model.set_rt_info(114, ["model_info", "pad_value"])
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ov_model.set_rt_info([255.0], ["model_info", "scale_values"])
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@ -524,7 +524,7 @@ class Exporter:
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@try_export
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def export_paddle(self, prefix=colorstr("PaddlePaddle:")):
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"""YOLOv8 Paddle export."""
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"""YOLO Paddle export."""
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check_requirements(("paddlepaddle", "x2paddle"))
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import x2paddle # noqa
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from x2paddle.convert import pytorch2paddle # noqa
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@ -538,7 +538,7 @@ class Exporter:
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@try_export
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def export_ncnn(self, prefix=colorstr("NCNN:")):
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"""YOLOv8 NCNN export using PNNX https://github.com/pnnx/pnnx."""
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"""YOLO NCNN export using PNNX https://github.com/pnnx/pnnx."""
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check_requirements("ncnn")
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import ncnn # noqa
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@ -606,7 +606,7 @@ class Exporter:
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@try_export
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def export_coreml(self, prefix=colorstr("CoreML:")):
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"""YOLOv8 CoreML export."""
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"""YOLO CoreML export."""
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mlmodel = self.args.format.lower() == "mlmodel" # legacy *.mlmodel export format requested
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check_requirements("coremltools>=6.0,<=6.2" if mlmodel else "coremltools>=7.0")
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import coremltools as ct # noqa
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@ -683,7 +683,7 @@ class Exporter:
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@try_export
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def export_engine(self, prefix=colorstr("TensorRT:")):
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"""YOLOv8 TensorRT export https://developer.nvidia.com/tensorrt."""
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"""YOLO TensorRT export https://developer.nvidia.com/tensorrt."""
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assert self.im.device.type != "cpu", "export running on CPU but must be on GPU, i.e. use 'device=0'"
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f_onnx, _ = self.export_onnx() # run before TRT import https://github.com/ultralytics/ultralytics/issues/7016
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@ -817,7 +817,7 @@ class Exporter:
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@try_export
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def export_saved_model(self, prefix=colorstr("TensorFlow SavedModel:")):
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"""YOLOv8 TensorFlow SavedModel export."""
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"""YOLO TensorFlow SavedModel export."""
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cuda = torch.cuda.is_available()
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try:
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import tensorflow as tf # noqa
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@ -869,22 +869,19 @@ class Exporter:
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np_data = None
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if self.args.int8:
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tmp_file = f / "tmp_tflite_int8_calibration_images.npy" # int8 calibration images file
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verbosity = "info"
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if self.args.data:
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f.mkdir()
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images = [batch["img"].permute(0, 2, 3, 1) for batch in self.get_int8_calibration_dataloader(prefix)]
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images = torch.cat(images, 0).float()
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np.save(str(tmp_file), images.numpy().astype(np.float32)) # BHWC
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np_data = [["images", tmp_file, [[[[0, 0, 0]]]], [[[[255, 255, 255]]]]]]
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else:
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verbosity = "error"
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LOGGER.info(f"{prefix} starting TFLite export with onnx2tf {onnx2tf.__version__}...")
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onnx2tf.convert(
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keras_model = onnx2tf.convert(
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input_onnx_file_path=f_onnx,
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output_folder_path=str(f),
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not_use_onnxsim=True,
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verbosity=verbosity,
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verbosity="error", # note INT8-FP16 activation bug https://github.com/ultralytics/ultralytics/issues/15873
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output_integer_quantized_tflite=self.args.int8,
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quant_type="per-tensor", # "per-tensor" (faster) or "per-channel" (slower but more accurate)
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custom_input_op_name_np_data_path=np_data,
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@ -905,11 +902,11 @@ class Exporter:
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for file in f.rglob("*.tflite"):
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f.unlink() if "quant_with_int16_act.tflite" in str(f) else self._add_tflite_metadata(file)
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return str(f), tf.saved_model.load(f, tags=None, options=None) # load saved_model as Keras model
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return str(f), keras_model # or keras_model = tf.saved_model.load(f, tags=None, options=None)
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@try_export
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def export_pb(self, keras_model, prefix=colorstr("TensorFlow GraphDef:")):
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"""YOLOv8 TensorFlow GraphDef *.pb export https://github.com/leimao/Frozen_Graph_TensorFlow."""
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"""YOLO TensorFlow GraphDef *.pb export https://github.com/leimao/Frozen_Graph_TensorFlow."""
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import tensorflow as tf # noqa
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from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2 # noqa
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@ -925,7 +922,7 @@ class Exporter:
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@try_export
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def export_tflite(self, keras_model, nms, agnostic_nms, prefix=colorstr("TensorFlow Lite:")):
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"""YOLOv8 TensorFlow Lite export."""
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"""YOLO TensorFlow Lite export."""
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# BUG https://github.com/ultralytics/ultralytics/issues/13436
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import tensorflow as tf # noqa
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@ -941,7 +938,7 @@ class Exporter:
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@try_export
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def export_edgetpu(self, tflite_model="", prefix=colorstr("Edge TPU:")):
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"""YOLOv8 Edge TPU export https://coral.ai/docs/edgetpu/models-intro/."""
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"""YOLO Edge TPU export https://coral.ai/docs/edgetpu/models-intro/."""
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LOGGER.warning(f"{prefix} WARNING ⚠️ Edge TPU known bug https://github.com/ultralytics/ultralytics/issues/1185")
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cmd = "edgetpu_compiler --version"
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@ -971,7 +968,7 @@ class Exporter:
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@try_export
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def export_tfjs(self, prefix=colorstr("TensorFlow.js:")):
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"""YOLOv8 TensorFlow.js export."""
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"""YOLO TensorFlow.js export."""
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check_requirements("tensorflowjs")
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if ARM64:
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# Fix error: `np.object` was a deprecated alias for the builtin `object` when exporting to TF.js on ARM64
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@ -1070,7 +1067,7 @@ class Exporter:
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tmp_file.unlink()
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def _pipeline_coreml(self, model, weights_dir=None, prefix=colorstr("CoreML Pipeline:")):
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"""YOLOv8 CoreML pipeline."""
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"""YOLO CoreML pipeline."""
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import coremltools as ct # noqa
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LOGGER.info(f"{prefix} starting pipeline with coremltools {ct.__version__}...")
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