Upgrade Tensorflow Version tflite-server
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Netron Tflite Model In/Output Formats:
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Output of Installation of tflite-server 0.2.0 from dev branch:
Output:voxl:~$ opkg install voxl-tflite-server Upgrading voxl-tflite-server from 0.1.6 to 0.2.0 on root. Downloading http://voxl-packages.modalai.com/dev/voxl-tflite-server_0.2.0_202202202255.ipk. Installing libmodal-pipe (2.1.4) on root. Downloading http://voxl-packages.modalai.com/dev/libmodal-pipe_2.1.4_202202040134.ipk. Installing libmodal-json (0.4.0) on root. Downloading http://voxl-packages.modalai.com/dev/libmodal-json_0.4.0_202202080557.ipk. To remove package debris, try `opkg remove libmodal-json`. To re-attempt the install, try `opkg install libmodal-json`. Collected errors: * check_data_file_clashes: Package libmodal-json wants to install file /usr/lib64/libmodal_json.so But that file is already provided by package * libmodal_json * check_data_file_clashes: Package libmodal-json wants to install file /usr/include/cJSON.h But that file is already provided by package * libmodal_json * check_data_file_clashes: Package libmodal-json wants to install file /usr/include/modal_json.h But that file is already provided by package * libmodal_json * check_data_file_clashes: Package libmodal-json wants to install file /usr/lib/libmodal_json.so But that file is already provided by package * libmodal_json * check_data_file_clashes: Package libmodal-json wants to install file /usr/bin/modal-test-json But that file is already provided by package * libmodal_json * opkg_install_cmd: Cannot install package voxl-tflite-server.
This does not work:
opkg remove libmodal-json opkg install libmodal-json
But when trying to install again:
voxl:~$ opkg install voxl-tflite-server Upgrading voxl-tflite-server from 0.1.6 to 0.2.0 on root. Installing voxl-opencv (4.5.5) on root.
it installed succesfully
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Have been trying around some other models and got some funny confidences:
Detected: 0 person, Confidence: 10.00 Detected: 0 person, Confidence: 0.68 Detected: 0 person, Confidence: 0.73 Detected: 0 person, Confidence: 2.63 Detected: 0 person, Confidence: 1.24 Detected: 0 person, Confidence: 0.98 Detected: 0 person, Confidence: 2.23 Detected: 0 person, Confidence: 0.87 Detected: 0 person, Confidence: 1.26 Detected: 0 person, Confidence: 0.74 Detected: 0 person, Confidence: 0.72 Detected: 0 person, Confidence: 1.34 Detected: 0 person, Confidence: 1.82 Detected: 0 person, Confidence: 0.67 Detected: 0 person, Confidence: 1.50 Detected: 0 person, Confidence: 0.74 Detected: 0 person, Confidence: 1.37 Detected: 0 person, Confidence: 0.89 Detected: 0 person, Confidence: 1.56 Fault address: 0x20 Unknown reason. Segmentation fault
didn't know that you can have a confidence of 1000%
Model: SSD ResNet101 V1 FPN 640x640 -
Let me try to address these individually!
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CUSTOM TFLite_Detection_PostProcess: Operation is not supported.
is simply due to the very last operation of the model not being supported for gpu delegation. This is because it is not a standard op, so it just gets delegated to the cpu with no issues!
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The issue with tflite-server hanging is not due to an improper install. I was able to replicate this on my setup using a BAD apm, but swapping out with a new one seemed to alleviate this issue. voxl-tflite-server is a fairly power hungry application, so I recommend checking for fraying cables and things of that nature but if you can send a picture of your current setup with cables/batteries etc included that may help debug. In the meantime, if you have another apm or power supply to quickly swap to and test please give that a try.
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I personally have not had much luck with the resnet architectures, but I would double check data types and output tensor lengths, because those confidence values seem way off.
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One last note, the dev release does not directly support all image formats out of voxl-uvc-server, only IMAGE_FORMAT_NV12 as of now. So, if your camera input is coming in as either IMAGE_FORMAT_YUV422 or IMAGE_FORMAT_YUV422_UYVY you may need to add some extra handling for that.
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@Matt-Turi thank you for the fast reply again. I will check the apm and Camera server output format tomorrow and also send you a picture of the setup.
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@Matt-Turi I got it working with changing the apm. Thank you for the suggestion. So i looked up my Camera Supports and it should support nv12 and in voxl-uvc-server it shows the following:
uvc_get_stream_ctrl_format_size succeeded for format 2
after looking at the voxl-uvc-server:
https://gitlab.com/voxl-public/modal-pipe-architecture/voxl-uvc-server/-/blob/dev/src/main.c
L: 307 There is a for loop looking for a format to choose and format 2 should be NV12 but for some reason when looking at the stream over voxl-portal i get green stripes in the ouput. Do you know what the problem could be?The Camera is a Boson 640 Black-White Thermal Camera.
