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View Code? Open in Web Editor NEWYOLO object detector for Movidius Neural Compute Stick (NCS)
License: MIT License
YOLO object detector for Movidius Neural Compute Stick (NCS)
License: MIT License
Hey there,
I noticed there is a difference between this repo's TinyYOLO model (yolo_tiny_deploy.prototxt) and the one generated by the code create_yolo_prototxt.py (i.e. the yolo_tiny_deploy.prototxt at xingwangsfu). May I ask where this repo's TinyYOLO model comes from and how can I train it?
Thank you and appreciate your help!
Hi.
Would it be possible to get the list of labels?
best regards
Facing error during compilation. Any idea on this?
Thanks for the help in advance.
mvNCCompile v02.00, Copyright @ Movidius Ltd 2016
Traceback (most recent call last):
File "/usr/local/bin/mvNCCompile", line 118, in
create_graph(args.network, args.inputnode, args.outputnode, args.outfile, args.nshaves, args.inputsize, args.weights)
File "/usr/local/bin/mvNCCompile", line 101, in create_graph
net = parse_caffe(args, myriad_config)
File "/usr/local/bin/ncsdk/Controllers/CaffeParser.py", line 365, in parse_caffe
if layers[0].type == 'Input':
IndexError: list index out of range
Hi ,
I want to convert my cfg file to prototxt format.
I use one of this dir's file(http://github.com/pjreddie/darknet/cfg/yolov1).,
then I use xingwangsfu's tools(https://github.com/xingwangsfu/caffe-yolo),but the result is not good.
Can you tell me which cfg you used?
Thanks
mvNCCompile prototxt/yolo_tiny_deploy.prototxt -w weights/yolo_tiny**_deploy**.caffemodel -s 12
EIther one needs to change the name of the weight file or use this name for downloaded weight file.
mvNCCompile prototxt/yolo_tiny_deploy.prototxt -w weights/yolo_tiny.caffemodel -s 12
Hi Everyone
I am getting error like below , could you please help me? Camera light is on and I installed OPENCV that was explained in 'http://milq.github.io/install-opencv-ubuntu-debian/' with OPTION 2. All examples work fine but I am still getting error like below. (ValueError: cannot reshape array of size 16922 into shape (7,7,2,4) this line looks like in trouble but I dont know how I can solve.)
[DEBUG/MainProcess] created semlock with handle 140701902925824
[DEBUG/MainProcess] created semlock with handle 140701902921728
[DEBUG/MainProcess] created semlock with handle 140701902917632
[DEBUG/MainProcess] Queue._after_fork()
[DEBUG/MainProcess] created semlock with handle 140701902913536
[DEBUG/MainProcess] created semlock with handle 140701902909440
[DEBUG/MainProcess] created semlock with handle 140701902905344
[DEBUG/MainProcess] Queue._after_fork()
Found stale device, resetting
Device 0 Address: 1.3.3 - VID/PID 03e7:2150
Starting wait for connect with 2000ms timeout
Found Address: 1.3.3 - VID/PID 03e7:2150
Found EP 0x81 : max packet size is 512 bytes
Found EP 0x01 : max packet size is 512 bytes
Found and opened device
Performing bulk write of 865724 bytes...
Successfully sent 865724 bytes of data in 214.364144 ms (3.851478 MB/s)
Boot successful, device address 1.3.3
Found Address: 1.3.3 - VID/PID 03e7:f63b
done
Booted 1.3.3 -> VSC
[DEBUG/MainProcess] created semlock with handle 140701902901248
[DEBUG/MainProcess] created semlock with handle 140701902897152
[DEBUG/MainProcess] created semlock with handle 140701902893056
[DEBUG/MainProcess] created semlock with handle 140701902888960
[DEBUG/MainProcess] added worker
[DEBUG/ForkPoolWorker-1] Queue._after_fork()
[DEBUG/ForkPoolWorker-1] Queue._after_fork()
[INFO/ForkPoolWorker-1] child process calling self.run()
[DEBUG/MainProcess] added worker
[DEBUG/ForkPoolWorker-2] Queue._after_fork()
[DEBUG/ForkPoolWorker-2] Queue._after_fork()
[INFO/ForkPoolWorker-2] child process calling self.run()
[DEBUG/MainProcess] Queue._start_thread()
[DEBUG/MainProcess] doing self._thread.start()
[DEBUG/MainProcess] starting thread to feed data to pipe
[DEBUG/MainProcess] ... done self._thread.start()
/usr/local/lib/python3.5/dist-packages/skimage/transform/_warps.py:84: UserWarning: The default mode, 'constant', will be changed to 'reflect' in skimage 0.15.
