Polar Bear AI

Results 6 issues of Polar Bear AI

My platform is: TensorFlow-GPU 1.4.0 tflearn 0.3.2 GTX 1080Ti But when I'm running the demo [code](https://github.com/tflearn/tflearn/blob/master/examples/images/vgg_network.py), tflearn **choses the CPU** to train the network rather than GPU? How to solve...

I exported my trained model into ONNX by the following code: ``` torch.onnx.export(model, input_tensor, onnx_name, verbose=True, opset_version=12, input_names=['images'], output_names=['output'], use_external_data_format=False) ``` But when running onnx model, I got the following...

I used LISA traffic dataset as the training dataset and translated all images and annotations to VOC format. But when training, **the AL, AC and OL are nan**: Epoch:1 ||...

Hi, Your work is excellent! I have seen your result of VOC2012, mAP=88.38% according to the [blog](https://yunyang1994.github.io/posts/YOLOv3/#more). But I cannot find your result on official VOC2012 [leaderboard](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb_main.php?challengeid=11&compid=3)

Hello. In KITTI2012 data_stereo_flow\training\disp_noc\000000_10.png, I saw the maximum raw value is 17873. Is it the real disparity? Does it need any transformation? Thanks a lot.

Device 0: "NVS 315" 1024Mb, sm_21, 48 cores, Driver/Runtime ver.8.0/8.0 KinFu2 error: Init failed: Can't create any node of the requested type! ..\..\kinfu_remake-master\kfusion\src\capture.cpp:85 NVS 315's architecture is Fermi. Anyone knows...