debian@beaglebone:/var/lib/cloud9$ uname -r 4.14.108-ti-r119
On Thursday, October 24, 2019 at 8:51:51 PM UTC-4, jonnymo wrote: > > Dobrin, > > Are you running the 4.14 or 4.19 kernel? > > > Cheers, > > Jon > > On Thursday, October 24, 2019, Dobrin Alexiev <dobri...@gmail.com > <javascript:>> wrote: > >> Thank you, Jason. >> >> Applying the changes made the classification demo reliably working. >> >> No crashes. >> >> Dobrin >> >> >> >> On Wednesday, October 23, 2019 at 11:20:21 AM UTC-4, Jason Kridner wrote: >>> >>> Sorry about that. I broke the example. I've updated it and it should >>> work now. >>> >>> >>> https://github.com/beagleboard/cloud9-examples/commit/210388017fcb233c2f422d54af293bb8d5c94bc2 >>> >>> I was visiting the TI office and talking to the developers about the >>> performance of this example. According to profiles, >>> it should run up to 60fps. I attempted to make some changes to speed it >>> up, but I did it wrong. >>> >>> You can group different layers in the network to run on different >>> processors. For this classifier network, it is said to >>> be fastest to run the first 11 stages on EVEs as fixed-point processes >>> and then run the last 3 layers as floating-point >>> processes on the C66 DSPs. And, because we'd only be running 3 layers on >>> the DSPs, we only need a single DSP. >>> >>> Anyway, I didn't assign the layers properly and I still need to look at >>> the code a bit more to set them properly. >>> >>> For now, I've just switched back to running on all 14 layers on 4 EVEs. >>> The 30fps data from the camera seems to >>> be reasonably processed with this configuration. >>> >>> I picked up a Logitech C922 that is capable of doing 60fps and I'll be >>> looking to update the demo to run that way soon >>> and finishing up the segmentation demo. >>> >>> Checking the commit-log is a nice way to check-up on me, even if my >>> comments aren't the best. >>> >>> The errors are mostly due to the fact that I'm learning as well. I'm >>> trying to get the TI developers to use my methodology >>> of single-file mjpg-streamer filters rather then OpenCV desktop apps as >>> I feel those the desktop apps are overly complex >>> and don't represent an embedded developer's use-case. They are pretty >>> reasonably documented, >>> but, as you can see, it is taking me some time to understand them. Some >>> additional debug visibility needs to be added >>> to my approach and I'll be chatting to the TI developers about that some >>> in my call later today about this stuff. >>> >>> Development work is on-going for Tensorflow Lite support. All should be >>> much easier once that lands. >>> >>> And, yes, I keep talking about TI as if I don't work there, and I do >>> work there, but my working with open source >>> developers all day keeps me from adopting certain development processes >>> other TI developers take as granted. >>> I don't install Code Composer Studio. I don't setup an Open Embedded >>> build environment. I don't cross-compile. >>> I don't setup JTAG. I hope you get the idea. >>> >>> >>> On Wednesday, October 23, 2019 at 12:46:26 AM UTC-4, Jon Morss wrote: >>>> >>>> >>>> Yeah, I always find it suspect when am example is posted and demo'd but >>>> does not seem to work for others. >>>> >>>> Headbanging continues. >>>> >>>> Jon >>>> >>>> On Tuesday, October 22, 2019 at 4:03:38 PM UTC-7, Dobrin Alexiev wrote: >>>>> >>>>> In my case I also see often ping-pong_ball, or more often >>>>> "segmentation fault". >>>>> I wonder how can I debug this? >>>>> >>>>> >>>>> On Sunday, October 20, 2019 at 2:11:54 AM UTC-4, Jon Morss wrote: >>>>>> >>>>>> I am attempting to run the TIDL example with a Beaglebone AI and the >>>>>> only thing it seems to report identifying is a ping-pong, although I am >>>>>> not >>>>>> presenting a ping pong to the camera. I am using a Logitech C920 camera >>>>>> and have performed all of the updates