ultralytics 8.2.78 fix DDP training with pretrained weights (#15616)
Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Laughing
GitHub
parent
0635a40b98
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6 changed files with 740 additions and 732 deletions
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{
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"nbformat": 4,
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"colab": {
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"gpuType": "T4",
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"toc_visible": true
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"name": "python3",
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"display_name": "Python 3"
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"language_info": {
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"name": "python"
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "PN1cAxdvd61e"
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},
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"source": [
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"<div align=\"center\">\n",
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"\n",
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@ -40,38 +26,35 @@
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"We hope that the resources in this notebook will help you get the most out of YOLOv8. Please browse the YOLOv8 <a href=\"https://docs.ultralytics.com/guides/heatmaps\">Heatmap Docs</a> for details, raise an issue on <a href=\"https://github.com/ultralytics/ultralytics\">GitHub</a> for support, and join our <a href=\"https://ultralytics.com/discord\">Discord</a> community for questions and discussions!\n",
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"\n",
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"</div>"
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],
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"metadata": {
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"id": "PN1cAxdvd61e"
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}
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]
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "o68Sg1oOeZm2"
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},
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"source": [
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"# Setup\n",
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"\n",
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"Pip install `ultralytics` and [dependencies](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) and check software and hardware.\n",
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"\n",
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"[](https://pypi.org/project/ultralytics/) [](https://pepy.tech/project/ultralytics) [](https://pypi.org/project/ultralytics/)"
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],
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"metadata": {
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"id": "o68Sg1oOeZm2"
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}
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"id": "9dSwz_uOReMI",
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "9dSwz_uOReMI",
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"outputId": "99866c77-e210-41e1-d581-8508371ce634"
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},
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Ultralytics YOLOv8.2.17 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
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"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 29.8/78.2 GB disk)\n"
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@ -81,11 +64,15 @@
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"source": [
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"%pip install ultralytics\n",
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"import ultralytics\n",
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"\n",
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"ultralytics.checks()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "m7VkxQ2aeg7k"
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},
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"source": [
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"# Introduction to Heatmaps\n",
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"\n",
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@ -97,15 +84,18 @@
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"|:-----------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------:|\n",
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"|  |  |\n",
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"| Ultralytics YOLOv8 Transportation Heatmap | Ultralytics YOLOv8 Retail Heatmap |\n"
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],
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"metadata": {
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"id": "m7VkxQ2aeg7k"
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}
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "Cx-u59HQdu2o"
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},
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"outputs": [],
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"source": [
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"import cv2\n",
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"\n",
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"from ultralytics import YOLO, solutions\n",
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"\n",
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"# Load YOLO model\n",
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@ -148,15 +138,13 @@
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"cap.release()\n",
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"video_writer.release()\n",
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"cv2.destroyAllWindows()"
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],
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"metadata": {
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"id": "Cx-u59HQdu2o"
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},
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"execution_count": null,
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"outputs": []
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "QrlKg-y3fEyD"
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},
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"source": [
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"# Additional Resources\n",
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"\n",
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@ -182,10 +170,24 @@
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"- [Discord](https://ultralytics.com/discord): Join our Discord community to connect with other users, share your projects, and get help from the Ultralytics team.\n",
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"\n",
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"These resources are designed to help you leverage the full potential of Ultralytics' offerings and YOLOv8. Whether you're a beginner or an experienced developer, you'll find the information and support you need to succeed."
