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  3. Can anyone recommend a Tflite Colab Notebook for VOXL2 Training

Can anyone recommend a Tflite Colab Notebook for VOXL2 Training

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  • tomT tom

    @sansoy Can you try adding your user to the dialout group and seeing if that fixes the issue?

    sudo usermod -a -G dialout $USER

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    sansoy
    Contributor
    wrote on last edited by
    #21

    @tom did that and still no inference.
    tflite_1705069939.png

    tomT 1 Reply Last reply
    0
    • S sansoy

      @tom did that and still no inference.
      tflite_1705069939.png

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      tom
      admin
      wrote on last edited by
      #22

      @sansoy That was for fixing the fastboot issue, unrelated

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      • tomT tom

        @sansoy That was for fixing the fastboot issue, unrelated

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        A Former User
        wrote on last edited by
        #23

        @sansoy

        When I get some time today I'll try to download your .tflite models and see what's going on. The good news is that the server is at least running! It very well may just be an issue with how the tensor is being parsed.

        Thomas
        thomas.patton@modalai.com

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        • ? A Former User

          @sansoy

          When I get some time today I'll try to download your .tflite models and see what's going on. The good news is that the server is at least running! It very well may just be an issue with how the tensor is being parsed.

          Thomas
          thomas.patton@modalai.com

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          A Former User
          wrote on last edited by
          #24

          @sansoy

          Hey, they just gave me access to the Google Drive folder. Can you confirm that the edgetpu.tflite in the root directory is the file you want me to try and get working?

          Thomas

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          • ? A Former User

            @sansoy

            Hey, they just gave me access to the Google Drive folder. Can you confirm that the edgetpu.tflite in the root directory is the file you want me to try and get working?

            Thomas

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            sansoy
            Contributor
            wrote on last edited by
            #25

            @thomas i just checked permissions and you have access to all the files and yes to

            edgetpu.tflit
            ssd-mobilenet-v2-fpnlite-640_quant.tflite
            ssd-mobilenet-v2-fpnlite-640.tflite
            saved_models/saved_model.pb

            ? 1 Reply Last reply
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            • S sansoy

              @thomas i just checked permissions and you have access to all the files and yes to

              edgetpu.tflit
              ssd-mobilenet-v2-fpnlite-640_quant.tflite
              ssd-mobilenet-v2-fpnlite-640.tflite
              saved_models/saved_model.pb

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              A Former User
              wrote on last edited by
              #26

              @sansoy

              Of these 4 models which is the custom trained YOLO model you mentioned above? I can't even get the edgetpu.tflite model to load so I need a little bit more information on how each of these files was generated.

              Thomas

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              • ? A Former User

                @sansoy

                Of these 4 models which is the custom trained YOLO model you mentioned above? I can't even get the edgetpu.tflite model to load so I need a little bit more information on how each of these files was generated.

                Thomas

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                sansoy
                Contributor
                wrote on last edited by
                #27

                @thomas here's a yolov5 trained model.
                https://drive.google.com/file/d/1wRbIXdylgx-EOGDLnuWnsytGd2DcTNeY/view?usp=drive_link

                I used this instruction set to train a yolov5 model which works well on my mac, rPI4, linux box and nvidia jetson.
                https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/#23-organize-directories

                S 1 Reply Last reply
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                • S sansoy

                  @thomas here's a yolov5 trained model.
                  https://drive.google.com/file/d/1wRbIXdylgx-EOGDLnuWnsytGd2DcTNeY/view?usp=drive_link

                  I used this instruction set to train a yolov5 model which works well on my mac, rPI4, linux box and nvidia jetson.
                  https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/#23-organize-directories

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                  sansoy
                  Contributor
                  wrote on last edited by
                  #28

                  @thomas here's the colab notebook i used to create the tflites and quantized tflites
                  https://colab.research.google.com/drive/1QdgpSl63OSQdLTnFwOyP8dxLQ7W0HtmW?usp=sharing

