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EfficientDet Implementation: zylo117/Yet-Another-EfficientDet-Pytorch
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Multiple Webcams with Object Detection: gaodechen/webcam_yolov3_jetson_tx_hikvision
Same usage as gaodechen/webcam_yolov3_jetson_tx_hikvision.
model.py
: post-packaging forYet-Another-EfficientDet-Pytorch
, no need to changesettings.py
: IP list & image shape could be modified here, view the zylo117/Yet-Another-EfficientDet-Pytorch repo for other configurations
Running:
python run.py --single_window=True (or False) --num_cameras=4
single_window
: argument used when multiple images should be merged and displayed into one single window.
num_cameras
: number of cameras to be processed.
Delete model processing part in predict() as below.
def predict(raw_q, pred_q):
# model = Model()
while True:
raw_img = raw_q.get()
# pred_img = model.run(raw_img)
pred_q.put(raw_img)
PyTorch 1.4.0 and torchvision 0.5.0 are required for EfficientDet. Now the ARM sources for pip are still not supporting those versions, so we need installing packages or sources to build.
No need to build from scratch, installation package of PyTorch for ARM is available.
- Download .whl package here: PyTorch for Jetson Nano - version 1.4.0 now available
Here you need to clone torchvision sources and build. git clone may take a while so I add the --depth
argument to download the latest commit only.
$ git clone --branch v0.5.0 https://github.com/pytorch/vision torchvision --depth=1
$ cd torchvision
$ sudo python setup.py install