ultralytics 8.0.203 DDP argparse and Tracker fixes (#6007)

.pre-commit-config.yaml

@@ -2,14 +2,17 @@
 # Pre-commit hooks. For more information see https://github.com/pre-commit/pre-commit-hooks/blob/main/README.md
 # Optionally remove from local hooks with 'rm .git/hooks/pre-commit'
 
-# exclude: 'docs/'
 # Define bot property if installed via https://github.com/marketplace/pre-commit-ci
 ci:
   autofix_prs: true
   autoupdate_commit_msg: '[pre-commit.ci] pre-commit suggestions'
   autoupdate_schedule: monthly
-  # submodules: true
+  submodules: true
 
+# Exclude directories (optional)
+# exclude: 'docs/'
+
+# Define repos to run
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.5.0

docker/Dockerfile

@@ -13,7 +13,6 @@ ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Aria
 # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
 RUN apt update \
     && apt install --no-install-recommends -y gcc git zip curl htop libgl1-mesa-glx libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
-# RUN alias python=python3
 
 # Security updates
 # https://security.snyk.io/vuln/SNYK-UBUNTU1804-OPENSSL-3314796

docker/Dockerfile-arm64

@@ -12,7 +12,6 @@ ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Aria
 # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
 RUN apt update \
     && apt install --no-install-recommends -y python3-pip git zip curl htop gcc libgl1-mesa-glx libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
-# RUN alias python=python3
 
 # Create working directory
 WORKDIR /usr/src/ultralytics

docker/Dockerfile-cpu

@@ -12,7 +12,6 @@ ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Aria
 # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
 RUN apt update \
     && apt install --no-install-recommends -y python3-pip git zip curl htop libgl1-mesa-glx libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
-# RUN alias python=python3
 
 # Create working directory
 WORKDIR /usr/src/ultralytics

docker/Dockerfile-jetson

@@ -12,7 +12,6 @@ ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Aria
 # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
 RUN apt update \
     && apt install --no-install-recommends -y gcc git zip curl htop libgl1-mesa-glx libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
-# RUN alias python=python3
 
 # Create working directory
 WORKDIR /usr/src/ultralytics

docker/Dockerfile-python

@@ -12,7 +12,6 @@ ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Aria
 # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
 RUN apt update \
     && apt install --no-install-recommends -y python3-pip git zip curl htop libgl1-mesa-glx libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
-# RUN alias python=python3
 
 # Create working directory
 WORKDIR /usr/src/ultralytics

docs/guides/index.md

@@ -15,6 +15,7 @@ Whether you're a beginner or an expert in deep learning, our tutorials offer val
 Here's a compilation of in-depth guides to help you master different aspects of Ultralytics YOLO.
 
 * [YOLO Common Issues](yolo-common-issues.md) ⭐ RECOMMENDED: Practical solutions and troubleshooting tips to the most frequently encountered issues when working with Ultralytics YOLO models.
+* [YOLO Performance Metrics](yolo-performance-metrics.md) ⭐ ESSENTIAL: Understand the key metrics like mAP, IoU, and F1 score used to evaluate the performance of your YOLO models. Includes practical examples and tips on how to improve detection accuracy and speed.
 * [K-Fold Cross Validation](kfold-cross-validation.md) 🚀 NEW: Learn how to improve model generalization using K-Fold cross-validation technique.
 * [Hyperparameter Tuning](hyperparameter-tuning.md) 🚀 NEW: Discover how to optimize your YOLO models by fine-tuning hyperparameters using the Tuner class and genetic evolution algorithms.
 * [SAHI Tiled Inference](sahi-tiled-inference.md) 🚀 NEW: Comprehensive guide on leveraging SAHI's sliced inference capabilities with YOLOv8 for object detection in high-resolution images.

