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Model typehints Docker fix (#8306)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-02-19 20:29:46 +01:00 committed by GitHub
parent e4a62f99f7
commit 7f0d5ef9d7
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4 changed files with 8 additions and 8 deletions
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2
.github/workflows/ci.yaml vendored
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@ -113,7 +113,7 @@ jobs:
run: |
python -m pip install --upgrade pip wheel
pip install -e ".[export]" "coverage[toml]" --extra-index-url https://download.pytorch.org/whl/cpu
yolo export format=tflite imgsz=32 || true
# yolo export format=tflite imgsz=32 || true
- name: Check environment
run: |
yolo checks

3
docker/Dockerfile
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@ -33,7 +33,8 @@ RUN python3 -m pip install --upgrade pip wheel
RUN pip install --no-cache -e ".[export]" albumentations comet pycocotools
# Run exports to AutoInstall packages
RUN yolo export model=tmp/yolov8n.pt format=edgetpu imgsz=32
# Edge TPU export fails the first time so is run twice here
RUN yolo export model=tmp/yolov8n.pt format=edgetpu imgsz=32 || yolo export model=tmp/yolov8n.pt format=edgetpu imgsz=32
RUN yolo export model=tmp/yolov8n.pt format=ncnn imgsz=32
# Requires <= Python 3.10, bug with paddlepaddle==2.5.0 https://github.com/PaddlePaddle/X2Paddle/issues/991
RUN pip install --no-cache paddlepaddle>=2.6.0 x2paddle

2
ultralytics/engine/exporter.py
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@ -716,7 +716,7 @@ class Exporter:
import tensorflow as tf # noqa
check_requirements(
(
"onnx",
"onnx>=1.12.0",
"onnx2tf>=1.15.4,<=1.17.5",
"sng4onnx>=1.0.1",
"onnxsim>=0.4.33",

9
ultralytics/engine/model.py
View File

@ -5,7 +5,6 @@ import sys
from pathlib import Path
from typing import Union
import PIL
import numpy as np
import torch
@ -146,7 +145,7 @@ class Model(nn.Module):
def __call__(
self,
source: Union[str, Path, int, list, tuple, PIL.Image.Image, np.ndarray, torch.Tensor] = None,
source: Union[str, Path, int, list, tuple, np.ndarray, torch.Tensor] = None,
stream: bool = False,
**kwargs,
) -> list:
@ -345,7 +344,7 @@ class Model(nn.Module):
def embed(
self,
source: Union[str, Path, int, list, tuple, PIL.Image.Image, np.ndarray, torch.Tensor] = None,
source: Union[str, Path, int, list, tuple, np.ndarray, torch.Tensor] = None,
stream: bool = False,
**kwargs,
) -> list:
@ -373,7 +372,7 @@ class Model(nn.Module):
def predict(
self,
source: Union[str, Path, int, list, tuple, PIL.Image.Image, np.ndarray, torch.Tensor] = None,
source: Union[str, Path, int, list, tuple, np.ndarray, torch.Tensor] = None,
stream: bool = False,
predictor=None,
**kwargs,
@ -431,7 +430,7 @@ class Model(nn.Module):
def track(
self,
source: Union[str, Path, int, list, tuple, PIL.Image.Image, np.ndarray, torch.Tensor] = None,
source: Union[str, Path, int, list, tuple, np.ndarray, torch.Tensor] = None,
stream: bool = False,
persist: bool = False,
**kwargs,