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@ -50,7 +50,6 @@ TensorFlow.js:
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"""
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"""
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import json
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import json
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import os
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import os
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import platform
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import shutil
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import shutil
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import subprocess
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import subprocess
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import time
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import time
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@ -64,7 +63,7 @@ from ultralytics.nn.autobackend import check_class_names
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from ultralytics.nn.modules import C2f, Detect, RTDETRDecoder
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from ultralytics.nn.modules import C2f, Detect, RTDETRDecoder
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from ultralytics.nn.tasks import DetectionModel, SegmentationModel
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from ultralytics.nn.tasks import DetectionModel, SegmentationModel
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from ultralytics.yolo.cfg import get_cfg
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from ultralytics.yolo.cfg import get_cfg
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from ultralytics.yolo.utils import (DEFAULT_CFG, LINUX, LOGGER, MACOS, ROOT, __version__, callbacks, colorstr,
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from ultralytics.yolo.utils import (ARM64, DEFAULT_CFG, LINUX, LOGGER, MACOS, ROOT, __version__, callbacks, colorstr,
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get_default_args, yaml_save)
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get_default_args, yaml_save)
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from ultralytics.yolo.utils.checks import check_imgsz, check_requirements, check_version
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from ultralytics.yolo.utils.checks import check_imgsz, check_requirements, check_version
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from ultralytics.yolo.utils.downloads import attempt_download_asset, get_github_assets
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from ultralytics.yolo.utils.downloads import attempt_download_asset, get_github_assets
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@ -72,8 +71,6 @@ from ultralytics.yolo.utils.files import file_size
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from ultralytics.yolo.utils.ops import Profile
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from ultralytics.yolo.utils.ops import Profile
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from ultralytics.yolo.utils.torch_utils import get_latest_opset, select_device, smart_inference_mode
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from ultralytics.yolo.utils.torch_utils import get_latest_opset, select_device, smart_inference_mode
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ARM64 = platform.machine() in ('arm64', 'aarch64')
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def export_formats():
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def export_formats():
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"""YOLOv8 export formats."""
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"""YOLOv8 export formats."""
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@ -170,7 +167,8 @@ class Exporter:
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assert not self.args.dynamic, 'half=True not compatible with dynamic=True, i.e. use only one.'
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assert not self.args.dynamic, 'half=True not compatible with dynamic=True, i.e. use only one.'
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self.imgsz = check_imgsz(self.args.imgsz, stride=model.stride, min_dim=2) # check image size
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self.imgsz = check_imgsz(self.args.imgsz, stride=model.stride, min_dim=2) # check image size
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if self.args.optimize:
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if self.args.optimize:
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assert self.device.type == 'cpu', '--optimize not compatible with cuda devices, i.e. use --device cpu'
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assert not ncnn, "optimize=True not compatible with format='ncnn', i.e. use optimize=False"
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assert self.device.type == 'cpu', "optimize=True not compatible with cuda devices, i.e. use device='cpu'"
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if edgetpu and not LINUX:
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if edgetpu and not LINUX:
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raise SystemError('Edge TPU export only supported on Linux. See https://coral.ai/docs/edgetpu/compiler/')
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raise SystemError('Edge TPU export only supported on Linux. See https://coral.ai/docs/edgetpu/compiler/')
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@ -405,7 +403,7 @@ class Exporter:
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"""
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"""
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YOLOv8 NCNN export using PNNX https://github.com/pnnx/pnnx.
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YOLOv8 NCNN export using PNNX https://github.com/pnnx/pnnx.
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"""
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"""
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check_requirements('ncnn') # requires NCNN
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check_requirements('git+https://github.com/Tencent/ncnn.git' if ARM64 else 'ncnn') # requires NCNN
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import ncnn # noqa
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import ncnn # noqa
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LOGGER.info(f'\n{prefix} starting export with NCNN {ncnn.__version__}...')
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LOGGER.info(f'\n{prefix} starting export with NCNN {ncnn.__version__}...')
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Glenn Jocher
1 year ago
committed by
GitHub