deep_sort_yolov3
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有没有人把这个东西运行在 NVIDIA 的JETSON NANO中的 ,求教程
有没有人把这个东西运行在 NVIDIA 的JETSON NANO中的 ,求教程 谢谢!
I'm trying to run this on Jeston Nano but I get stuck on this:
out_boxes, out_scores, out_classes = self.sess.run(
[self.boxes, self.scores, self.classes],
feed_dict={
self.yolo_model.input: image_data,
self.input_image_shape: [image.size[1], image.size[0]],
K.learning_phase(): 0
})
return_boxs = []
It hangs out at this level forever. What could it be causing it?
After leaving it for a while, it displays the following message:
kthreadd: page allocation stalls for 10004ms, order:2, mode:0x27080c0(GFP_KERNAL_ACCOUNT|__GFP_ZERO|__GFP_NOTRACK)
kthreadd invoked oom-killer: gfp_mask=0x27080c0(GFP_KERNEL_ACCOUNT|__GFP_ZERO|__GFP_NOTRACK), nodemask=0, order=2, oom_score_adj=0
Out of memory: Kill process 7248 (python3) score 266 or sacrifice child
看上去这内存分配失败了,是不是内存/显存不足?
Memory is hitting the limit, just verified it with tegrastats
I'm adding a swapfile to help the the memory, will let you know if that fixed it.
@kzka90 Thank you very much !
tensorflow part in generate_detections: config = tf.ConfigProto() config.gpu_options.per_process_gpu_memory_fraction = 0.1 # GPU10% self.session = tf.Session(config=config)
keras part in yolo: config = tf.ConfigProto() config.gpu_options.per_process_gpu_memory_fraction = 0.2 # GPU20% set_session(tf.Session(config=config))
@kzka90 did you solve the issue with a swapfile? I made a 6GB swapfile. But I can`t do well on my nano.
this seems to be running stuck on the following issue for me:
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[3,3,512,1024] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:Mul]
8GB allocated for memory, should a swap file help?
Also: would this work in a live setup, pulling images from the camera?