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Here is a Picture of the green stripes:
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@Philemon-Benner Can you post the output of
lsusb
,voxl-uvc-server -s
, andvoxl-uvc-server -d -m -r 640x512
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@Eric-Katzfey
lsusb:Bus 004 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub Bus 002 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 003 Device 002: ID 09cb:4007 Bus 003 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub
voxl-uvc-server -s:
*** START DEVICE LIST *** Found device 1 Got device descriptor for 09cb:4007 134275 Found device 09cb:4007 DEVICE CONFIGURATION (09cb:4007/134275) --- Status: idle VideoControl: bcdUVC: 0x0100 VideoStreaming(1): bEndpointAddress: 129 Formats: UncompressedFormat(1) bits per pixel: 12 GUID: 4934323000001000800000aa00389b71 (I420) default frame: 1 aspect ratio: 0x0 interlace flags: 00 copy protect: 00 FrameDescriptor(1) capabilities: 02 size: 640x512 bit rate: 10592000-235929600 max frame size: 491520 default interval: 1/60 interval[0]: 1/60 interval[1]: 1/30 UncompressedFormat(2) bits per pixel: 16 GUID: 5931362000001000800000aa00389b71 (Y16 ) default frame: 1 aspect ratio: 0x0 interlace flags: 00 copy protect: 00 FrameDescriptor(1) capabilities: 02 size: 640x512 bit rate: 10592000-629145600 max frame size: 655360 default interval: 1/60 interval[0]: 1/60 interval[1]: 1/30 UncompressedFormat(3) bits per pixel: 12 GUID: 4e56313200001000800000aa00389b71 (NV12) default frame: 1 aspect ratio: 0x0 interlace flags: 00 copy protect: 00 FrameDescriptor(1) capabilities: 02 size: 640x512 bit rate: 10592000-235929600 max frame size: 491520 default interval: 1/60 interval[0]: 1/60 interval[1]: 1/30 UncompressedFormat(4) bits per pixel: 12 GUID: 4e56323100001000800000aa00389b71 (NV21) default frame: 1 aspect ratio: 0x0 interlace flags: 00 copy protect: 00 FrameDescriptor(1) capabilities: 02 size: 640x512 bit rate: 10592000-235929600 max frame size: 491520 default interval: 1/60 interval[0]: 1/60 interval[1]: 1/30 END DEVICE CONFIGURATION *** END DEVICE LIST ***
voxl-uvc-server -d -m -r 640x512:
Enabling debug messages Enabling MPA debug messages voxl-uvc-server starting Image resolution 640x512, 30 fps chosen UVC initialized Device found Device opened uvc_get_stream_ctrl_format_size succeeded for format 2 Streaming starting Got frame callback! frame_format = 17, width = 640, height = 512, length = 491520, ptr = (nil) making new fifo /run/mpa/uvc/voxl-tflite-server0 opened new pipe for writing after 3 attempt(s) write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 1 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 * got image 30 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 40 errno: 0 previous client state was 2 write to ch: 0 id: 0 result: 491520 errno: 0
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Just checked the camera on my laptop. Camera it self is working fine
It's also working fine with nv12 format without the green lines:ffplay /dev/video4 -pixel_format nv12
Output:
Input #0, video4linux2,v4l2, from '/dev/video4':B sq= 0B f=0/0 Duration: N/A, start: 33575.082223, bitrate: 235929 kb/s Stream #0:0: Video: rawvideo (NV12 / 0x3231564E), nv12, 640x512, 235929 kb/s, 60 fps, 60 tbr, 1000k tbn, 1000k tbc
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@Philemon-Benner It looks like voxl-uvc-server is working fine. The error messages seem to be related to voxl-tflite-server and not voxl-uvc-server. Can you use voxl-streamer to stream the output of voxl-uvc-server to VLC and see if there are still green lines? What are you currently using to stream the output of voxl-uvc-server?
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@Philemon-Benner I'm guessing that there may be a version mismatch somewhere in there.
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@Eric-Katzfey Yeah i will try that today. I'm currently showing the stream with voxl Portal but with the voxl-tflite-server pipe. So voxl-uvc-server --> voxl-tflite-server --> voxl-portal(green lines output).
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@Eric-Katzfey what a exactly do you mean with version mismatch, and where. The thing i could think of is tflite server 0.2.0 as seen above in the first try of installation i had some errors because of existing dependencies.
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@Eric-Katzfey Ok so i tried using it with voxl-streamer. It's working completely fine. Any suggestions?
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I also tried changing the model but still the same result.
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Update:
So i stepped back to TF1 and trained the ssdlite_mobilenet_v2. It's working great on the drone with tflite-server 0.1.8. Thanks for all the suggestions ·@Matt-Turi . But i am looking forward to using the tflite-server 0.2.0. If you still have suggestions for fixing the green stripes in the new version please let me know, because for custom models the new tflite-version is way easier to integrate and the code is more understandable for me. -
@Philemon-Benner Thanks for the follow up on this! We'll take a look.
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@Matt-Turi is there a way to change small stuff in tflite-server code without building from source? Or is there a way to do it over ssh?. I can't access the usb slot from the voxl of the drone. I just wanna change the box color and confidence threshhold.
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@Philemon-Benner If you make any changes to the code you will need to rebuild it from source. Once built, you can push this package over ssh either manually or using the deploy_to_voxl.sh script that is up on dev, which has an arg for ssh and send ip. Lines 106 and 107 of the script have the scp and opkg install commands that are used.