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Python scripts performing object detection using the YOLOv7 model in ONNX.

Original image: https://www.flickr.com/photos/nicolelee/19041780

Important

• The input images are directly resized to match the input size of the model. I skipped adding the pad to the input image, it might affect the accuracy of the model if the input image has a different aspect ratio compared to the input size of the model. Always try to get an input size with a ratio close to the input images you will use.

Requirements

• Check the requirements.txt file.
• For ONNX, if you have a NVIDIA GPU, then install the onnxruntime-gpu, otherwise use the onnxruntime library.

Installation

git clone https://github.com/ibaiGorordo/ONNX-YOLOv7-Object-Detection.git
cd ONNX-YOLOv7-Object-Detection
pip install -r requirements.txt

ONNX Runtime

For Nvidia GPU computers: pip install onnxruntime-gpu

Otherwise: pip install onnxruntime

ONNX model

The original models were converted to different formats (including .onnx) by PINTO0309. Download the models from [his repository](https://github.com/PINTO0309/PINTO_model_zoo/tree/main/307_YOLOv7). For that, you can either run the download_single_batch.sh or copy the google drive link inside that script in your browser to manually download the file. Then, extract and copy the downloaded onnx models (for example yolov7-tiny_480x640.onnx) to your models directory, and fix the file name in the python scripts accordingly.

• The License of the models is GPL-3.0 license: License

Original YOLOv7 model

The original YOLOv7 model can be found in this repository: YOLOv7 Repository

• For Darknet style model, check the darknet branch
• For YOLOv5 compatible model, check the u5 branch

Examples

• Image inference:

   python image_object_detection.py
  

• Webcam inference:

   python webcam_object_detection.py
  

• Video inference: https://youtu.be/yYo0XQp97vo

   python video_object_detection.py
  

  

Original video: https://youtu.be/zPre8MgmcHY

• Comparison with YOLOv5 or YOLOv6: https://youtu.be/WSFmLMLIbDQ

   python comparison_with_yolov5_v6.py
  

  Original video: https://youtu.be/zPre8MgmcHY

• Replace the yolov5_v6_path with the actual path to the YOLOv5 or YOLOv6 model.
• Convert YOLOv5 model to ONNX
• Convert YOLOv6 model to ONNX

References:

• YOLOv7 model: https://github.com/WongKinYiu/yolov7
• Paper: https://arxiv.org/abs/2207.02696
• YOLOv6 model: https://github.com/WongKinYiu/yolov7
• YOLOv5 model: https://github.com/ultralytics/yolov5
• PINTO0309’s model zoo: https://github.com/PINTO0309/PINTO_model_zoo
• PINTO0309’s model conversion tool: https://github.com/PINTO0309/openvino2tensorflow