Fix PyPI downloads links (#17399)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/README.md

@@ -15,7 +15,7 @@
 ## 🛠️ Installation
 
 [![PyPI - Version](https://img.shields.io/pypi/v/ultralytics?logo=pypi&logoColor=white)](https://pypi.org/project/ultralytics/)
-[![Downloads](https://static.pepy.tech/badge/ultralytics)](https://pepy.tech/project/ultralytics)
+[![Downloads](https://static.pepy.tech/badge/ultralytics)](https://www.pepy.tech/projects/ultralytics)
 [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ultralytics?logo=python&logoColor=gold)](https://pypi.org/project/ultralytics/)
 
 To install the ultralytics package in developer mode, ensure you have Git and Python 3 installed on your system. Then, follow these steps:

docs/en/index.md

@@ -20,7 +20,7 @@ keywords: Ultralytics, YOLO, YOLO11, object detection, image segmentation, deep
 <br>
 <br>
     <a href="https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml"><img src="https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml/badge.svg" alt="Ultralytics CI"></a>
-    <a href="https://pepy.tech/project/ultralytics"><img src="https://static.pepy.tech/badge/ultralytics" alt="Ultralytics Downloads"></a>
+    <a href="https://www.pepy.tech/projects/ultralytics"><img src="https://static.pepy.tech/badge/ultralytics" alt="Ultralytics Downloads"></a>
     <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="Ultralytics YOLO Citation"></a>
     <a href="https://discord.com/invite/ultralytics"><img alt="Ultralytics Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
     <a href="https://community.ultralytics.com/"><img alt="Ultralytics Forums" src="https://img.shields.io/discourse/users?server=https%3A%2F%2Fcommunity.ultralytics.com&logo=discourse&label=Forums&color=blue"></a>

docs/en/models/yolo11.md

@@ -130,7 +130,7 @@ Note that the example below is for YOLO11 [Detect](../tasks/detect.md) models fo
 
 !!! tip "Ultralytics YOLO11 Publication"
 
-    Ultralytics has not published a formal research paper for YOLO11 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com).
+    Ultralytics has not published a formal research paper for YOLO11 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com/).
 
 If you use YOLO11 or any other software from this repository in your work, please cite it using the following format:
 

docs/en/models/yolov5.md

@@ -94,7 +94,7 @@ This example provides simple YOLOv5 training and inference examples. For full do
 
 !!! tip "Ultralytics YOLOv5 Publication"
 
-    Ultralytics has not published a formal research paper for YOLOv5 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com).
+    Ultralytics has not published a formal research paper for YOLOv5 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com/).
 
 If you use YOLOv5 or YOLOv5u in your research, please cite the Ultralytics YOLOv5 repository as follows:
 

docs/en/models/yolov8.md

@@ -167,7 +167,7 @@ Note the below example is for YOLOv8 [Detect](../tasks/detect.md) models for obj
 
 !!! tip "Ultralytics YOLOv8 Publication"
 
-    Ultralytics has not published a formal research paper for YOLOv8 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com).
+    Ultralytics has not published a formal research paper for YOLOv8 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com/).
 
 If you use the YOLOv8 model or any other software from this repository in your work, please cite it using the following format:
 

docs/en/quickstart.md

@@ -28,7 +28,7 @@ Ultralytics provides various installation methods including pip, conda, and Dock
         Install the `ultralytics` package using pip, or update an existing installation by running `pip install -U ultralytics`. Visit the Python Package Index (PyPI) for more details on the `ultralytics` package: [https://pypi.org/project/ultralytics/](https://pypi.org/project/ultralytics/).
 
         [![PyPI - Version](https://img.shields.io/pypi/v/ultralytics?logo=pypi&logoColor=white)](https://pypi.org/project/ultralytics/)
-        [![Downloads](https://static.pepy.tech/badge/ultralytics)](https://pepy.tech/project/ultralytics)
+        [![Downloads](https://static.pepy.tech/badge/ultralytics)](https://www.pepy.tech/projects/ultralytics)
 
         ```bash
         # Install the ultralytics package from PyPI

docs/overrides/javascript/extra.js

@@ -47,7 +47,9 @@ checkAutoTheme();
 document.addEventListener("DOMContentLoaded", () => {
   const autoThemeInput = document.getElementById("__palette_1");
   autoThemeInput?.addEventListener("click", () => {
-    if (autoThemeInput.checked) setTimeout(checkAutoTheme);
+    if (autoThemeInput.checked) {
+      setTimeout(checkAutoTheme);
+    }
   });
 });
 
@@ -165,7 +167,9 @@ let chart = null;  // chart variable will hold the reference to the current char
 // This function is responsible for updating the benchmarks chart.
 function updateChart() {
     // If a chart instance already exists, destroy it.
-    if (chart) chart.destroy();
+    if (chart) {
+      chart.destroy();
+    }
 
     // Get the selected algorithms from the checkboxes.
     const selectedAlgorithms = [...document.querySelectorAll('input[name="algorithm"]:checked')].map(e => e.value);
@@ -187,7 +191,9 @@ function updateChart() {
     }));
 
     // If there are no selected algorithms, return without creating a new chart.
-    if (datasets.length === 0) return;
+    if (datasets.length === 0) {
+      return;
+    }
 
     // Create a new chart instance.
     chart = new Chart(document.getElementById('chart').getContext('2d'), {

docs/overrides/javascript/giscus.js

@@ -1,7 +1,9 @@
 // Giscus functionality
 function loadGiscus() {
   const giscusContainer = document.getElementById("giscus-container");
-  if (!giscusContainer || giscusContainer.querySelector("script")) return;
+  if (!giscusContainer || giscusContainer.querySelector("script")) {
+    return;
+  }
 
   const script = document.createElement("script");
   script.src = "https://giscus.app/client.js";