warn("The default mode, 'constant', will be changed to 'reflect' in "
[INFO/ForkPoolWorker-1] process shutting down
[DEBUG/ForkPoolWorker-1] running all "atexit" finalizers with priority >= 0
[DEBUG/ForkPoolWorker-1] running the remaining "atexit" finalizers
Process ForkPoolWorker-1:
Traceback (most recent call last):
File "/usr/lib/python3.5/multiprocessing/process.py", line 249, in _bootstrap
self.run()
File "/usr/lib/python3.5/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/usr/lib/python3.5/multiprocessing/pool.py", line 103, in worker
initializer(*initargs)
File "py_examples/object_detection_app.py", line 115, in worker
results = interpret_output(out.astype(np.float32), frame.shape[1], frame.shape[0])
File "py_examples/object_detection_app.py", line 55, in interpret_output
boxes = (np.reshape(output[1078:],(7,7,2,4)))
File "/usr/local/lib/python3.5/dist-packages/numpy/core/fromnumeric.py", line 232, in reshape
return _wrapfunc(a, 'reshape', newshape, order=order)
File "/usr/local/lib/python3.5/dist-packages/numpy/core/fromnumeric.py", line 57, in _wrapfunc
return getattr(obj, method)(*args, **kwds)
ValueError: cannot reshape array of size 16922 into shape (7,7,2,4)
[INFO/ForkPoolWorker-1] process exiting with exitcode 1
[DEBUG/MainProcess] cleaning up worker 0
[Level 5/MainProcess] finalizer calling with args (19,) and kwargs {}
[DEBUG/MainProcess] added worker
[DEBUG/ForkPoolWorker-3] Queue._after_fork()
[DEBUG/ForkPoolWorker-3] Queue._after_fork()
[INFO/ForkPoolWorker-3] child process calling self.run()
Hi there i wanted to convert tiny yolo cfg to yolo prototxt but i am getting this error.
configparser.DuplicateOptionError: While reading from 'tiny-yolo-azface-fddb.cfg' [line 44]: option 'batch_normalize' in section 'convolutional' already exists
Are the pretrained weights generated by using create_yolo_caffemodel.py
?
If I want to train the model on my own what would the process be? Should I first train yolo by darknet and then use create_yolo_caffemodel.py
and create_yolo_prototxt.py
?
How can I load several models simultaneously?
Hello,
First of all, thank you for the project. I already installed the project and compiled everything. The problem is when I try to run 'python3 py_examples/yolo_example.py images/dog.jpg' I get the following error:
Device 0 Address: 3 - VID/PID 03e7:2150
Starting wait for connect with 2000ms timeout
Found Address: 3 - VID/PID 03e7:2150
Found EP 0x81 : max packet size is 512 bytes
Found EP 0x01 : max packet size is 512 bytes
Found and opened device
Performing bulk write of 865212 bytes...
Successfully sent 865212 bytes of data in 457.894553 ms (1.802010 MB/s)
Boot successful, device address 3
Found Address: 3 - VID/PID 03e7:f63b
done
Booted 3 -> VSC
Traceback (most recent call last):
File "py_examples/yolo_example.py", line 126, in
graph = device.AllocateGraph(blob)
File "/usr/local/lib/python3.5/dist-packages/mvnc/mvncapi.py", line 201, in AllocateGraph
raise Exception(Status(status))
Exception: mvncStatus.ERROR
Any suggestions? I do have the 'graph' file in the main folder. Thanks again!
Hi,
I just bought the Movidius stick and installed ncsdk 1.09 release. Seems the structure has changed a lot. Command line for mvNCCompile is different, and i cannot find the directory for ncapi/networks/YoloTiny/ . Could you please provide suggestions that how I can run tiny yolo in ncsdk1.09 please?