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]
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}
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],
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"metadata": {
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"id": "QrlKg-y3fEyD"
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"accelerator": "GPU",
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"colab": {
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"gpuType": "T4",
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"provenance": [],
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"toc_visible": true
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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}
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}
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]
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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@ -1,20 +1,4 @@
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"name": "Ultralytics HUB",
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"provenance": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "markdown",
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@ -56,28 +40,29 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"id": "FyDnXd-n4c7Y",
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "FyDnXd-n4c7Y",
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"outputId": "e1d713ec-e8a6-4422-fe61-c76ec9f03df5"
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},
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"source": [
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"%pip install ultralytics # install\n",
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"from ultralytics import YOLO, checks, hub\n",
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"checks() # checks"
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],
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"execution_count": 1,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
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"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 28.8/78.2 GB disk)\n"
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]
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}
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],
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"source": [
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"%pip install ultralytics # install\n",
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"from ultralytics import YOLO, checks, hub\n",
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"\n",
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"checks() # checks"
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]
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},
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{
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@ -93,21 +78,37 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "XSlZaJ9Iw_iZ"
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},
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"outputs": [],
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"source": [
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"# Log in to HUB using your API key (https://hub.ultralytics.com/settings?tab=api+keys)\n",
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"hub.login('YOUR_API_KEY')\n",
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"hub.login(\"YOUR_API_KEY\")\n",
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"\n",
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"# Load your model from HUB (replace 'YOUR_MODEL_ID' with your model ID)\n",
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"model = YOLO('https://hub.ultralytics.com/models/YOUR_MODEL_ID')\n",
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"model = YOLO(\"https://hub.ultralytics.com/models/YOUR_MODEL_ID\")\n",
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"\n",
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"# Train the model\n",
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"results = model.train()"
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],
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"execution_count": null,
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"outputs": []
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}
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]
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}
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],
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"name": "Ultralytics HUB",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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@ -1,23 +1,10 @@
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"gpuType": "T4"
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "PN1cAxdvd61e"
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},
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"source": [
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"<div align=\"center\">\n",
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"\n",
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@ -39,38 +26,35 @@
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"We hope that the resources in this notebook will help you get the most out of YOLOv8. Please browse the YOLOv8 <a href=\"https://docs.ultralytics.com/guides/object-counting/\"> Object Counting Docs</a> for details, raise an issue on <a href=\"https://github.com/ultralytics/ultralytics\">GitHub</a> for support, and join our <a href=\"https://ultralytics.com/discord\">Discord</a> community for questions and discussions!\n",
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"\n",
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"</div>"
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],
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"metadata": {
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||||
"id": "PN1cAxdvd61e"
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||||
}
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||||
]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "o68Sg1oOeZm2"
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},
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"source": [
|
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"# Setup\n",
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"\n",
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"Pip install `ultralytics` and [dependencies](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) and check software and hardware.\n",
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"\n",
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"[](https://pypi.org/project/ultralytics/) [](https://pepy.tech/project/ultralytics) [](https://pypi.org/project/ultralytics/)"
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],
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"metadata": {
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"id": "o68Sg1oOeZm2"
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}
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"id": "9dSwz_uOReMI",
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"outputId": "fd3bab88-2f25-46c0-cae9-04d2beedc0c1",
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"colab": {
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"base_uri": "https://localhost:8080/"
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}
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},
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"id": "9dSwz_uOReMI",
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"outputId": "fd3bab88-2f25-46c0-cae9-04d2beedc0c1"
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},
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Ultralytics YOLOv8.2.18 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
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"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 29.8/78.2 GB disk)\n"
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@ -80,11 +64,15 @@
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"source": [
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"%pip install ultralytics\n",
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"import ultralytics\n",
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"\n",
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"ultralytics.checks()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "m7VkxQ2aeg7k"
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},
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"source": [
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"# Object Counting using Ultralytics YOLOv8 🚀\n",
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"\n",
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@ -104,15 +92,18 @@
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"|:-------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------:|\n",
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"|  |  |\n",
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"| Conveyor Belt Packets Counting Using Ultralytics YOLOv8 | Fish Counting in Sea using Ultralytics YOLOv8 |\n"
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],
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"metadata": {
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"id": "m7VkxQ2aeg7k"
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}
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "Cx-u59HQdu2o"
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},
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"outputs": [],
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"source": [
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"import cv2\n",
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"\n",
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"from ultralytics import YOLO, solutions\n",
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"\n",
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"# Load the pre-trained YOLOv8 model\n",
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"\n",
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"# Close all OpenCV windows\n",
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"cv2.destroyAllWindows()"
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],
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"metadata": {
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"id": "Cx-u59HQdu2o"
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},
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"execution_count": null,
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"outputs": []
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "QrlKg-y3fEyD"
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},
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"source": [
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"# Additional Resources\n",
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"\n",
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@ -199,10 +188,23 @@
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"- [Discord](https://ultralytics.com/discord): Join our Discord community to connect with other users, share your projects, and get help from the Ultralytics team.\n",
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"\n",
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"These resources are designed to help you leverage the full potential of Ultralytics' offerings and YOLOv8. Whether you're a beginner or an experienced developer, you'll find the information and support you need to succeed."