docs/help/CI.md

@@ -23,12 +23,12 @@ Here's a brief description of our CI actions:
 Below is the table showing the status of these CI tests for our main repositories:
 
 | Repository                                                | CI                                                                                                                                                                        | Docker Deployment                                                                                                                                                                        | Broken Links                                                                                                                                                                      | CodeQL                                                                                                                                                                          | PyPi and Docs Publishing                                                                                                                                                                                      |
-|-----------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|-----------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | [yolov3](https://github.com/ultralytics/yolov3)           | [![YOLOv3 CI](https://github.com/ultralytics/yolov3/actions/workflows/ci-testing.yml/badge.svg)](https://github.com/ultralytics/yolov3/actions/workflows/ci-testing.yml)  | [![Publish Docker Images](https://github.com/ultralytics/yolov3/actions/workflows/docker.yml/badge.svg)](https://github.com/ultralytics/yolov3/actions/workflows/docker.yml)             | [![Check Broken links](https://github.com/ultralytics/yolov3/actions/workflows/links.yml/badge.svg)](https://github.com/ultralytics/yolov3/actions/workflows/links.yml)           | [![CodeQL](https://github.com/ultralytics/yolov3/actions/workflows/codeql-analysis.yml/badge.svg)](https://github.com/ultralytics/yolov3/actions/workflows/codeql-analysis.yml) |                                                                                                                                                                                                               |
 | [yolov5](https://github.com/ultralytics/yolov5)           | [![YOLOv5 CI](https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml/badge.svg)](https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml)  | [![Publish Docker Images](https://github.com/ultralytics/yolov5/actions/workflows/docker.yml/badge.svg)](https://github.com/ultralytics/yolov5/actions/workflows/docker.yml)             | [![Check Broken links](https://github.com/ultralytics/yolov5/actions/workflows/links.yml/badge.svg)](https://github.com/ultralytics/yolov5/actions/workflows/links.yml)           | [![CodeQL](https://github.com/ultralytics/yolov5/actions/workflows/codeql-analysis.yml/badge.svg)](https://github.com/ultralytics/yolov5/actions/workflows/codeql-analysis.yml) |                                                                                                                                                                                                               |
 | [ultralytics](https://github.com/ultralytics/ultralytics) | [![ultralytics CI](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml/badge.svg)](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml) | [![Publish Docker Images](https://github.com/ultralytics/ultralytics/actions/workflows/docker.yaml/badge.svg)](https://github.com/ultralytics/ultralytics/actions/workflows/docker.yaml) | [![Check Broken links](https://github.com/ultralytics/ultralytics/actions/workflows/links.yml/badge.svg)](https://github.com/ultralytics/ultralytics/actions/workflows/links.yml) | [![CodeQL](https://github.com/ultralytics/ultralytics/actions/workflows/codeql.yaml/badge.svg)](https://github.com/ultralytics/ultralytics/actions/workflows/codeql.yaml)       | [![Publish to PyPI and Deploy Docs](https://github.com/ultralytics/ultralytics/actions/workflows/publish.yml/badge.svg)](https://github.com/ultralytics/ultralytics/actions/workflows/publish.yml)            |
 | [hub](https://github.com/ultralytics/hub)                 | [![HUB CI](https://github.com/ultralytics/hub/actions/workflows/ci.yaml/badge.svg)](https://github.com/ultralytics/hub/actions/workflows/ci.yaml)                         |                                                                                                                                                                                          | [![Check Broken links](https://github.com/ultralytics/hub/actions/workflows/links.yml/badge.svg)](https://github.com/ultralytics/hub/actions/workflows/links.yml)                 |                                                                                                                                                                                 |                                                                                                                                                                                                               |
-| [docs](https://github.com/ultralytics/docs)               |                                                                                                                                                                           |                                                                                                                                                                                          |                                                                                                                                                                                   |                                                                                                                                                                                 | [![pages-build-deployment](https://github.com/ultralytics/docs/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/ultralytics/docs/actions/workflows/pages/pages-build-deployment) [![Check Broken links](https://github.com/ultralytics/docs/actions/workflows/links.yml/badge.svg)](https://github.com/ultralytics/docs/actions/workflows/links.yml) |
+| [docs](https://github.com/ultralytics/docs)               |                                                                                                                                                                           |                                                                                                                                                                                          | [![Check Broken links](https://github.com/ultralytics/docs/actions/workflows/links.yml/badge.svg)](https://github.com/ultralytics/docs/actions/workflows/links.yml)               |                                                                                                                                                                                 | [![pages-build-deployment](https://github.com/ultralytics/docs/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/ultralytics/docs/actions/workflows/pages/pages-build-deployment) |
 