to the system, so am not sure what >>>>>> I >>>>>> am missing. >>>>>> >>>>>> This is what I see when running the classification.tidl.cpp example: >>>>>> >>>>>> sudo mjpg_streamer -i "input_opencv.so -r 640x480 --filter ./ >>>>>> classification.tidl.so" -o "output_http.so -p 8080 -w >>>>>> /usr/share/mjpg-streamer/www" >>>>>> [sudo] password for debian: >>>>>> MJPG Streamer Version.: 2.0 >>>>>> i: device........... : default >>>>>> i: Desired Resolution: 640 x 480 >>>>>> i: filter........... : ./classification.tidl.so >>>>>> i: filter args ..... : >>>>>> Initializing filter >>>>>> loading configuration >>>>>> allocating execution object pipelines (EOP) >>>>>> allocating executors >>>>>> allocating individual EOPs >>>>>> allocating I/O memory for each EOP >>>>>> Allocating input and output buffers >>>>>> Allocating input and output buffers >>>>>> Allocating input and output buffers >>>>>> Allocating input and output buffers >>>>>> num_eops=4 >>>>>> About to start ProcessFrame loop!! >>>>>> http://localhost:8080/?action=stream >>>>>> o: www-folder-path......: /usr/share/mjpg-streamer/www/ >>>>>> o: HTTP TCP port........: 8080 >>>>>> o: HTTP Listen Address..: (null) >>>>>> o: username:password....: disabled >>>>>> o: commands.............: enabled >>>>>> (722)=ping-pong_ball >>>>>> (722)=ping-pong_ball >>>>>> (722)=ping-pong_ball >>>>>> (722)=ping-pong_ball >>>>>> (722)=ping-pong_ball >>>>>> (722)=ping-pong_ball >>>>>> >>>>>> >>>>>> This is what I see from dmesg: >>>>>> >>>>>> [20753.769040] usb 1-1: New USB device found, idVendor=046d, >>>>>> idProduct=082d >>>>>> [20753.769075] usb 1-1: New USB device strings: Mfr=0, Product=2, >>>>>> SerialNumber=1 >>>>>> [20753.769097] usb 1-1: Product: HD Pro Webcam C920 >>>>>> [20753.769118] usb 1-1: SerialNumber: C0DB0F6F >>>>>> [20754.099831] uvcvideo: Found UVC 1.00 device HD Pro Webcam C920 ( >>>>>> 046d:082d) >>>>>> [20754.120146] uvcvideo 1-1:1.0: Entity type for entity Processing 3 >>>>>> was not initialized! >>>>>> [20754.120179] uvcvideo 1-1:1.0: Entity type for entity Extension 6 >>>>>> was not initialized! >>>>>> >>>>>> [20754.120323] uvcvideo 1-1:1.0: Entity type for entity Extension 11 >>>>>> was not initialized! >>>>>> [20754.125089] input: HD Pro Webcam C920 as /devices/platform/ >>>>>> 44000000.ocp/488c0000.omap_dwc3_2/488d0000.usb/xhci-hcd.1.auto/usb1/1 >>>>>> -1/1-1:1.0/input/input3 >>>>>> [20754.135851] usbcore: registered new interface driver uvcvideo >>>>>> [20754.135871] USB Video Class driver (1.1.1) >>>>>> [20754.437849] usbcore: registered new interface driver snd-usb-audio >>>>>> [20867.134498] usb 1-1: reset high-speed USB device number 3 using >>>>>> xhci-hcd >>>>>> [20867.558788] omap-iommu 58882000.mmu: 58882000.mmu: version 2.1 >>>>>> [20867.605127] omap_hwmod: mmu0_dsp2: _wait_target_disable failed >>>>>> [20867.605206] omap-iommu 41501000.mmu: 41501000.mmu: version 3.0 >>>>>> [20867.605483] omap-iommu 41502000.mmu: 41502000.mmu: version 3.0 >>>>>> [20867.619103] omap_hwmod: mmu0_dsp1: _wait_target_disable failed >>>>>> >>>>>> >>>>>> Am I missing a step? >>>>>> >>>>>> Cheers, >>>>>> >>>>>> Jon >>>>>> >>>>> -- >> For more options, visit http://beagleboard.org/discuss >> --- >> You received this message because you are subscribed to the Google Groups >> "BeagleBoard" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to beagl...@googlegroups.com <javascript:>. >> To view this discussion on the web visit >> https://groups.google.com/d/msgid/beagleboard/3e959a98-3efd-4970-b2ec-e147bf3f4ef9%40googlegroups.com >> >> <https://groups.google.com/d/msgid/beagleboard/3e959a98-3efd-4970-b2ec-e147bf3f4ef9%40googlegroups.com?utm_medium=email&utm_source=footer> >> . >> > -- For more options, visit http://beagleboard.org/discuss --- You received this message because you are subscribed to the Google Groups "BeagleBoard" group. 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