How to Train TensorFlow Lite Object Detection Models Using Google Colab | SSD MobileNet

[@JaiPatel-y5b]

Ive been banging my head on my desk trying to find a good tutorial. Big thank

[@EdjeElectronics]

Hey all, just a quick update (April 10 2024). I ran through the full notebook today with my coin dataset, and everything worked without errors. A "Restart Session" option appears during Step 1 after running the last set of install commands. When it appears, click the "Restart Session" option, and then keep working through the steps. If you're getting errors, try using my coin dataset and seeing if it works (it should). Then, compare your annotation files with the annotation files from the coin dataset. It's likely there's a difference in your annotation files that are causing problems.

[@joeycherisea5999]

Hello Edje, thanks for this great tutorial! While following exactly the steps in your notebook, I ran into an error repetitively when running model_builder_tf2_test.py: "Could not load dynamic library 'libcudart.so.11.0'; dlerror:.." Any idea of how to solve it?

[@SanilJadhav711]

On Step 5 Training the model there's this another error that most of us are getting now, can you try checking it out ? The error goes like this, "TensorFlow Addons (TFA) has ended development and introduction of new features. TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024. Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP)." Followed by some errors about not identifying variables like {num_steps}, pipeline_file and model_dir that we indeed declared just some snippets ago, really frustrating error

[@lucasinunas]

for anyone who noticed that not all images are getting moved to its respective folders, and that later it gives some error that a file is missing: make sure all your images end with .jpg instead of .jpeg since all the scripts on the github page only takes into account those files

[@fe_nik_s776]

Hello, to increase performance, you can use multithreaded computing. To do this, when loading the model, specify the "num_threads" argument, which must contain the number of threads that the processor supports. Basically, TFLite uses only one core. The code: import multiprocessing tf.lite.Interpreter(model_path=PATH_TO_CKPT, num_threads=multiprocessing.cpu_count() ) On my old laptop with dual-core CPU, this gave a double increase in performance. Basic - 140 ms per frame. With two cores - 85 ms per frame

[@EdjeElectronics]

Thanks, I'll have to try that!

[@khamismuniru5188]

This works like a charm bro! On a pi 4, My fps went from 8fps to 20fps when using the google sample tflite model!🤯

[@darrenmendoza7620]

@@khamismuniru5188 how

[@fe_nik_s776]

@@SumitKumaar321 Section 7.1. In the line -> interpreter = Interpreter(model_path=modelpath)

[@randomvideochamber1723]

@@fe_nik_s776 you mean like this? import multiprocessing tf.lite.Interpreter(model_path=PATH_TO_CKPT, num_threads=multiprocessing.cpu_count() ) interpreter = Interpreter(model_path=modelpath)

[@baumotorola9149]

Really nice video. Anxiously waiting for an Android deploying tutorial!

[@iotlalo]

I struggle a week trying the repo from Google and this video save my life thank you I would like to see a video of posenet in Raspberry Pi

[@shivarajchangale47]

is your tflite model detecting items well? because my model detecting false products

[@iotlalo]

@@shivarajchangale47 yes but i mean when i tried to run It in a new OS from Raspberry PI

[@AlexanderSomma]

Thank you for a wonderful breakdown of all the needed steps to do training on colab.

[@ivandimitrov2401]

Amazing tutorial! One of the most useful videos I've ever watched. Keep up the good work! Thanks a lot, Edje!

[@SAYED-ZALALBIA.]

Thank you for a wonderful breakdown of all the needed steps to do training on colab ❤❤❤ Your follower from Egypt 🥰

[@huberthernandezjr.4279]

its working thankyouuuuuuu edje electronics, i transfer it to raspberry pi also and it did not work at first time i just update some lib and it worked now thankyouuu thankyouuu super awsomeeee

[@ujjwalpranami7165]

Thankyou so much you made my day, I was searching all internet for working colab notebook for this model.

[@felixoyeleke]

Your tutorial is the best on the internet. Exactly what I needed! Thank you! Thank you! Thank you!!!

[@MakerMadness]

Really excited your back! Thanks for the video.

[@ejarao8321]

Still is one of the best tutorial for model training in KZbin. But I have a suggestion, could there be an option to add metadata scripts to the notebook? this could be highly useful since of the release of googles ML kit for android & ios development.

[@PraiseTheLord527]

@EdjeElectronics, I had a bug whereby on step 5, the training stops about a minute :( I practically did everything according to the tutorial. The code ends with a ^C symbol. Also, I noticed that the system RAM skyrocketed to 12.1Gb before the training process stopped... Could this be the issue? I would be really grateful if you could provide me some guidance please.

[@louisrossin-b8v]

i have the same issue ! I'm pretty much sure this is beacause of the ram capabilities... I gess we have to subscibe to googlecolab pro

[@kai-ten15]

Your images are too large and you're running out of memory. Resize them to be around 200-300KB, don't upload too many images, and you should be good to go

[@crickshowshorts]

Superb..It is hard to install tensorflow api because the version incompatibilities..you handle those superbly

[@kai-ten15]

Great tutorial!! Great introductory experience while also providing everything needed for learning rabbit holes. If you come across Step 5 ending with ^c, it is because you are running out of memory. Either resize your images to be large/medium (~200-300KB per image), upload less images, or both.

[@nadavdashevski4300]

wow thanks man!

[@istillplay271]

Thankkk youu sooo much for the tutorial, I've been researching on the internet but didn't get the solution. Great work you've earned a subscriber.

[@navishkhadooa5867]

Really amazing video with detailed and well-explained steps. Great job!

[@CRIMX0N]

Thank you! Clear and easy to understand while having sprinkles of humor made this video really educational AND enjoyable. Easiest like and subscribe.

[@EdjeElectronics]

Thanks for the kind words! 😸

[@OsamaShamim]

@@EdjeElectronics There are a few persistent warnings in the notebook now because of which it does not run anymore. Kindly check the comment sections and reply. The training does not commence in step 5. It worked once when we tried the notebook on a smaller dataset but then now we are trying to deploy the full dataset it shows this issue and does not run.

[@emanuelrodrigues6453]

Amazing!! Incredible to see you using the model on another device.

[@viniciusc3723]

No fucking way u are givin us for free this kind of information, i love u so much, i have spend the last 2 months trying do a tensorFlow Object Detecion works, u deserve the best things of world can provide thanks thanks thankssssssssssssssssssssssssssssssss

[@bergjoel93]

Hello and thank you again for this tutorial! Today I was successfully able to get to the training step with my own dataset but I unfortunately forgot to turn my computer's sleep mode off. When I went to go back through the steps I keep getting an error Step 4 Cell 4 commented: "# Set file locations and get number of classes for config file". The error says "NotFoundError: /content/labelmap.pbtxt; No such file or directory" I can share a screenshot if you like. I've ran through the notebook several times and have also reset it with your most current version and I keep getting this. And in fact, there is no labelmap.pbtxt in my files. There is a labelmap.txt though! Thank you!

[@GoldenMoments100]

yeah, the .pbtxt does not get created in my case either.

[@GoldenMoments100]

I ran this in a seperate cell to create the .pbtxt file: path_to_labeltxt = os.path.join(os.getcwd(), 'labelmap.txt') with open(path_to_labeltxt, 'r') as f: labels = [line.strip() for line in f.readlines()] path_to_labelpbtxt = os.path.join(os.getcwd(), 'labelmap.pbtxt') with open(path_to_labelpbtxt,'w') as f: for i, label in enumerate(labels): f.write('item { ' + ' id: %d ' % (i + 1) + ' name: \'%s\' ' % label + '} ' + ' ')

[@qbotx]

have you fix this problem yet?

[@LaraCalvo-mk2uh]

This tutorial was super helpful, thank you a lot! It is very easy to follow along and understand with step-by-step instructions

[@Tzu-LingLiu]

Thanks for making this amazing video! It is really helpful. Look forward to the "quantize TFLite model:" video too!!!

[@veranium24]

thank you so much for uploading this video. Helped a lot! :D

[@venven9839]

Thankyou somuch for your helping with this video, now can implement this tutorial in my final task

[@qbotx]

i unable to make labelmap.pbtxt on step 3.3, how do i fix this?

[@roeyasher1396]

same problem

[@rmmtech1218]

@@roeyasher1396 i can't paste here the raw code..sorry

[@madhuraj3940]

@@rmmtech1218 please let us know what to be done or can you drop same to mail id?

[@madhurajr4454]

Drop your mail id, I will send pdtxt file, you have to change classes there and paste at location

[@empi9249]

Good to see you again!

[@EdjeElectronics]

Thanks! I'm going to try and hold myself to a more regular release schedule now... we'll see how it goes! 😁

[@kaant21]

if you do everything right and it stuck on "use tf.cast instead" without any error. The problem is your train.tfrecord is empty. you need to change your xml files to make it work. it should look like this without any extra rows or parameters. Dont worry only important thing in this code is object name, min/max values and filename. If you have any additional row in your xml just manually delete it or use different label tool datasetjpg 20.jpg C:\Users\Kaan PC\Desktop\datasetjpg\20.jpg Unknown 1920 1080 3 0 car Unspecified 0 0 1205 38 1900 387

[@EdjeElectronics]

Thanks for posting this solution!

[@alikemalsar4595]

@@EdjeElectronics I want to train my own model and there is only one class for example car. Just one. But section 3.3 doesn't accept it. And it give a error masege " penny, nickel, dime, quarter use " like this. What should ı do?

[@anushkachauhan6397]

I did this but it's still stuck in there? What else can be the solution?

[@slametjumpshoot]

thank you broo, you're amazing💣

[@ciscomike82]

That was so detailed and easy process! Thank you so much for the effort you have been given for all those videos. Quick question, what if somebody wants to use rstp streams instead of raspberry or USB camera on the Raspberry Pi, what should be change and where? Thanks again.

[@rashmikajayasundara4553]

Thank you. Very nice guide for beginner. Please do video for audio classification using microphone with raspberry pi.

[@saramasood4675]

Thank you soo much.. i just trained model on coral usb

[@kevinsmithwoo]

Please keep making great videos. Awesome content.

[@PraveenKumar-wv8hf]

Wonderful, thanks for the efforts for explaining step by step

[@EdjeElectronics]

Sigh, sorry guys. It looks like something changed in Colab or in TensorFlow, and now it's not able to run training on the GPU. I get several error messages like this when I try to run training in Step 5: " Could not load dynamic library 'libcudart.so.11.0' ". This means it's not able to load the CUDA libraries needed to run on the GPU. I'm not sure why. If anyone can figure out the problem, please post a solution. I'll dive into it after New Year's if no one has found anything by then. EDIT: I'll send $50 USD to the first person who can figure out a reliable solution and post it. And I'd also be highly interested in hiring you for a paid internship at ejtech.io 😃

[@rikitiu369]

Up! Thank you!

[@VietTran-ij2cp]

Up!!! Thank you so much

[@markwassef8643]

I have the solution, however KZbin deletes my comment because the code contains a URL. Any workaround for this?

[@EdjeElectronics]

@@markwassef8643 cool! What’s your email? I’ll send you a message.

[@EdjeElectronics]

Or, you can contact me at [e-mail] .

[@xenva8474]

Hello! Awesome video btw! I tried to create my own model but i start to run training block, this error shows: TensorFlow Addons (TFA) has ended development and introduction of new features. TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024. Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP). any help with this? Really appreciate it!!

[@roeyasher1396]

same problem pls help.

[@SanilJadhav711]

Exactly, same here

[@thewongwayround]

Great tutorial. Anybody else having an issue with getting more than 10 detections of the same class per image?

[@humilam4808]

Nice and clear step-by-step video! However, I cannot run it smoothly at my side. At section3.3, no labelmap.pbtxt is generated so the later step in section 4 crash. Would you know the reason ?

[@260.vighneshbablu2]

Yes for me too got any fix?

[@humilam4808]

@@260.vighneshbablu2 it suddenly fixed after i reload the notebook and redo all the steps

[@humilam4808]

@@260.vighneshbablu2 guess another solusion can be finding one .pbtxt, follow its formet and edit according to your custom class names.

[@260.vighneshbablu2]

@@humilam4808 but the format is not shown in the video

[@humilam4808]

@@260.vighneshbablu2 find one online

[@potatowo5712]

Hello! Really informative video, I just wanted to know the process stays or less the same even if im on a Mac while making the project right? Is there anything I should be aware of? Furthermore its possible for me to make it so that the software detects when I am bending/bent towards the right/left and give an output, or because its the same person it wont be able to recognise that? thanks!

[@EdjeElectronics]

Thanks! It should all work inside the web browser, even if you're on a mac. However, I still haven't written the guide for how to take the downloaded model and run it on macOS. You should take a stab at it though! In fact, I'd pay you $50USD if you can write a macOS deployment guide similar to the one I wrote for Windows (github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi/blob/master/deploy_guides/Windows_TFLite_Guide.md). Email me if you're interested in that - [e-mail] ! For detecting which way you are bent, I would try using an OpenPose model (look it up on KZbin to see what I mean).

[@FabrizioCoppolecchia]

hey, when next video about object detection fine tuning and creating apps with that? really love your videos

[@EdjeElectronics]

Thanks, I appreciate you saying that! It helps motivate me to make more videos 😀. I have been busy working on paid projects, but I really want to do a video series on creating applications with YOLOv8. I don't know when I'll get to it though.

[@karenjin7111]

Really good tutorial, I am following along for my school project, I can get as far as to the training, then it won't start training in Colab, in the log, it shows that the TensorFlow Addons needs tf version 2.12 - 2.15.0, would that be the case? I can see your video using python 3.8, currently the colab is run on python 3.10, could that be the reason? Could you please help? Thank you

[@0oMardev]

Great job man, I love the work you've done ❤ I'm a complete beginner at this, I wanted to ask if it would be possible to add to the notebook on colab a way to save progress and then continue it in another session. When I train the model I get up to 20000 steps but then I get disconnected from colab (having the free version), I was thinking if before I get disconnected I could stop the training and then later (when colab allows it again) continue it.

[@0oMardev]

Nevernind i solved this, for everyone interested i chnaged pretty much all of the paths to save on google drive.

[@nikulee__]

hello! would you mind if i can ask how to be able to save paths on gdrive ? thanks a lot

[@0oMardev]

Hi, what I did was to replace the directories in the colab with “/mydrive/” so that everything is saved on google drive, for example instead of “!mkdir /content/images” I have “!mkdir /mydrive/images”. It is still quite risky because you are doing operations in your google drive. That's it ! I can't post my changes now because they are quite specific to my case (and I don't know if it always works), but this is how you can do it too.

[@flourencelapore4404]

@@0oMardev i hope you still can read my comment man, thanks for your tips but can you still provide more info? Thank youuu

[@flourencelapore4404]

@@0oMardev so when you continue to train it again, you just have to mount your gdrive and run the "Train" again?

[@dreamofaneye8946]

Thank You for your tutorial, it has been of great help to me but, I when upload the images folder and run it to distribute data for training, validation and test it show me zero images in total Please guide me in this regard

[@remsuuu]

hello, I have a question. I bought an edge tpu coral for more camera fps, I also used the file that downloaded in the final part which is for edge tpu. It works but it cannot easily detect objects when the coral is plugged in, but if the edge tpu is disconnected, it runs at 2 fps but it always detect the object. May I know if there’s a fix on this one? Thank you!

[@PraiseTheLord527]

Hello Remus! Just wondering if you were able to solve this issue? :O

[@salmanulfaris7165]

Thank you for the great content. Waiting for the deployment of tflite on the android studio part. Thank you

[@wilsonhuanquisoria2954]

gracias por los vídeos, me ayudo mucho a entrenar modelos.

[@Karaokephil1]

So cool, a bit beyond me (at the moment!) but it gives me a good idea for coin collecting

[@carladrianangeles2811]

Great tutorial! I've been encountering a problem though with my dataset. All file names are correct, also the file extensions, and have tried all options of adding a dataset (upload, gdrive mounting, dropbox) I even checked the csv file and all are intact. However, when its time to create the tfrecord files, there appear to be some files missing in both the train and validation folders, thus I can't generate the pbtxt file. Any tips?

[@EdjeElectronics]

Thank you! Hmm, usually if there's an issue with the pbtxt file, it's because there's a problem with the annotation data (like a typo in a class name). Can you try using my coin dataset and see if you get the same issue?

[@JayBryanOdero]

LIFE SAVER MAN THANKS

[@chaitrapatil1156]

my model detecting constancy only 10 objects why so. have used any restriction here model should detect 10 object only

[@gnavarrolema]

Great video tutorial. Thank you!!!

[@rml0226]

hello good sir, this is a very helpful vid. Currently waiting for the how to capture and label training data video

[@EdjeElectronics]

It will be out on Monday! Just finishing up the editing now.

[@rml0226]

@@EdjeElectronics happy to hear that sir, thank you for uploading such helpful videos

[@madhuraj3940]

Getting this error "NotFoundError: /content/labelmap.pbtxt; No such file or directory" at step 28, If I try set file locaton, does anyone had same issue, please someone help me with this

[@flourencelapore4404]

I have the same error, can someone please help

[@yuvrajanand9342]

Your video have been so useful to me, i just would like you make a tutorial to run it on a mac machine

[@Nummi31]

The best tutorial in the world! :) Please could you modify the code on Google Colab in the future so that training also works for negative images and xml files without objects in them? Now it gives errors. Thank you so much, we love you!

[@PeterPan-hs5tu]

Love your tutorial!! good job with the instruction. I kind of using your material as my object detection experiment for my own dataset. But I got stuck at the training. seems like there is a version deprecation issue due to the colab upgrading TF version. I am wondering if there is an update to the code that helps at stage 5. TFLite model training :)

[@EdjeElectronics]

Thanks! Sorry, I'm not sure what's going on, and I don't have time currently to look in to it. Can you try Google searching the error to see if there's a resolution?

[@Cicatka.Michal]

Hey, I was facing some issues as well. Make sure to run the session with the GPU. When I was training a larger model without the GPU, it hung on the training initialization. I also decreased the batch-size but I'm not convinced that it's actually necessary. Btw, thanks @EdjeElectronics for the tutorial, I really appreciate it!

[@PeterPan-hs5tu]

Yeah thanks you two for replying, and can’t thank enough to @EdjeElectronic for providing the tutorial. So my issue turns out to be that my dataset contains .csv for annotation. So I had to ask GPT to write me a code to convert the labeling datasets back to .xml w/ exactly the same format as the dataset you provide for the coin dataset. I did it offline with Jupyter Notebook and re-upload them back to Gdrive and continue using your code to train, and after 2 weeks of tweaking, I finally made it to train with your magical instruction:) I looked into every line of your code and went down the rabbit hole with even the extension .py you linked and trying to study the logic behind the code w/ the help of chatGPT :D Long story short, I got it to train and it’s training. Yay!!!

[@PeterPan-hs5tu]

Ok so i figured it out. I realize that the entire process requires xml and image dataset. i had csv and image as my dataset. So i converted the csv labeling dataset back into xml format locally and re upload the dataset and run the code and worked!! yay~✌😇

[@EdjeElectronics]

@@PeterPan-hs5tu Awesome, glad you were able to figure it out!

[@shovitregmi._4081]

Thankyouuu Sirrr, you were such a helpp

[@rajmeetsingh1625]

Great tutorial...............

[@wilhelmusolejr4979]

Please make a video for android studio version. Thank you. Great tutorial by the way

[@DrMatthewHudson]

Can you do this with screenshots from a website to train it to identify certain images on a website?

[@zhangliu8]

Hi! I'm getting an error when training a custom model (Train Custom TFLite Detection Model) and a warning: TensorFlow Addons (TFA) has ended development and introduction of new features. TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024. Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP).

[@SanilJadhav711]

Exactly, Ive been receiving this exact error and its eating my brain up I know its really late to reply to you but did you find a solution to this ?

[@petrusdimase1520]

Great videos. It works well thanks.

[@jtd3e_19_muhammadyogaakbar4]

excuse me sir, i want trouble notif "Corrupt JPEG data: 251 extraneous bytes before marker 0xd9" how to the fix this sir ? thaks you

[@RD0726]

I tried to find my problem in the bottom of colab, but i only found there is one setence and a cant find any thing?

[@aqilhakim3459]

hello sir, why my labelmap.pbtxt is not appear? please help mee

[@ancysa5830]

Helpful video. can i peform segmentation instead of object detection in tensorflow lite?

[@vjn1109]

Good afternoon, great contribution that you really make, congratulations, a question when doing the training is paralyzed and does not continue on API in Colab, what could happen?

[@EdjeElectronics]

Sorry, I haven't encountered that problem before. My guess is to restart the Colab from scratch and try to run through it again. Otherwise, I'm not sure how to solve it.

[@auspiciadjima]

Really thank you very much for the tutorial I was able to do the inference on a Raspberry Pi. However, just after the entire model I evaluated the precision of the model on the training and test data but the script that I I wrote to myself about errors since the images were saved in tfrecord format. Could I have a hand lesson?

[@zyadbenchrifa8182]

Thank you for the wonderful breakdown !! Can you do a tutorial on how to deploy on android please

[@cheerio4742]

Hi wonderful video, I'm working on a custom dataset with more than 4 classes what file or code would I change?

[@technovert1614]

I got error at step 3.3 No such file or directory: 'images/validation_labels.csv'

[@MichaelM-e3x]

Many thanks for the good video and the excellent Google Colab script. But when I want to use the T100 CPU (Batch 64) in Colab, problems occur. It then takes a very long time before the training starts and the output in the tensor board is relatively senseless. (Only flat graphs). Maybe you would like to check the code, because a lot has changed in the packages. (Unfortunately, I can't, because my detailed knowledge is not yet good enough). Thank you very much for your efforts. Best regards, Michael

[@robin2080]

Dude can you update the tensorflow lite on raspi for Obj detection. a good chunch of the requirements on the get-req bash are deprecated. Thanks!

[@maconnor2546]

Thank you for the tutorial video! And I have a question how can I export the classification output data and save in the txt file?

[@aljazherodez1692]

Hi, I have encountered a problam everything works fine until i get to Start training a model. It displays log text but after about 3 minutes RAM usage go to max and script just exit. Please HELP!! i have this for a school project and I'm running out of time. Thanks

[@PraiseTheLord527]

Does the script end with^C? I think I encountered this error too...

[@PraiseTheLord527]

Hey were you able to solve this issue?

[@AllanNgure-h4j]

Really detailed. A query though, where in the above procedures should I rectify to train a face detection model??

[@kaloivan3482]

Great video intesetd if you have Instructions to run TFLite models on mac os

[@amroelmughrabi]

Previews comment: "Hello, sometimes the training stops after 400 steps and some times stops after 200 steps i don't know why." answer: If the images are over 1 MB each, that will fill the Colab Ram which leads the code to stop, after Trying, i recommend sticking with 400 KB at max per photo specially if we are talking about a big amount of images.

[@jako3939]

Thanks! Had the same error. I wrote a python script to resize all pictures in a folder and now it works. The collab environments RAM usage is now much lower.

[@JamesJuta]

Hello, can we have a tutorial about implementing the tensorflow lite model that is made in this video to a mobile object detection application. Thank you very much and looking forward to it

[@vcodevideo]

Thanks for the video!!. I have some doubts, if I would train a model for detecting no ok parts, the way you showed us will fit for my model?, Must I take a picture for any defect and label it? Must take pictures for ok parts and label it also?. I'm trying to detect defects like scratches, marks, paint defects, etc...any help will be much appreciated!!

[@johnkidsman]

great video! thanks!

[@mortocks]

Any chance you can update the instructions to show how to convert the model to tensorflow.js? I've followed the video and it all worked but running the model through tensorflowjs_converter results in a 16kb .bin file which is obviously not correct. Fantastic tutorial - thanks!!

[@EdjeElectronics]

I can look into it! Do you know where in the TensorFlow docs I can find more info about tensorflowjs_converter?

[@mortocks]

That'd be awesome. Thanks@@EdjeElectronics. Here's the docs that I've read - I "think" that your tutorial creates a "shared model" and then you convert from that but I might be wrong

[@Luke-ji2bt]

@@mortocks Hi! Did you find a solution? can you help me, i need in .js too

[@EdjeElectronics]

Good news! Training on GPU is working again. Thank you @markwassef8643 for finding the solution.

[@rajmeetsingh1625]

I want to deploy custom detection model on jetson nano..............

[@moshiesamuel6026]

Thanks for the tutorial. I noticed the image detection draws a maximum of 10 objects is there a way to increase the count?

[@orrafaellis]

hey mate! Did you manage to solve it? I'm having the same issue.

[@aurynonagata1124]

Why does the model only detect one class during the testing process even though the dataset has three classes?

[@isabagheri5992]

hello, thanks for your tutorial, how can increase number of boxes in model config(not detect more than 10 object per image) can everybody help me please?

[@eugenioverrelwong8733]

hello I want to ask when i was running the python script on 3.2 for splitting images into train, validation and test folders. I have this problem: Total images: 0 Images moving to train: 0 Images moving to validation: 0 Images moving to test: 0 Looking forward to the response! Thank u!

[@EdjeElectronics]

Hmm... was your images folder named "images.zip"? Can you see any files in the "images/all" folder in the filemenu on the left side bar? What are the file extensions for your images (.jpg, .bmp, something else)?

[@eugenioverrelwong8733]

@@EdjeElectronics oh the name was car images and i changed it and it got fixed, however the script doesnt take in jpeg file does it? Because when it was splitting I still had some file in the all file mostly jpeg format

[@EdjeElectronics]

@@eugenioverrelwong8733 Thanks! I forgot about the .jpeg file extension 😅, I'll change the code to support that too.

[@eugenioverrelwong8733]

@@EdjeElectronics urwell, anyways i wanna ask so i basically wanted to make an automatic license plate reader using object detection for residential area and I sort of want it to read the letters and numbers in the license plate, if it was you would you prefer to train the model so it can read the letters or use OCR to detect the letters from the license plate? Thank you so much looking forward for your tips, tricks and answers

[@EdjeElectronics]

@@eugenioverrelwong8733 I would train a model to detect the license plates, and then crop out the detected plate and use OCR to read the letters. Actually, I just saw a blog post talking about this exact topic! Check it out here: blog.roboflow.com/how-to-crop-computer-vision-model-predictions/

[@bxoz3352]

