`Model` typehints Docker fix (#8306)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

.github/workflows/ci.yaml

@@ -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

docker/Dockerfile

@@ -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

ultralytics/engine/exporter.py

@@ -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",

ultralytics/engine/model.py

@@ -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,