Hey, I am getting an error loading this.
[DEBUG/MainProcess] added worker
[DEBUG/ForkPoolWorker-2] Queue._after_fork()
[DEBUG/ForkPoolWorker-2] Queue._after_fork()
[INFO/ForkPoolWorker-2] child process calling self.run()
[DEBUG/MainProcess] Queue._start_thread()
[DEBUG/MainProcess] doing self._thread.start()
[DEBUG/MainProcess] starting thread to feed data to pipe
[DEBUG/MainProcess] ... done self._thread.start()
[INFO/ForkPoolWorker-1] process shutting down
[DEBUG/ForkPoolWorker-1] running all "atexit" finalizers with priority >= 0
[DEBUG/ForkPoolWorker-1] running the remaining "atexit" finalizers
Process ForkPoolWorker-1:
Traceback (most recent call last):
File "/usr/lib/python3.5/multiprocessing/process.py", line 249, in _bootstrap
self.run()
File "/usr/lib/python3.5/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/usr/lib/python3.5/multiprocessing/pool.py", line 103, in worker
initializer(*initargs)
File "object_detection_app.py", line 113, in worker
graph.LoadTensor(resize(frame/255.0,dim,1)[:,:,(2,1,0)].astype(np.float16), 'user object')
TypeError: unsupported operand type(s) for /: 'NoneType' and 'float'
[INFO/ForkPoolWorker-1] process exiting with exitcode 1
[DEBUG/MainProcess] cleaning up worker 0
[Level 5/MainProcess] finalizer calling <built-in function close> with args (18,) and kwargs {}
[DEBUG/MainProcess] added worker
[DEBUG/ForkPoolWorker-3] Queue._after_fork()
[DEBUG/ForkPoolWorker-3] Queue._after_fork()
[INFO/ForkPoolWorker-3] child process calling self.run()
Let me know if you can help
Hi I want to use this TinyYolo model but want it only for some other specified categories.
Can you give me some instructions on how can I retrain and compile it?
File " ./YoloV2NCS/detectionExample/ObjectWrapper.py", line 101, in Detect
ObjectWrapper.fifoInHandle[i],
NameError: name 'i' is not defined
The single image test works.
This appears to be a video capture issue.
The object detection is producing a graph.LoadTensor error
[INFO/ForkPoolWorker-1] process shutting down
[DEBUG/ForkPoolWorker-1] running all "atexit" finalizers with priority >= 0
[DEBUG/ForkPoolWorker-1] running the remaining "atexit" finalizers
Process ForkPoolWorker-1:
Traceback (most recent call last):
File "/usr/lib/python3.5/multiprocessing/process.py", line 249, in _bootstrap
self.run()
File "/usr/lib/python3.5/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/usr/lib/python3.5/multiprocessing/pool.py", line 103, in worker
initializer(*initargs)
File "py_examples/object_detection_app.py", line 113, in worker
graph.LoadTensor(resize(frame/255.0,dim,1)[:,:,(2,1,0)].astype(np.float16), 'user object')
TypeError: unsupported operand type(s) for /: 'NoneType' and 'float'
[INFO/ForkPoolWorker-1] process exiting with exitcode 1
[DEBUG/MainProcess] cleaning up worker 0
[Level 5/MainProcess] finalizer calling <built-in function close> with args (18,) and kwargs {}
[DEBUG/MainProcess] added worker
[DEBUG/ForkPoolWorker-3] Queue._after_fork()
[DEBUG/ForkPoolWorker-3] Queue._after_fork()
[INFO/ForkPoolWorker-3] child process calling self.run()
pi@raspberrypi:~/YoloV2NCS-1.0 $ python3 detectionExample/Main.py
Traceback (most recent call last):
File "detectionExample/Main.py", line 5, in
from ObjectWrapper import *
File "/home/pi/YoloV2NCS-1.0/detectionExample/ObjectWrapper.py", line 1, in
from libpydetector import YoloDetector
ImportError: /home/pi/YoloV2NCS-1.0/detectionExample/libpydetector.so: wrong ELF class: ELFCLASS64
I compiled it on another box a move the files, created the lync
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