 Each badge shows the status of the last run of the corresponding CI test on the `main` branch of the respective repository. If a test fails, the badge will display a "failing" status, and if it passes, it will display a "passing" status.
 

docs/modes/train.md

@@ -47,7 +47,7 @@ The following are some notable features of YOLOv8's Train mode:
 
 ## Usage Examples
 
-Train YOLOv8n on the COCO128 dataset for 100 epochs at image size 640. See Arguments section below for a full list of training arguments.
+Train YOLOv8n on the COCO128 dataset for 100 epochs at image size 640. The training device can be specified using the `device` argument. If no argument is passed GPU `device=0` will be used if available, otherwise `device=cpu` will be used. See Arguments section below for a full list of training arguments.
 
 !!! example "Single-GPU and CPU Training Example"
 
@@ -82,10 +82,12 @@ Train YOLOv8n on the COCO128 dataset for 100 epochs at image size 640. See Argum
 
 ### Multi-GPU Training
 
-The training device can be specified using the `device` argument. If no argument is passed GPU `device=0` will be used if available, otherwise `device=cpu` will be used.
+Multi-GPU training allows for more efficient utilization of available hardware resources by distributing the training load across multiple GPUs. This feature is available through both the Python API and the command-line interface. To enable multi-GPU training, specify the GPU device IDs you wish to use.
 
 !!! example "Multi-GPU Training Example"
 
+    To train with 2 GPUs, CUDA devices 0 and 1 use the following commands. Expand to additional GPUs as required.
+
     === "Python"
 
         ```python

mkdocs.yml

@@ -215,6 +215,7 @@ nav:
   - Guides:
       - guides/index.md
       - YOLO Common Issues: guides/yolo-common-issues.md
+      - Performance Metrics: guides/yolo-performance-metrics.md
       - K-Fold Cross Validation: guides/kfold-cross-validation.md
       - Hyperparameter Tuning: guides/hyperparameter-tuning.md
       - SAHI Tiled Inference: guides/sahi-tiled-inference.md

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.202'
+__version__ = '8.0.203'
 
 from ultralytics.models import RTDETR, SAM, YOLO
 from ultralytics.models.fastsam import FastSAM

ultralytics/trackers/bot_sort.py

@@ -192,3 +192,8 @@ class BOTSORT(BYTETracker):
     def multi_predict(self, tracks):
         """Predict and track multiple objects with YOLOv8 model."""
         BOTrack.multi_predict(tracks)
+
+    def reset(self):
+        """Reset tracker."""
+        super().reset()
+        self.gmc.reset_params()

ultralytics/trackers/byte_tracker.py

@@ -374,6 +374,15 @@ class BYTETracker:
         """Resets the ID counter of STrack."""
         STrack.reset_id()
 
+    def reset(self):
+        """Reset tracker."""
+        self.tracked_stracks = []  # type: list[STrack]
+        self.lost_stracks = []  # type: list[STrack]
+        self.removed_stracks = []  # type: list[STrack]
+        self.frame_id = 0
+        self.kalman_filter = self.get_kalmanfilter()
+        self.reset_id()
+
     @staticmethod
     def joint_stracks(tlista, tlistb):
         """Combine two lists of stracks into a single one."""

ultralytics/trackers/track.py

@@ -1,6 +1,7 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
 from functools import partial
+from pathlib import Path
 
 import torch
 
@@ -40,8 +41,12 @@ def on_predict_start(predictor, persist=False):
 def on_predict_postprocess_end(predictor):
     """Postprocess detected boxes and update with object tracking."""
     bs = predictor.dataset.bs
-    im0s = predictor.batch[1]
+    path, im0s = predictor.batch[:2]
+
     for i in range(bs):
+        if predictor.vid_path[i] != str(predictor.save_dir / Path(path[i]).name):  # new video
+            predictor.trackers[i].reset()
+
         det = predictor.results[i].boxes.cpu().numpy()
         if len(det) == 0:
             continue

ultralytics/trackers/utils/gmc.py

@@ -300,3 +300,10 @@ class GMC:
         self.prevKeyPoints = copy.copy(keypoints)
 
         return H
+
+    def reset_params(self):
+        """Reset parameters."""
+        self.prevFrame = None
+        self.prevKeyPoints = None
+        self.prevDescriptors = None
+        self.initializedFirstFrame = False