yolo-ios-app
Ultralytics YOLO iOS App source code for running YOLOv8 in your own iOS apps 🌟
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The Ultralytics YOLO iOS App GitHub repository offers an advanced object detection tool leveraging YOLOv8 models for iOS devices. Users can transform their devices into intelligent detection tools to explore the world in a new and exciting way. The app provides real-time detection capabilities with multiple AI models to choose from, ranging from 'nano' to 'x-large'. Contributors are welcome to participate in this open-source project, and licensing options include AGPL-3.0 for open-source use and an Enterprise License for commercial integration. Users can easily set up the app by following the provided steps, including cloning the repository, adding YOLOv8 models, and running the app on their iOS devices.
README:
Welcome to the Ultralytics YOLO iOS App GitHub repository! đź“– Leveraging Ultralytics' advanced YOLOv8 object detection models, this app transforms your iOS device into an intelligent detection tool. Explore our guide to get started with the Ultralytics YOLO iOS App and discover the world in a new and exciting way.
Getting started with the Ultralytics YOLO iOS App is straightforward. Follow these steps to install the app on your iOS device.
Ensure you have the following before you start:
-
Xcode: The Ultralytics YOLO iOS App requires Xcode installed on your macOS machine. Download it from the Mac App Store.
-
An iOS Device: For testing the app, you'll need an iPhone or iPad running iOS 14.0 or later.
-
An Apple Developer Account: A free Apple Developer account will suffice for device testing. Sign up here if you haven't already.
-
Clone the Repository:
git clone https://github.com/ultralytics/yolo-ios-app.git
-
Open the Project in Xcode:
Navigate to the cloned directory and open the
YOLO.xcodeproj
file.In Xcode, go to the project's target settings and choose your Apple Developer account under the "Signing & Capabilities" tab.
-
Add YOLOv8 Models to the Project:
Export CoreML INT8 models using the
ultralytics
Python package (withpip install ultralytics
), or download them from our GitHub release assets. You should have 5 YOLOv8 models in total. Place these in theYOLO/Models
directory as seen in the Xcode screenshot below.from ultralytics import YOLO # Loop through all YOLOv8 model sizes for size in ("n", "s", "m", "l", "x"): # Load a YOLOv8 PyTorch model model = YOLO(f"yolov8{size}.pt") # Export the PyTorch model to CoreML INT8 format with NMS layers model.export(format="coreml", int8=True, nms=True, imgsz=[640, 384])
-
Run the Ultralytics YOLO iOS App:
Connect your iOS device and select it as the run target. Press the Run button to install the app on your device.
The Ultralytics YOLO iOS App is designed to be intuitive:
- Real-Time Detection: Launch the app and aim your camera at objects to detect them instantly.
- Multiple AI Models: Select from a range of Ultralytics YOLOv8 models, from YOLOv8n 'nano' to YOLOv8x 'x-large'.
We warmly welcome your contributions to Ultralytics' open-source projects! Your support and contributions significantly impact. Get involved by reviewing our Contributing Guide, and share your feedback through our Survey. A massive thank you 🙏 to everyone who contributes!
Ultralytics offers two licensing options:
-
AGPL-3.0 License: An OSI-approved open-source license, perfect for academics, researchers, and enthusiasts. It encourages sharing knowledge and collaboration. See the LICENSE file for details.
-
Enterprise License: Designed for commercial use, this license permits integrating Ultralytics software into proprietary products and services. For commercial use, please contact us through Ultralytics Licensing.
- Submit Ultralytics bug reports and feature requests via GitHub Issues.
- Join our Discord for assistance, questions, and discussions with the community and team!
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