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                  • S sansoy

                    @thomas here's the colab notebook i used to create the tflites and quantized tflites
                    https://colab.research.google.com/drive/1QdgpSl63OSQdLTnFwOyP8dxLQ7W0HtmW?usp=sharing

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                    A Former User
                    wrote on last edited by
                    #29

                    @sansoy

                    I found the bug in our code that's causing the issue. You can see on this line that a for YOLO models a former employee hardcoded the number of classes to be 80 leading to a segfault when we only have a single class like in your case. Here's what your model looks like on our server with the fix:

                    7b4e7252-e3f7-4204-be81-abacde3b5c4b-image.png

                    What I'm going to do is write a patch for voxl-tflite-server that more intelligently reads the number from the labels file. This will be available in our SDK Nightlies and so you'll be able to use the fix tomorrow morning. If you'd like the fix sooner, what I can do is package the new voxl-tflite-server into a .deb so you can deploy it manually to your VOXL. I can help you out with this process if you're not familiar.

                    Thanks,
                    Thomas Patton
                    thomas.patton@modalai.com

                    ? S 2 Replies Last reply
                    1
                    • ? A Former User

                      @sansoy

                      I found the bug in our code that's causing the issue. You can see on this line that a for YOLO models a former employee hardcoded the number of classes to be 80 leading to a segfault when we only have a single class like in your case. Here's what your model looks like on our server with the fix:

                      7b4e7252-e3f7-4204-be81-abacde3b5c4b-image.png

                      What I'm going to do is write a patch for voxl-tflite-server that more intelligently reads the number from the labels file. This will be available in our SDK Nightlies and so you'll be able to use the fix tomorrow morning. If you'd like the fix sooner, what I can do is package the new voxl-tflite-server into a .deb so you can deploy it manually to your VOXL. I can help you out with this process if you're not familiar.

                      Thanks,
                      Thomas Patton
                      thomas.patton@modalai.com

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                      A Former User
                      wrote on last edited by
                      #30

                      @thomas

                      Link Preview Image
                      Fix TFLite Num Classes Bug (!22) · Merge requests · voxl / VOXL SDK / Services / voxl-tflite-server · GitLab

                      Tensorflow-Lite (TFlite) server that outputs Tflite processed images

                      favicon

                      GitLab (gitlab.com)

                      Here's the merge request with the fix, this will be published both in tonight's nightly and new SDK releases.

                      Thomas

                      S 1 Reply Last reply
                      1
                      • ? A Former User

                        @sansoy

                        I found the bug in our code that's causing the issue. You can see on this line that a for YOLO models a former employee hardcoded the number of classes to be 80 leading to a segfault when we only have a single class like in your case. Here's what your model looks like on our server with the fix:

                        7b4e7252-e3f7-4204-be81-abacde3b5c4b-image.png

                        What I'm going to do is write a patch for voxl-tflite-server that more intelligently reads the number from the labels file. This will be available in our SDK Nightlies and so you'll be able to use the fix tomorrow morning. If you'd like the fix sooner, what I can do is package the new voxl-tflite-server into a .deb so you can deploy it manually to your VOXL. I can help you out with this process if you're not familiar.

                        Thanks,
                        Thomas Patton
                        thomas.patton@modalai.com

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                        sansoy
                        Contributor
                        wrote on last edited by
                        #31

                        @thomas you rock! awesome! thanks for troubleshooting.

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                        • ? A Former User

                          @thomas

                          Link Preview Image
                          Fix TFLite Num Classes Bug (!22) · Merge requests · voxl / VOXL SDK / Services / voxl-tflite-server · GitLab

                          Tensorflow-Lite (TFlite) server that outputs Tflite processed images

                          favicon

                          GitLab (gitlab.com)

                          Here's the merge request with the fix, this will be published both in tonight's nightly and new SDK releases.

                          Thomas

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                          sansoy
                          Contributor
                          wrote on last edited by
                          #32

                          @thomas thanks thomas. will download tomorrow and test either in evening or next day. Really appreciate your help with this.
                          Great job! Sabri

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                          • S sansoy

                            @thomas thanks thomas. will download tomorrow and test either in evening or next day. Really appreciate your help with this.
                            Great job! Sabri

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                            A Former User
                            wrote on last edited by
                            #33

                            @sansoy

                            Yeah of course, glad I could be of assistance! Be sure to let me know if you need any more help with this.

                            Two things I was thinking about on my drive home that you should know - First, when you're on that page I linked above for the software nightlies make sure you sort the files by date descending so that you get the most recent one. I always make the mistake of getting the wrong one. Secondly, when you flash that nightly SDK it will overwrite anything not in the /data/ directory and so you will need to put your model file and labels txt back into /usr/bin/dnn/.

                            Thomas

                            S 1 Reply Last reply
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                            • ? A Former User

                              @sansoy

                              Yeah of course, glad I could be of assistance! Be sure to let me know if you need any more help with this.

                              Two things I was thinking about on my drive home that you should know - First, when you're on that page I linked above for the software nightlies make sure you sort the files by date descending so that you get the most recent one. I always make the mistake of getting the wrong one. Secondly, when you flash that nightly SDK it will overwrite anything not in the /data/ directory and so you will need to put your model file and labels txt back into /usr/bin/dnn/.

                              Thomas

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                              sansoy
                              Contributor
                              wrote on last edited by
                              #34

                              @thomas Morning Thomas, just getting back to this. I couldnt find any SDK that had a 2024 stamp. Was this uploaded somewhere else?
                              Sabri

                              ? 1 Reply Last reply
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                              • S sansoy

                                @thomas Morning Thomas, just getting back to this. I couldnt find any SDK that had a 2024 stamp. Was this uploaded somewhere else?
                                Sabri

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                                A Former User
                                wrote on last edited by
                                #35

                                @sansoy

                                Here's the one from last night:

                                https://console.cloud.google.com/storage/browser/_details/platform-nightlies/voxl2/voxl2_SDK_nightly_20240117.tar.gz?pageState=("StorageObjectListTable":("s":[("i":"objectListDisplayFields%2FtimeLastModified","s":"1"),("i":"displayName","s":"0")]))&organizationId=517175400245&project=modalai-core-services

                                You just have to make sure when you're on this page that you sort date modified by descending.

                                Thanks,
                                Thomas

                                S 1 Reply Last reply
                                0
                                • ? A Former User

                                  @sansoy

                                  Here's the one from last night:

                                  https://console.cloud.google.com/storage/browser/_details/platform-nightlies/voxl2/voxl2_SDK_nightly_20240117.tar.gz?pageState=("StorageObjectListTable":("s":[("i":"objectListDisplayFields%2FtimeLastModified","s":"1"),("i":"displayName","s":"0")]))&organizationId=517175400245&project=modalai-core-services

                                  You just have to make sure when you're on this page that you sort date modified by descending.

                                  Thanks,
                                  Thomas

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                                  sansoy
                                  Contributor
                                  wrote on last edited by
                                  #36

                                  @thomas

                                  installed voxl2_SDK_nightly_20240117.tar.gz
                                  per https://docs.modalai.com/flash-system-image/

                                  still not getting any detection even with your default yolov5. ive tried with hires large color, small color and grey.

                                  tflite_1705597671.png

                                  ? 1 Reply Last reply
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                                  • S sansoy

                                    @thomas

                                    installed voxl2_SDK_nightly_20240117.tar.gz
                                    per https://docs.modalai.com/flash-system-image/

                                    still not getting any detection even with your default yolov5. ive tried with hires large color, small color and grey.

                                    tflite_1705597671.png

                                    ? Offline
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                                    A Former User
                                    wrote on last edited by
                                    #37

                                    @sansoy

                                    Checking this out right now, will let you know when I have something.

                                    Thomas

                                    ? 1 Reply Last reply
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                                    • ? A Former User

                                      @sansoy

                                      Checking this out right now, will let you know when I have something.

                                      Thomas

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                                      A Former User
                                      wrote on last edited by
                                      #38

                                      @thomas @sansoy

                                      So I was able to get our YOLO model running immediately, am about to try yours next. All I did was:

                                      1. Flash the nightly SDK from last night using the steps you linked above
                                      2. Edited /etc/modalai/voxl-tflite-server.conf so that the model was /usr/bin/dnn/yolov5_float16_quant.tflite and the input pipe was /run/mpa/hires_small_color.

                                      You should definitely try to reproduce this result as if you can't it might indicate a deeper problem.

                                      Then to use your custom model:

                                      1. adb shell and then cd /usr/bin/dnn and then cp yolov5_labels.txt yolov5_labels.txt.bak && cp yolov5_float16_quant.tflite yolov5_float16_quant.tflite.bak to back up the existing model and label files.
                                      2. vi yolov5_labels.txt and change to only have ar15 as a class
                                      3. From outside ADB, adb push yolo5_fp16_quant.tflite /usr/bin/dnn/yolov5_float16_quant.tflite
                                      4. voxl-tflite-server

                                      e2ee78d8-8d17-4863-ad90-8917442727b5-image.png

                                      Thomas
                                      thomas.patton@modalai.com

                                      S 1 Reply Last reply
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                                      • ? A Former User

                                        @thomas @sansoy

                                        So I was able to get our YOLO model running immediately, am about to try yours next. All I did was:

                                        1. Flash the nightly SDK from last night using the steps you linked above
                                        2. Edited /etc/modalai/voxl-tflite-server.conf so that the model was /usr/bin/dnn/yolov5_float16_quant.tflite and the input pipe was /run/mpa/hires_small_color.

                                        You should definitely try to reproduce this result as if you can't it might indicate a deeper problem.

                                        Then to use your custom model:

                                        1. adb shell and then cd /usr/bin/dnn and then cp yolov5_labels.txt yolov5_labels.txt.bak && cp yolov5_float16_quant.tflite yolov5_float16_quant.tflite.bak to back up the existing model and label files.
                                        2. vi yolov5_labels.txt and change to only have ar15 as a class
                                        3. From outside ADB, adb push yolo5_fp16_quant.tflite /usr/bin/dnn/yolov5_float16_quant.tflite
                                        4. voxl-tflite-server

                                        e2ee78d8-8d17-4863-ad90-8917442727b5-image.png

                                        Thomas
                                        thomas.patton@modalai.com

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                                        sansoy
                                        Contributor
                                        wrote on last edited by
                                        #39

                                        @thomas WORKED! i did most of what you stated except for renaming my file to your filename. !tflite_1705605919.png

                                        in a future release would be able to use the original filename vs renaming it to something that is hardcoded?

                                        ? 1 Reply Last reply
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                                        • S sansoy

                                          @thomas WORKED! i did most of what you stated except for renaming my file to your filename. !tflite_1705605919.png

                                          in a future release would be able to use the original filename vs renaming it to something that is hardcoded?

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                                          wrote on last edited by
                                          #40

                                          @sansoy

                                          Glad you got it working!

                                          It's important to note that voxl-tflite-server isn't intended to be a high-grade tool for running any ML model with great configurations and optimizations; it's just an example of how you can use the VOXL ecosystem to run models. As much as I would enjoy building such a tool and implementing your request (and the others I get), there just isn't enough of a business demand for it right now.

                                          That being said, the code is open source and right here is the line that does the string comparison. If you want to put out a merge request to add a new field for model_type to the /etc/modalai/voxl-tflite-server.conf JSON and have it select an inference method based on that, you can tag me and I'll review it.

                                          Thanks,
                                          Thomas Patton
                                          thomas.patton@modalai.com

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