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View Code? Open in Web Editor NEWmodification of pydarknet to support getting logits out of yolo darknet
License: Apache License 2.0
modification of pydarknet to support getting logits out of yolo darknet
License: Apache License 2.0
Appreciate the python wrapper, nice work.
I am curious if there is a configuration that would improve performance.
When I invoke ./dark-net detect demo /foo/video.mp4 my setup gets around ~20 fps using yolov3-tiny.cfg and yolov3-tiny.weights.
when I run python3 video_demo.py with the same parameters and same video it appears to be in the ~5 fps. Below is the setup
...
net = Detector(bytes("cfg/yolov3-tiny.cfg", encoding="utf-8"), bytes("weights/yolov3-tiny.weights", encoding="utf-8"), 0,
bytes("cfg/coco.data", encoding="utf-8"))
...
Any thoughts why? Thanks in advance for your support.
Hello, I was wondering how I can the change the threshold of images returned by the Detector,
Any help?
Thanks
I wanna to convert the yolov3-tiny model with pytorch to onnx model.
'
model = pydarknet.Detector(bytes(cfg_file, encoding="utf-8"), bytes(weights_file, encoding="utf-8"), 0, bytes(classes_file, encoding="utf-8"))
batch_size=1
onnx_path ="onnx_model.onnx"
dummy_input = Variable(torch.randn(batch_size, 3, 224, 224), requires_grad=True)
torch_out = torch.onnx.export(model, dummy_input, onnx_path )
'
But this error occurs: AttributeError: pydarknet.detector' object has no attribute 'state_dict'.
how to compile it for cuda 10? Thanks
In instantiating the Detector, can another path to data/coco.names be specified? Currently changing it to the directory which contains both cfg/ and data/ as in:
cur_dir = os.getcwd()
good_dir = /path/to/dir/with/cfg/and/data
os.chdir(good_dir)
detector = Detector(
bytes("cfg/yolov3.cfg", encoding="utf-8"),
bytes("weights/yolov3.weights", encoding="utf-8"),
0,
bytes("cfg/coco.data", encoding="utf-8")
)
os.chdir(cur_dir)
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