cpgeier / santosnet Goto Github PK

A simple self driving car in GTAV that uses the Xception deep neural network model with DeepGTAV

Python 100.00%

self-driving-car keras-tensorflow computer-vision gtav

santosnet's Issues

Location of model_trained_categorical.h5 pretrained weights

The drive_categorical.py file loads a pretrained model which is not provided in the repo. Is there a place we can find these weights?

Git LFS: (0 of 1 files) 0 B / 262.27 MB .batch response: This repository is over its data quota. Purchase more data packs to restore access.

Hi:
I'd like to git clone the folder and I met the problem as following:

D:\Git LFS\1>git lfs clone https://github.com/cpgeier/SantosNet.git
WARNING: 'git lfs clone' is deprecated and will not be updated
with new flags from 'git clone'
'git clone' has been updated in upstream Git to have comparable
speeds to 'git lfs clone'.
Cloning into 'SantosNet'...
remote: Enumerating objects: 79, done.
remote: Total 79 (delta 0), reused 0 (delta 0), pack-reused 79
Unpacking objects: 100% (79/79), done.
Git LFS: (0 of 1 files) 0 B / 262.27 MB
batch response: This repository is over its data quota. Purchase more data packs to restore access.
error: failed to fetch some objects from 'https://github.com/cpgeier/SantosNet.git/info/lfs'

would you like to purchase more data packs and restore access, thanks very much!

Trouble in receiving throttle, brake and steering

Hi, I use VPilot to receive the messages to from DeepGTAV as you said, but it seems some problems happen when I receive the message. I can get the correct data such as 'frame', 'speed', 'reward' and so on, but the data of 'throttle', 'brake' and 'steering' do not reflect correctly, which is always keeping as 0 or 1. Does the game version or driving mode influence this?

git can not download the h5 file.

Git can not download the h5 file. Could you please upload the h5 file on google drive?

Version of Keras, Tensorflow

Hi， what's the version of Keras, Tensorflow. Thank you.

i tried training model on GTX 1050 but it gives error

Excepted with OOM when allocating tensor with shape[32,128,77,157] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[{{node training/Adadelta/gradients/AddN_120-0-TransposeNHWCToNCHW-LayoutOptimizer}} = Transpose[T=DT_FLOAT, Tperm=DT_INT32, _device="/job:localhost/replica:0/task:0/device:GPU:0"](training/Adadelta/gradients/block2_sepconv2_bn/cond/FusedBatchNorm/Switch_grad/cond_grad, PermConstNHWCToNCHW-LayoutOptimizer)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

 [[{{node loss/mul/_1543}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_16371_loss/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

i dont know why that error is coming

Unable to download sample model

Hi, could you rehost sample_model.h5 on Google drive. I'm unable to download it from GitHub.

Excepted as: Error when checking input: expected input_1 to have shape (80, 320, 3) but got array with shape (160, 320, 3)

Hey I get this error:
Excepted as: Error when checking input: expected input_1 to have shape (80, 320, 3) but got array with shape (160, 320, 3) do you know why ?

training fails with "Resource exhausted"

Hi,

I've tried getting this to work but got stuck in the training step. No matter how few samples in the dataset, I run out of memory even though this runs on a GTX 1070 with 8GB VRAM.
Was there a change causing it to use more memory? Is there something to tweak?
I know this here is pretty much provided 'as-is' but would be happy about any pointers.

Here is the full error:

2017-10-13 00:34:32.073550: I c:\l\work\tensorflow-1.1.0\tensorflow\core\common_runtime\bfc_allocator.cc:696] 1 Chunks of size 149082112 totalling 142.18MiB
2017-10-13 00:34:32.073739: I c:\l\work\tensorflow-1.1.0\tensorflow\core\common_runtime\bfc_allocator.cc:696] 5 Chunks of size 198066176 totalling 944.45MiB
2017-10-13 00:34:32.073941: I c:\l\work\tensorflow-1.1.0\tensorflow\core\common_runtime\bfc_allocator.cc:696] 1 Chunks of size 198066432 totalling 188.89MiB
2017-10-13 00:34:32.074106: I c:\l\work\tensorflow-1.1.0\tensorflow\core\common_runtime\bfc_allocator.cc:696] 1 Chunks of size 396130304 totalling 377.78MiB
2017-10-13 00:34:32.074279: I c:\l\work\tensorflow-1.1.0\tensorflow\core\common_runtime\bfc_allocator.cc:700] Sum Total of in-use chunks: 6.35GiB
2017-10-13 00:34:32.074451: I c:\l\work\tensorflow-1.1.0\tensorflow\core\common_runtime\bfc_allocator.cc:702] Stats:
Limit:                  6814913823
InUse:                  6814913024
MaxInUse:               6814913536
NumAllocs:                    2329
MaxAllocSize:           1624768512

