ultralytics 8.1.1 Docs, Solutions and Export updates (ultralytics#7545

)

Co-authored-by: Sergiu Waxmann <47978446+sergiuwaxmann@users.noreply.github.com>
Co-authored-by: Vivek Malvi <malvivivek8198@gmail.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: psaxton <psaxton+github.com@gmail.com>

docker/Dockerfile

@@ -34,7 +34,7 @@ RUN pip install --no-cache -e ".[export]" albumentations comet pycocotools lance
 RUN 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==2.4.2 x2paddle
+RUN pip install --no-cache paddlepaddle>=2.6.0 x2paddle
 # Fix error: `np.bool` was a deprecated alias for the builtin `bool` segmentation error in Tests
 RUN pip install --no-cache numpy==1.23.5
 # Remove exported models

docker/Dockerfile-python

@@ -32,7 +32,7 @@ RUN pip install --no-cache -e ".[export]" lancedb --extra-index-url https://down
 RUN 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==2.4.2 x2paddle
+RUN pip install --no-cache paddlepaddle>=2.6.0 x2paddle
 # Remove exported models
 RUN rm -rf tmp
 

docs/overrides/stylesheets/style.css

@@ -48,3 +48,10 @@ div.highlight {
 .md-header .md-select:hover .md-select__inner {
   max-height: 75vh;
 }
+
+/* Update the background of the banner (same as the one on the Ultralytics website) */
+.md-banner {
+  background-image: url(https://assets-global.website-files.com/646dd1f1a3703e451ba81ecc/659fc4f4163e480e7ec280d0_banner.webp);
+  background-size: cover;
+  background-position: center;
+}

pyproject.toml

@@ -98,11 +98,9 @@ dev = [
 ]
 export = [
     "onnx>=1.12.0", # ONNX export
-    "coremltools>=7.0", # CoreML export
+    "coremltools>=7.0; platform_system != 'Windows'", # CoreML only supported on macOS and Linux
     "openvino-dev>=2023.0", # OpenVINO export
     "tensorflow<=2.13.1", # TF bug https://github.com/ultralytics/ultralytics/issues/5161
-    "jax<=0.4.21", # tensorflowjs bug https://github.com/google/jax/issues/18978
-    "jaxlib<=0.4.21", # tensorflowjs bug https://github.com/google/jax/issues/18978
     "tensorflowjs>=3.9.0", # TF.js export, automatically installs tensorflow
 ]
 

tests/test_python.py

@@ -463,6 +463,21 @@ def test_utils_files():
         print(new_path)
 
 
+@pytest.mark.slow
+def test_utils_patches_torch_save():
+    """Test torch_save backoff when _torch_save throws RuntimeError."""
+    from unittest.mock import patch, MagicMock
+    from ultralytics.utils.patches import torch_save
+
+    mock = MagicMock(side_effect=RuntimeError)
+
+    with patch('ultralytics.utils.patches._torch_save', new=mock):
+        with pytest.raises(RuntimeError):
+            torch_save(torch.zeros(1), TMP / 'test.pt')
+
+    assert mock.call_count == 4, "torch_save was not attempted the expected number of times"
+
+
 def test_nn_modules_conv():
     """Test Convolutional Neural Network modules."""
     from ultralytics.nn.modules.conv import CBAM, Conv2, ConvTranspose, DWConvTranspose2d, Focus

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.1.0"
+__version__ = "8.1.1"
 
 from ultralytics.data.explorer.explorer import Explorer
 from ultralytics.models import RTDETR, SAM, YOLO

ultralytics/engine/exporter.py

@@ -555,6 +555,7 @@ def export_coreml(self, prefix=colorstr("CoreML:")):
         import coremltools as ct  # noqa
 
         LOGGER.info(f"\n{prefix} starting export with coremltools {ct.__version__}...")
+        assert not WINDOWS, "CoreML export is not supported on Windows, please run on macOS or Linux."
         f = self.file.with_suffix(".mlmodel" if mlmodel else ".mlpackage")
         if f.is_dir():
             shutil.rmtree(f)

ultralytics/solutions/object_counter.py

@@ -182,25 +182,29 @@ def extract_and_process_tracks(self, tracks):
                     track_line, color=self.track_color, track_thickness=self.track_thickness
                 )
 
