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https://github.com/thnak/yolov7-2-tensorflow

export any your YOLOv7 model to TensorFlow, TensorFlowJs, ONNX, OpenVINO, RKNN,...
https://github.com/thnak/yolov7-2-tensorflow

deep-learning directml object-detection rknn tensorflow tensorflowjs tfjs windows yolov7

Last synced: 5 months ago
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export any your YOLOv7 model to TensorFlow, TensorFlowJs, ONNX, OpenVINO, RKNN,...

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README

          


YOLOv7 supported for tfjs, tflite, saved model, openvino, onnx, rknn.Support for WINDOWS and LINUX


Train


!python train.py --batch 4 --epochs 10 --data 'data/coco.yaml' --cache_images disk --cfg 'cfg/yolov7-tiny.yaml' --device dml:0 --imgsz 640


dml:0 to set dml device (windows), cuda:0 to set cuda device, cache-images for faster training disk/ram/no

Export


python export.py --weights "yolov7.pt" --include tfjs/onnx/saved_model/openvino/tflite


for more information


python export.py --help


Usage


tfjs model can be used with makesense.ai


🔥Actions -> Run AI locally -> YOLOv5 object detection using rectangles -> and import all files from *_web_model folder




also you can follow this step to use (from https://github.com/Hyuto/yolov5-tfjs)




.onnx can be used with python.exe detect.py --weights "yolov7-w6.onnx" --nosave --source 0 --view-img 1 (use 0 to freeze screen)


References