2017-10-13 00:34:32.074716: W c:\l\work\tensorflow-1.1.0\tensorflow\core\common_runtime\bfc_allocator.cc:277] **************************************xx***************************x********************************
2017-10-13 00:34:32.074799: W c:\l\work\tensorflow-1.1.0\tensorflow\core\framework\op_kernel.cc:1152] Resource exhausted: OOM when allocating tensor with shape[728]
Excepted with OOM when allocating tensor with shape[728]
         [[Node: block12_sepconv1_bn/moments/sufficient_statistics/mean_ss = Sum[T=DT_FLOAT, Tidx=DT_INT32, keep_dims=false, _device="/job:localhost/replica:0/task:0/gpu:0"](block12_sepconv1_bn/moments/sufficient_statistics/Sub, block12_sepconv1_bn/moments/sufficient_statistics/mean_ss/reduction_indices)]]
         [[Node: block14_sepconv2_bn/moments/sufficient_statistics/Gather/_187 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_9496_block14_sepconv2_bn/moments/sufficient_statistics/Gather", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'block12_sepconv1_bn/moments/sufficient_statistics/mean_ss', defined at:
  File "model_xception.py", line 226, in <module>
    model = Xception(include_top=True,weights=None)
  File "model_xception.py", line 166, in Xception
    x = BatchNormalization(name=prefix + '_sepconv1_bn')(x)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\keras\engine\topology.py", line 596, in __call__
    output = self.call(inputs, **kwargs)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\keras\layers\normalization.py", line 177, in call
    epsilon=self.epsilon)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\keras\backend\tensorflow_backend.py", line 1650, in normalize_batch_in_training
    shift=None, name=None, keep_dims=False)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\tensorflow\python\ops\nn_impl.py", line 642, in moments
    y, axes, shift=shift, keep_dims=keep_dims, name=name)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\tensorflow\python\ops\nn_impl.py", line 564, in sufficient_statistics
    m_ss = math_ops.reduce_sum(m_ss, axes, keep_dims=keep_dims, name="mean_ss")
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1236, in reduce_sum
    name=name)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 2656, in _sum
    keep_dims=keep_dims, name=name)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "C:\Users\windo\AppData\Local\conda\conda\envs\santosnet\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__
    self._traceback = _extract_stack()

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[728]
         [[Node: block12_sepconv1_bn/moments/sufficient_statistics/mean_ss = Sum[T=DT_FLOAT, Tidx=DT_INT32, keep_dims=false, _device="/job:localhost/replica:0/task:0/gpu:0"](block12_sepconv1_bn/moments/sufficient_statistics/Sub, block12_sepconv1_bn/moments/sufficient_statistics/mean_ss/reduction_indices)]]
         [[Node: block14_sepconv2_bn/moments/sufficient_statistics/Gather/_187 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_9496_block14_sepconv2_bn/moments/sufficient_statistics/Gather", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Recommend Projects

React

A declarative, efficient, and flexible JavaScript library for building user interfaces.
Vue.js

🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Typescript

TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
TensorFlow

An Open Source Machine Learning Framework for Everyone
Django

The Web framework for perfectionists with deadlines.
Laravel

A PHP framework for web artisans
D3

Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

javascript

JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
web

Some thing interesting about web. New door for the world.
server

A server is a program made to process requests and deliver data to clients.
Machine learning

Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Visualization

Some thing interesting about visualization, use data art
Game

Some thing interesting about game, make everyone happy.

Recommend Org

Facebook

We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft

Open source projects and samples from Microsoft.
Google

Google ❤️ Open Source for everyone.
Alibaba

Alibaba Open Source for everyone
D3

Data-Driven Documents codes.
Tencent

China tencent open source team.