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Edge TPU export table fix (#13420)

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pull/13380/head^2
Burhan 8 months ago committed by GitHub
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commit 11a2ed1e83
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10 changed files with 12 additions and 9 deletions
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  1. 2
      docs/en/integrations/index.md
  2. 2
      docs/en/modes/benchmark.md
  3. 2
      docs/en/modes/export.md
  4. 2
      docs/en/tasks/classify.md
  5. 2
      docs/en/tasks/detect.md
  6. 2
      docs/en/tasks/obb.md
  7. 2
      docs/en/tasks/pose.md
  8. 2
      docs/en/tasks/segment.md
  9. 2
      docs/en/usage/cli.md
  10. 3
      ultralytics/engine/exporter.py

2
docs/en/integrations/index.md
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@ -96,7 +96,7 @@ We also support a variety of model export formats for deployment in different en
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/modes/benchmark.md
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@ -98,7 +98,7 @@ Benchmarks will attempt to run automatically on all possible export formats belo
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/modes/export.md
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@ -106,7 +106,7 @@ Available YOLOv8 export formats are in the table below. You can export to any fo
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/tasks/classify.md
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@ -173,7 +173,7 @@ Available YOLOv8-cls export formats are in the table below. You can export to an
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n-cls_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n-cls.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n-cls.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-cls_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-cls_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n-cls_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n-cls_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n-cls_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/tasks/detect.md
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@ -174,7 +174,7 @@ Available YOLOv8 export formats are in the table below. You can export to any fo
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/tasks/obb.md
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@ -195,7 +195,7 @@ Available YOLOv8-obb export formats are in the table below. You can export to an
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n-obb_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n-obb.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n-obb.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-obb_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-obb_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n-obb_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n-obb_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n-obb_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/tasks/pose.md
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@ -189,7 +189,7 @@ Available YOLOv8-pose export formats are in the table below. You can export to a
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n-pose_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n-pose.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n-pose.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-pose_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-pose_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n-pose_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n-pose_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n-pose_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/tasks/segment.md
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@ -179,7 +179,7 @@ Available YOLOv8-seg export formats are in the table below. You can export to an
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n-seg_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n-seg.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n-seg.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-seg_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n-seg_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n-seg_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n-seg_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n-seg_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

2
docs/en/usage/cli.md
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@ -181,7 +181,7 @@ Available YOLOv8 export formats are in the table below. You can export to any fo
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `yolov8n_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `yolov8n.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `yolov8n.tflite` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `yolov8n_web_model/` | ✅ | `imgsz`, `half`, `int8`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz`, `batch` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |

3
ultralytics/engine/exporter.py
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@ -211,6 +211,9 @@ class Exporter:
assert self.device.type == "cpu", "optimize=True not compatible with cuda devices, i.e. use device='cpu'"
if edgetpu and not LINUX:
raise SystemError("Edge TPU export only supported on Linux. See https://coral.ai/docs/edgetpu/compiler/")
elif edgetpu and self.args.batch != 1: # see github.com/ultralytics/ultralytics/pull/13420
LOGGER.warning("WARNING ⚠️ Edge TPU export requires batch size 1, setting batch=1.")
self.args.batch = 1
if isinstance(model, WorldModel):
LOGGER.warning(
"WARNING ⚠️ YOLOWorld (original version) export is not supported to any format.\n"

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