+            prev_position = self.track_history[track_id][-2] if len(self.track_history[track_id]) > 1 else None
+
             # Count objects
             if len(self.reg_pts) == 4:
-                if self.counting_region.contains(Point(track_line[-1])):
-                    if track_id not in self.counting_list:
-                        self.counting_list.append(track_id)
-                        if box[0] < self.counting_region.centroid.x:
-                            self.out_counts += 1
-                        else:
-                            self.in_counts += 1
+                if prev_position is not None:
+                    if self.counting_region.contains(Point(track_line[-1])):
+                        if track_id not in self.counting_list:
+                            self.counting_list.append(track_id)
+                            if (box[0] - prev_position[0]) * (self.counting_region.centroid.x - prev_position[0]) > 0:
+                                self.in_counts += 1
+                            else:
+                                self.out_counts += 1
 
             elif len(self.reg_pts) == 2:
-                distance = Point(track_line[-1]).distance(self.counting_region)
-                if distance < self.line_dist_thresh:
-                    if track_id not in self.counting_list:
-                        self.counting_list.append(track_id)
-                        if box[0] < self.counting_region.centroid.x:
-                            self.out_counts += 1
-                        else:
-                            self.in_counts += 1
+                if prev_position is not None:
+                    distance = Point(track_line[-1]).distance(self.counting_region)
+                    if distance < self.line_dist_thresh:
+                        if track_id not in self.counting_list:
+                            self.counting_list.append(track_id)
+                            if (box[0] - prev_position[0]) * (self.counting_region.centroid.x - prev_position[0]) > 0:
+                                self.in_counts += 1
+                            else:
+                                self.out_counts += 1
 
         incount_label = "In Count : " + f"{self.in_counts}"
         outcount_label = "OutCount : " + f"{self.out_counts}"

ultralytics/utils/benchmarks.py

@@ -85,10 +85,12 @@ def benchmark(
         emoji, filename = "❌", None  # export defaults
         try:
             assert i != 9 or LINUX, "Edge TPU export only supported on Linux"
-            if i == 10:
+            if i == 5:
+                assert MACOS or LINUX, "CoreML export only supported on macOS and Linux"
+            elif i == 10:
                 assert MACOS or LINUX, "TF.js export only supported on macOS and Linux"
-            elif i == 11:
-                assert sys.version_info < (3, 11), "PaddlePaddle export only supported on Python<=3.10"
+            # elif i == 11:
+            #     assert sys.version_info < (3, 11), "PaddlePaddle export only supported on Python<=3.10"
             if "cpu" in device.type:
                 assert cpu, "inference not supported on CPU"
             if "cuda" in device.type:

ultralytics/utils/patches.py

@@ -1,6 +1,7 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 """Monkey patches to update/extend functionality of existing functions."""
 
+import time
 from pathlib import Path
 
 import cv2
@@ -61,7 +62,8 @@ def imshow(winname: str, mat: np.ndarray):
 
 def torch_save(*args, **kwargs):
     """
-    Use dill (if exists) to serialize the lambda functions where pickle does not do this.
+    Use dill (if exists) to serialize the lambda functions where pickle does not do this. Also adds 3 retries with
+    exponential standoff in case of save failure to improve robustness to transient issues.
 
     Args:
         *args (tuple): Positional arguments to pass to torch.save.
@@ -74,4 +76,11 @@ def torch_save(*args, **kwargs):
 
     if "pickle_module" not in kwargs:
         kwargs["pickle_module"] = pickle  # noqa
-    return _torch_save(*args, **kwargs)
+
+    for i in range(4):  # 3 retries
+        try:
+            return _torch_save(*args, **kwargs)
+        except RuntimeError:  # unable to save, possibly waiting for device to flush or anti-virus to finish scanning
+            if i == 3:
+                raise
+            time.sleep((2**i) / 2)  # exponential standoff 0.5s, 1.0s, 2.0s