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]
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}
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],
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"metadata": {
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"id": "QrlKg-y3fEyD"
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"accelerator": "GPU",
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"colab": {
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"gpuType": "T4",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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}
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}
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]
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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@ -1,23 +1,10 @@
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"gpuType": "T4"
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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||||
"id": "PN1cAxdvd61e"
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||||
},
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||||
"source": [
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"<div align=\"center\">\n",
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"\n",
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@ -39,38 +26,35 @@
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"We hope that the resources in this notebook will help you get the most out of YOLOv8. Please browse the YOLOv8 <a href=\"https://docs.ultralytics.com/modes/track/\"> Tracking Docs</a> for details, raise an issue on <a href=\"https://github.com/ultralytics/ultralytics\">GitHub</a> for support, and join our <a href=\"https://ultralytics.com/discord\">Discord</a> community for questions and discussions!\n",
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"\n",
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"</div>"
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||||
],
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||||
"metadata": {
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||||
"id": "PN1cAxdvd61e"
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||||
}
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||||
]
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},
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{
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"cell_type": "markdown",
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||||
"metadata": {
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||||
"id": "o68Sg1oOeZm2"
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||||
},
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||||
"source": [
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"# Setup\n",
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"\n",
|
||||
"Pip install `ultralytics` and [dependencies](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) and check software and hardware.\n",
|
||||
"\n",
|
||||
"[](https://pypi.org/project/ultralytics/) [](https://pepy.tech/project/ultralytics) [](https://pypi.org/project/ultralytics/)"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "o68Sg1oOeZm2"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {
|
||||
"id": "9dSwz_uOReMI",
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
},
|
||||
"id": "9dSwz_uOReMI",
|
||||
"outputId": "ed8c2370-8fc7-4e4e-f669-d0bae4d944e9"
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Ultralytics YOLOv8.2.17 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
|
||||
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 29.8/78.2 GB disk)\n"
|
||||
|
|
@ -80,11 +64,15 @@
|
|||
"source": [
|
||||
"%pip install ultralytics\n",
|
||||
"import ultralytics\n",
|
||||
"\n",
|
||||
"ultralytics.checks()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "m7VkxQ2aeg7k"
|
||||
},
|
||||
"source": [
|
||||
"# Ultralytics Object Tracking\n",
|
||||
"\n",
|
||||
|
|
@ -102,50 +90,53 @@
|
|||
"|:---------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------:|\n",
|
||||
"|  |  |\n",
|
||||
"| Ultralytics Instance Segmentation 😍 | Ultralytics Instance Segmentation with Object Tracking 🔥 |"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "m7VkxQ2aeg7k"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "-ZF9DM6e6gz0"
|
||||
},
|
||||
"source": [
|
||||
"## CLI\n",
|
||||
"\n",
|
||||
"Command-Line Interface (CLI) example."
|
||||
],
|
||||
"metadata": {
|
||||
"id": "-ZF9DM6e6gz0"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"!yolo track source=\"/path/to/video/file.mp4\" save=True"
|
||||
],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "-XJqhOwo6iqT"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"!yolo track source=\"/path/to/video/file.mp4\" save=True"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "XRcw0vIE6oNb"
|
||||
},
|
||||
"source": [
|
||||
"## Python\n",
|
||||
"\n",
|
||||
"Python Instance Segmentation and Object tracking example."
|
||||
],
|
||||
"metadata": {
|
||||
"id": "XRcw0vIE6oNb"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "Cx-u59HQdu2o"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from collections import defaultdict\n",
|
||||
"\n",
|
||||
"import cv2\n",
|
||||
"\n",
|
||||
"from ultralytics import YOLO\n",
|
||||
"from ultralytics.utils.plotting import Annotator, colors\n",
|
||||
"\n",
|
||||
|
|
@ -200,15 +191,13 @@
|
|||
"out.release()\n",
|
||||
"cap.release()\n",
|
||||
"cv2.destroyAllWindows()"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "Cx-u59HQdu2o"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "QrlKg-y3fEyD"
|
||||
},
|
||||
"source": [
|
||||
"# Additional Resources\n",
|
||||
"\n",
|
||||
|
|
@ -234,10 +223,23 @@
|
|||
"- [Discord](https://ultralytics.com/discord): Join our Discord community to connect with other users, share your projects, and get help from the Ultralytics team.\n",
|
||||
"\n",
|
||||
"These resources are designed to help you leverage the full potential of Ultralytics' offerings and YOLOv8. Whether you're a beginner or an experienced developer, you'll find the information and support you need to succeed."
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"id": "QrlKg-y3fEyD"
|
||||
"accelerator": "GPU",
|
||||
"colab": {
|
||||
"gpuType": "T4",
|
||||
"provenance": []
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
}
|
||||
]
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
# Ultralytics YOLO 🚀, AGPL-3.0 license
|
||||
|
||||
__version__ = "8.2.77"
|
||||
__version__ = "8.2.78"
|
||||
|
||||
import os
|
||||
|
||||
|
|
|
|||
|
|
@ -381,6 +381,7 @@ class Model(nn.Module):
|
|||
"""
|
||||
self._check_is_pytorch_model()
|
||||
if isinstance(weights, (str, Path)):
|
||||
self.overrides["pretrained"] = weights # remember the weights for DDP training
|
||||
weights, self.ckpt = attempt_load_one_weight(weights)
|
||||
self.model.load(weights)
|
||||
return self
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue