stanford-futuredata / noscope Goto Github PK
View Code? Open in Web Editor NEWAccelerating network inference over video
Home Page: http://dawn.cs.stanford.edu/2017/06/22/noscope/
Accelerating network inference over video
Home Page: http://dawn.cs.stanford.edu/2017/06/22/noscope/
Once NoScope optimized the model for a video, can it output the optimized model so I can use it to process more videos from the same fixed camera without having to optimize again for each video? For instance, I have 5 videos from the same camera. NoScope found the optimized model from the 1st video, then how to run that model for the remaining 4 videos without the optimization again? Thank you!
I have installed tensorflow-noscope and noscope by following the instruction. When I run
noscope/example/run.sh
It complained:
ImportError: No module named noscope
ImportError: No module named tensorflow
So what did I miss to have python finds noscope and tensorflow?
Thanks,
Jan
<Code>AccessDenied</Code>
<Message>Access denied.</Message>
<Details>
Anonymous users does not have storage.objects.get access to noscope-data/videos/VIDEO_NAME.mp4.
</Details>
</Error>
Could I obtain the data set by other means?
Hi all
Just found the repo from the original publication. I am wondering if this project is ready to test or demo. It seems like there is no documentation and there are no commits in the last four months.
Hi,
I tried to download the dataset using gsutil
, below is the bash scripts I have.
gsutil -u downloadtest-249815 cp gs://noscope-data/csvs-yolo/coral-reef-long.csv .
However, I got the following error message,
AccessDeniedException: 403 [email protected] does not have storage.objects.list access to noscope-data.
I wonder is there anything wrong with my method? Or do I need to first get permission from somewhere else before downloading the related dataset?
Thanks,
Bo
I finally got NoScope running on my Linux with 2 GPUs. To help me understand NoScope better, I have the following questions:
Thanks!
Jan
when i run
bazel build -c opt --copt=-mavx2 --config=cuda noscope
i got some error
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/activation_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/activation_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/avgpool_layer_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/avgpool_layer_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/blas_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/blas_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/col2im_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/col2im_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/convolutional_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/convolutional_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/crop_layer_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/crop_layer_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/deconvolutional_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/deconvolutional_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/dropout_layer_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/dropout_layer_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/im2col_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/im2col_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/maxpool_layer_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/maxpool_layer_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: file '//tensorflow/noscope/darknet:src/network_kernels.cu' is misplaced here (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: in srcs attribute of cc_library rule //tensorflow/noscope/darknet:yolo_gpu: '//tensorflow/noscope/darknet:src/network_kernels.cu' does not produce any cc_library srcs files (expected .cc, .cpp, .cxx, .c++, .C, .c, .h, .hh, .hpp, .hxx, .inc, .S, .s, .asm, .a, .lib, .pic.a, .lo, .pic.lo, .so, .dylib, .dll, .o or .pic.o). Since this rule was created by the macro 'tf_kernel_library', the error might have been caused by the macro implementation in /home/zjc/DeepLearning/tensorflow-noscope/tensorflow/tensorflow.bzl:634:12.
ERROR: Analysis of target '//tensorflow/noscope:noscope' failed; build aborted.
can someone help me fix this?
hi all
i run : git submodule init git submodule update
but i got an error
fatal: reference is not a tree: d3ea51f6bbe3e20d37b5b449f15903f2a5a7a37d
Unable to checkout 'd3ea51f6bbe3e20d37b5b449f15903f2a5a7a37d' in submodule path 'tensorflow/noscope/darknet'
no any code in darknet
thank your help
Hi Daniel,
I am really interested in integrating your system into Deep Video Analytics by combining the difference detector with segmented video to make the system a lot more memory efficient. I had few questions:
How long does it takes to train the frame-difference -> label model?
Is this model trained continuously or is it trained once per video stream/background?
Can this system be used for video feeds where background is NOT constant?
Is there any Open Source license associated with the codebase?
Thanks,
This job is very great, and the paper also enlightening!!
I want to try it, but I don`t know how to run it. Could you update some demo or illustrate for this?
thank you
hi there! Thank you for your great work in this detection mission. It was inspiring. I was trying to reproduce it. I followed every step but the opencv version. Could it be the reason for the resize error ?
cv2.error: OpenCV(3.4.3) /io/opencv/modules/imgproc/src/resize.cpp:4044: error: (-215:Assertion failed) !ssize.empty() in function 'resize'
I am trying to download the dataset but the given link is not working for me? anyone has updated link. it would be nice to have it for experiment purpose.
Thank You
Error:
(tfg) [root@pinky csv]# wget https://storage.googleapis.com/noscope-data/videos/coral-reef-long.mp4
--2019-07-11 11:47:41-- https://storage.googleapis.com/noscope-data/videos/coral-reef-long.mp4
Resolving storage.googleapis.com (storage.googleapis.com)... 2a00:1450:4001:817::2010, 172.217.21.208
Connecting to storage.googleapis.com (storage.googleapis.com)|2a00:1450:4001:817::2010|:443... connected.
HTTP request sent, awaiting response... 400 Bad Request
2019-07-11 11:47:42 ERROR 400: Bad Request.
Thanks very much!
def get_feature_and_dist_fns(feature_type):
if feature_type == 'hog':
return (HOG.compute_feature, HOG.get_distance_fn, HOG.DIST_METRICS)
elif feature_type == 'sift':
return (SIFT.compute_feature, SIFT.get_distance_fn, SIFT.DIST_METRICS)
elif feature_type == 'ch':
return (ColorHistogram.compute_feature, ColorHistogram.get_distance_fn, ColorHistogram.DIST_METRICS)
elif feature_type == 'raw':
return (RawImage.compute_feature, RawImage.get_distance_fn, RawImage.DIST_METRICS)
import cv2
import numpy as np
from scipy.spatial.distance import euclidean, cityblock, chebyshev, cosine
DIST_METRICS = [
('euclidean', euclidean),
('manhattan', cityblock),
('chebyshev', chebyshev),
('cosine', lambda x, y: -1*cosine(x, y)),
#('chisqr', lambda x, y: cv2.compareHist(x, y, cv2.HISTCMP_CHISQR)),
#('bhatta', lambda x, y: cv2.compareHist(x, y, cv2.HISTCMP_BHATTACHARYYA))
]
def compute_feature(frame):
sift = cv2.xfeatures2d.SIFT_create()
image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
_, des = sift.detectAndCompute(image, None)
if des is not None:
return np.mean(des, axis=0).astype('float32')
else:
return np.zeros(128)
SIFT difinition no SIFT.get_distance_fn
Unable to build using bazel
While running
bazel build -c opt --copt=-mavx2 --config=cuda --verbose_failures --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" noscope
Error : js_embed: symbol _ZNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEE9_M_createERmm, version GLIBCXX_3.4.21 not defined in file libstdc++.so.6 with link time reference
when i run VUSELabeler.py,it says no YOLO attribut, it seems that the YOLO class is missing under noscop dir:
ubuntu@XP1:~/cvs/noscope$ python scripts/VUSELabeler.py Using TensorFlow backend. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally Traceback (most recent call last): File "scripts/VUSELabeler.py", line 85, in <module> main() File "scripts/VUSELabeler.py", line 79, in main args.yolo_dir, args.start_from) File "scripts/VUSELabeler.py", line 38, in label_video yolo_dir + '/cfg/coco.data') File "scripts/VUSELabeler.py", line 15, in __init__ self.YOLO = noscope.YOLO(config_filename, weights_filename, data_config) AttributeError: 'module' object has no attribute 'YOLO'
when I do "git submodule update", I get this error:
fatal: reference is not a tree: d3ea51f6bbe3e20d37b5b449f15903f2a5a7a37d
Unable to checkout 'd3ea51f6bbe3e20d37b5b449f15903f2a5a7a37d' in submodule path 'tensorflow/noscope/darknet'
Could you please help me.
I see this in noscope_motherdog.py:
YOLO_LABELS["coral-reef-long"] = (
0,
[("coral-reef-long_convnet_32_32_1.pb", None),
("coral-reef-long_convnet_32_32_2.pb", None),],
648000 + 1188000,
1188000,
648000 + 1188000 * 2,
1188000
)
So what do those numbers mean? Is there a document explaining those?
I really need to understand those so I can add my own
YOLO_LABELS["my-video"] session with the correct numbers to have Yolo process my video.
Right now, Yolo is not processing my video correctly because those numbers are not setup right.
read the noscope article it's a good idea to add a difference detector on top of Object Detector since my project uses the scene cut detection to reduce the computation but on the other hand losing many important frames.
rt, can you tell me what the protobuf version it need?Thank you very much.
I was looking into the scripts and hope that I can find there something that could help to visualize testing results (draw bounding boxes on frames just like in the article on that GIFs animations), but haven't found it. Is there such a tool in the source code or not?
Can you provide the instructions on how to run the demo include train and detect?
GTX1070:7.9G memory
when i run_optimizerset.sh,the train_9180_18360.log displayed errors.
train_9180_18360.log:
2017-08-28 17:31:50.229531: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2017-08-28 17:31:50.351945: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2017-08-28 17:31:50.352224: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties:
name: GeForce GTX 1070
major: 6 minor: 1 memoryClockRate (GHz) 1.8225
pciBusID 0000:01:00.0
Total memory: 7.92GiB
Free memory: 7.31GiB
2017-08-28 17:31:50.352235: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0
2017-08-28 17:31:50.352240: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y
2017-08-28 17:31:50.352249: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1070, pci bus id: 0000:01:00.0)
layer filters size input output
0 CUDA Error: out of memory: File exists
CUDA Error: out of memory
First,Thank you for contributing the code.When i read the Models.py,i have a problem that i can't understand.
in noscope/Models.py,the function of try_params(...),in line 305
nb_classes means the number of the classes,but params[1] is member of list(itertools.product( *[[X_train.shape[1:]], [nb_classes],[32, 64, 128, 256], [32], [0, 1, 2]])),
so params[1]=[(50,50,3),2,32,32,1]
why nb_classes = params[1]?I think nb_classes=params[1][2],because params[1][2] is [nb_classes].
am I wrong?if i am wrong,please help me understand it,thank you!
Hi, all
It seems that the link for the video is unavailable at this time. Can anybody send me a new link about the video source?
Many thanks!!
Firstly, thanks a lot for updating your tutorial in time , and i follow your steps which you required.
Everything seems good until the error appears:
and in that directory i only to find as following:
it generate the train_918000_1836000.log but no train_918000_1836000.csv
I do not know where the problem is,can you help me?
(PS:for the mp4 is too large, i just cut it to 3000 frames and i also changge the NUM_FRAMES="3000")
When I run python VUSELabeler.py --yolo_dir /path/to/darkflow --output_csv_fname /path/to/output.csv --input_video_fname /path/to/output.avi --start_from 0
it throws an error:
Using TensorFlow backend.
Traceback (most recent call last):
File "VUSELabeler.py", line 85, in <module>
main()
File "VUSELabeler.py", line 79, in main
args.yolo_dir, args.start_from)
File "VUSELabeler.py", line 38, in label_video
yolo_dir + '/cfg/coco.data')
File "VUSELabeler.py", line 15, in __init__
self.YOLO = noscope.YOLO(config_filename, weights_filename, data_config)
AttributeError: 'module' object has no attribute 'YOLO'
I am very interested in this approach. Is it possible to share the demo which you did on the paper?
When I run Visualizer.py for (jackson-town-square.mp4 + jackson-town-square.csv), the script throws an error:
Traceback (most recent call last):
File "/opt/pycharm-2017.2.2/helpers/pydev/pydevd.py", line 1596, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "/opt/pycharm-2017.2.2/helpers/pydev/pydevd.py", line 1023, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "/home/user/noscope/noscope/Visualizer.py", line 81, in <module>
main()
File "/home/user/noscope/noscope/Visualizer.py", line 77, in main
draw_video(args.input_csv, args.video_in, nb_frames, args.start_frame, objects)
File "/home/user/noscope/noscope/Visualizer.py", line 56, in draw_video
if label['object_name'] not in OBJECTS:
TypeError: string indices must be integers, not str
The code in that place looks strange as you're trying to enumerate the pandas dataframe instead of df.iterrows()
:
for i, labels in enumerate(all_labels):
if i % 500 == 0:
print i
for label in labels:
if label['object_name'] not in OBJECTS:
continue
draw_label(label, frame, obj_to_color[label['object_name']])
vout.write(frame)
ret, frame = cap.read()
As a result in for loop the variable labels
is a string and is equal to "object_name" and the further iteration over it iterates over the string.
pandas version: 0.20.3
python version: 2.7.6
when I run the run.sh i meet with the following issue:
which shows that there are some problems in noscope_motherdog.py , so i open the py and find the related code, as is following:
and i think the code tells that if i have no experiment_dir ,it will make it automatically, but the fact is that though it print the sentence as following:
but there is no directory generated in fact,so when it run the code "os.chdir( experiment_dir )", it raise the issue ,i am not sure how to debug it,can you help me?
when I run the run.sh, after 'Generate the models', 'Convert keras models to TF models', 'Generate the avg' were done and the 'Run the inference' was just start, i meet with the following issue
Could you let me know the 'train_918000_1836000.csv' was created in which step or place? And what's the possible reasons that created this problem, because the several steps before that were executed successfully. Thank you.
First my video TimeSquare.mp4 is 29 minutes, is that long enough for NoScope study?
How to create the TimeSquare.csv required by NoScope?
Thanks!
Hi all:
After reading the paper, I still don't know why this framework is called NoScope.
Is it some kind of abbreviation?
I am not sure whether I fully digested this work. Is this work NoScope can replace YOLO v2 but reach much higher speed? The most important question I am concerned is that, YOLO v2 can not only detect whether a frame have a bus, but also can give the position and rectangle where the bus is.
Can NoScope give the position and rectangle where the bus is? Or NoScope can only classify whether a frame have or not have a bus?
The detection position is very important for our lab, so we hope we can know whether NoScope can provide detection rectangles.
Thank you!
I am trying to use GCP and gsutil to download the dataset but I couldn't find any instructions on how to do that. I already enabled the billing account on GCP and when I am trying this command gsutil -u enduring-maxim-269304 cp gs://noscope-data/csvs-yolo/coral-reef-long.csv ~/Downloads/noscope-data
, it gives me this error 'AccessDeniedException: 403 [email protected] does not have storage.objects.list access to noscope-data'. Can you please provide some basic instructions on how to download them.
Bests
Thanks
I’m having the following issue when running the bazel build -c opt --copt=-mavx2 --config=cuda noscope
INFO: From Compiling tensorflow/noscope/darknet/src/yolo.cu.cc:
tensorflow/noscope/darknet/src/yolo.cu.cc(36): error: namespace "std" has no member "runtime_error"
tensorflow/noscope/darknet/src/yolo.cu.cc(57): error: namespace "std" has no member "runtime_error"
2 errors detected in the compilation of "/tmp/tmpxft_00016431_00000000-10_yolo.cu.compute_52.cpp1.ii".
ERROR: /home/five/PycharmProjects/chenglin/dataset/IPIU/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: output 'tensorflow/noscope/darknet/_objs/yolo_gpu/tensorflow/noscope/darknet/src/yolo.cu.o' was not created.
ERROR: /home/five/PycharmProjects/chenglin/dataset/IPIU/tensorflow-noscope/tensorflow/noscope/darknet/BUILD:10:1: not all outputs were created or valid.
Target //tensorflow/noscope:noscope failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 8.297s, Critical Path: 7.96s
Has anyone seen this error before? Please help me,Thank you
when i use the command bazel build -c opt --copt=-mavx2 --config=cuda noscope
and everything is fine but i meet this issue
and then i use the command bazel build -c opt --copt=-mavx2 --config=cuda noscope -lopencv_core and have no command,i don not know how ti fix it
when i use the command ./configure
i decide not to build TensorFlow with OpenCL support,i do not know if it matters.
As the training file is required in noscope_optimizer.py, I can not find a way to produce the file. Can you please give me some hints? Thank you
Closed: I found out that my GPU doesn't support AVX2
I tried to download the dataset using gsutil
I have opened a new google cloud account. And I can create a bucket with the command:
gsutil -u download-255905 mb gs://wtx8887-download/
However, when I want to download the dataset, (using the bash scripts like #47 )
gsutil -u download-255905 cp gs://noscope-data/csvs-yolo/coral-reef-long.csv .
I faced issue as below,
AccessDeniedException: 403 The project to be billed is associated with a closed billing account.
I checked my account, its Statu was Active.
I wonder that is there anything wrong with my method?
Thanks.
I am experimenting with different types of difference detectors that I would like to contribute to the noscope project. Is there a chance that you can share the rest of the 6 videos studied in the paper so that I can make comprehensive comparison between the difference detectors ?
It would be great if the code could be made py3 compatible. The current blockers are the print commands and the relative imports
I noticed that NoScope needs CSV with ground truth labels along with the video as input.
Two questions:
Is the ground truth for the entire video or just for the beginning part of the video? If it is only for partial video, what is that partial, for example, the first half of the video or first 20% of the video (in time) or a percentage like that? That will help me to prepare my CSV.
If the ground truth is for the entire video, does NoScope really use all the ground truth? If so, what is the purpose of processing if all the ground truth is known as input?
Thanks!
Jan
Hi, this work is so attractive in video detection mission. Just want to know if this code can be used in CPU? Plus, can I simply add the yolo3 module in this code?
Thank you!
hello there,
I was trying to reproduce the noscope and met the problem:
OpenCV Error: Assertion failed (ssize.width > 0 && ssize.height > 0) in resize, file /root/opencv/modules/imgproc/src/resize.cpp, line 3289
terminate called after throwing an instance of 'cv::Exception'
what(): /root/opencv/modules/imgproc/src/resize.cpp:3289: error: (-215) ssize.width > 0 && ssize.height > 0 in function resize
Any help?
Thanks in advance.
I am confused how does this system can use up to 300+GB of memory ?
when i run
bazel build -c opt --copt=-mavx2 --config=cuda noscope
i got some error
ERROR: /home/user08/video_object_detection/noscope/tensorflow-noscope/tensorflow/stream_executor/BUILD:39:1: C++ compilation of rule '//tensorflow/stream_executor:cuda_platform' failed (Exit 1).
tensorflow/stream_executor/cuda/cuda_dnn.cc: In instantiation of 'cudnnStatus_t perftools::gputools::cuda::wrap::WrapperShim__cudnnSetRNNDescriptor::operator()(perftools::gputools::cuda::CUDAExecutor*, Args ...) [with Args = {cudnnRNNStruct*, int, int, cudnnDropoutStruct*, cudnnRNNInputMode_t, cudnnDirectionMode_t, cudnnRNNMode_t, cudnnDataType_t}]':
tensorflow/stream_executor/cuda/cuda_dnn.cc:1017:50: required from here
tensorflow/stream_executor/cuda/cuda_dnn.cc:139:38: error: cannot convert 'cudnnRNNStruct*' to 'cudnnHandle_t {aka cudnnContext*}' for argument '1' to 'cudnnStatus_t cudnnSetRNNDescriptor(cudnnHandle_t, cudnnRNNDescriptor_t, int, int, cudnnDropoutDescriptor_t, cudnnRNNInputMode_t, cudnnDirectionMode_t, cudnnRNNMode_t, cudnnRNNAlgo_t, cudnnDataType_t)'
cudnnStatus_t retval = ::__name(args...);
^
tensorflow/stream_executor/cuda/cuda_dnn.cc:233:3: note: in expansion of macro 'PERFTOOLS_GPUTOOLS_CUDNN_WRAP'
__macro(cudnnSetRNNDescriptor)
^
tensorflow/stream_executor/cuda/cuda_dnn.cc:238:1: note: in expansion of macro 'CUDNN_DNN_ROUTINE_EACH_R5'
CUDNN_DNN_ROUTINE_EACH_R5(PERFTOOLS_GPUTOOLS_CUDNN_WRAP)
^
In file included from tensorflow/stream_executor/cuda/cuda_dnn.cc:42:0:
bazel-out/local_linux-opt/genfiles/external/local_config_cuda/cuda/cuda/include/cudnn.h:1507:8: note: class type 'cudnnRNNStruct' is incomplete
struct cudnnRNNStruct;
^
can someone help me fix this?
I was having problems with both 0.5.4 which is what I guess the authors used back then and 0.10.0. They have different problems.
Just wondering which version did you guys use and successfully build it?
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.