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hailo-ai / Hailo-Application-Code-Examples

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Hailo Application Code Examples

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🚀 Runtime

Application examples for Hailo inference with different languages and operating systems

Python APP | Description | |:---|:---| | `depth_estimation` | Depth estimation with StereoNet | `detection_with_tracker` | Object detection with tracking using ByteTracker and Supervision | `hailo_onnxruntime` | Inference with a Hailo device and postprocessing with ONNXRuntime | `instance_segmentation` | Instance segmentation with yolov5_seg, yolov8_seg | `lane_detection` | Lane detection with UFLDv2 | `object_detection` | Object detection with yolo, ssd, centernet | `pose_estimation` | Pose estimation with yolov8 | `streaming` | Object detection on a streaming input from a camera using OpenCV | `super_resolution` | Super resolution with espcnx4, srgan
C++ APP | Description | |:---|:---| | `classifier` | Classification with models trained on ImageNet | `depth_estimation` | Depth estimation with scdepthv3 and stereonet | `hailo_onnxruntime` | Inference with a Hailo device and postprocessing with ONNXRuntime | `hailo15_media_library` | H-15 Inference using the media library tools - crop and resize, nv12 conversion | `instance_segmentation` | Instance segmentation with yolov5_seg, yolov8_seg | `object_detection` | Object detection - generic, asynchronous, H15 | `pose estimation` | Pose estimation with yolov8 | `re_id` | People re-identification using yolov5s and repvgg_a0 | `scheduler` | Multi-model inference using the Hailo scheduler | `semantic_segmentation` | Semantic segmentation with Resnet18_fcn trained on cityscape
GStreamer APP | Description | |:---|:---| | `advanced_cpp_app` | Complex GStreamer pipeline wrapped by C++ | `cpp_cascaded_networks_dynamic_osd` | Cascade networks pipeline wrapped by C++ | `cropper_aggregator` | Gstreamer pipeline with hailocropper and hailoaggregator | `detection_python` | Python implementation of TAPPAS detection pipeline using Yolov5m | `hailo"_clip` | CLIP inference on a video in real-time | `multistream_app` | Inference on multiple streams on the same pipeline, added C++ usability | `multistream_multi_networks` | Object detection + semantic segmentation | `multistream_stream_id` | Multistream with stream ID | `simple_cpp_app` | Simple app that shows how to use Gstreamer with C++ on top | `tda4vm/pose_estimation` | Single-stream pose estimation pipelin` on top of GStreamer and TDA4VM DSP | `tonsofstreams` | Many streams with 4 Hailo devices
Windows APP | Description | |:---|:---| | `yolov5` | Object detection with yolov5 using a C++ script compiled for Windows | `yolov8` | Object detection with yolov8 using a C++ script compiled for Windows
C# APP | Description | |:---|:---| | `csharp_infer_wrapper` | Yolov5 Inference using a C# wrapper

🏗️ Compilation

Basic optimization diagnostic tool: help diagnosing common optimization issues and mistakes
Pointpillars: Hailo device offload of the heavy 2D-convolutional part of a 3D-object-detection network operating on point-clouds
16-bit Optimization: Guide on how to perform 16-bit optimization

📚 Resources

Documents and other files

⚠️ Disclaimer

The code examples are provided by Hailo solely on an “AS IS” basis and “with all faults”. No responsibility or liability is accepted or shall be imposed upon Hailo regarding the accuracy, merchantability, completeness or suitability of the code example. Hailo shall not have any liability or responsibility for errors or omissions in, or any business decisions made by you in reliance on this code example or any part of it. If an error occurs when running the examples, please open a ticket in the "Issues" tab.