I got an error about labelmap.pbtxt at first so i created it myself The code gets stuck in the training part /usr/local/lib/python3.10/dist-packages/tensorflow_io/python/ops/__init__.py:98: UserWarning: unable to load libtensorflow_io_plugins.so: unable to open file: libtensorflow_io_plugins.so, from paths: ['/usr/local/lib/python3.10/dist-packages/tensorflow_io/python/ops/libtensorflow_io_plugins.so'] caused by: ['/usr/local/lib/python3.10/dist-packages/tensorflow_io/python/ops/libtensorflow_io_plugins.so: undefined symbol: _ZN3tsl5mutexC1Ev'] warnings.warn(f"unable to load libtensorflow_io_plugins.so: {e}") /usr/local/lib/python3.10/dist-packages/tensorflow_io/python/ops/__init__.py:104: UserWarning: file system plugins are not loaded: unable to open file: libtensorflow_io.so, from paths: ['/usr/local/lib/python3.10/dist-packages/tensorflow_io/python/ops/libtensorflow_io.so'] caused by: ['/usr/local/lib/python3.10/dist-packages/tensorflow_io/python/ops/libtensorflow_io.so: undefined symbol: _ZNK10tensorflow4data11DatasetBase8FinalizeEPNS_15OpKernelContextESt8functionIFN3tsl8StatusOrISt10unique_ptrIS1_NS5_4core15RefCountDeleterEEEEvEE'] warnings.warn(f"file system plugins are not loaded: {e}") /usr/local/lib/python3.10/dist-packages/tensorflow_addons/utils/tfa_eol_msg.py:23: UserWarning: TensorFlow Addons (TFA) has ended development and introduction of new features. TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024. Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP). For more information see: github.com/tensorflow/addons/issues/2807 warnings.warn( /usr/local/lib/python3.10/dist-packages/tensorflow_addons/utils/ensure_tf_install.py:53: UserWarning: Tensorflow Addons supports using Python ops for all Tensorflow versions above or equal to 2.10.0 and strictly below 2.13.0 (nightly versions are not supported). The versions of TensorFlow you are currently using is 2.8.0 and is not supported. Some things might work, some things might not. If you were to encounter a bug, do not file an issue. If you want to make sure you're using a tested and supported configuration, either change the TensorFlow version or the TensorFlow Addons's version. You can find the compatibility matrix in TensorFlow Addon's readme: github.com/tensorflow/addons warnings.warn( 2023-06-19 11:13:33.517675: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0. INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',) I0619 11:13:33.530389 139697095886656 mirrored_strategy.py:374] Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',) INFO:tensorflow:Maybe overwriting train_steps: 20000 I0619 11:13:33.534287 139697095886656 config_util.py:552] Maybe overwriting train_steps: 20000 INFO:tensorflow:Maybe overwriting use_bfloat16: False I0619 11:13:33.534482 139697095886656 config_util.py:552] Maybe overwriting use_bfloat16: False WARNING:tensorflow:From /usr/local/lib/python3.10/dist-packages/object_detection/model_lib_v2.py:563: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version. Instructions for updating: rename to distribute_datasets_from_function W0619 11:13:33.569274 139697095886656 deprecation.py:337] From /usr/local/lib/python3.10/dist-packages/object_detection/model_lib_v2.py:563: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version. Instructions for updating: rename to distribute_datasets_from_function INFO:tensorflow:Reading unweighted datasets: ['/content/train.tfrecord'] I0619 11:13:33.572712 139697095886656 dataset_builder.py:162] Reading unweighted datasets: ['/content/train.tfrecord'] INFO:tensorflow:Reading record datasets for input file: ['/content/train.tfrecord'] I0619 11:13:33.572935 139697095886656 dataset_builder.py:79] Reading record datasets for input file: ['/content/train.tfrecord'] INFO:tensorflow:Number of filenames to read: 1 I0619 11:13:33.573024 139697095886656 dataset_builder.py:80] Number of filenames to read: 1 WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards. W0619 11:13:33.573094 139697095886656 dataset_builder.py:86] num_readers has been reduced to 1 to match input file shards. WARNING:tensorflow:From /usr/local/lib/python3.10/dist-packages/object_detection/builders/dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`. W0619 11:13:33.575423 139697095886656 deprecation.py:337] From /usr/local/lib/python3.10/dist-packages/object_detection/builders/dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`. WARNING:tensorflow:From /usr/local/lib/python3.10/dist-packages/object_detection/builders/dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.map() W0619 11:13:33.600855 139697095886656 deprecation.py:337] From /usr/local/lib/python3.10/dist-packages/object_detection/builders/dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.map() WARNING:tensorflow:From /usr/local/lib/python3.10/dist-packages/tensorflow/python/util/dispatch.py:1082: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead. W0619 11:13:42.011853 139697095886656 deprecation.py:337] From /usr/local/lib/python3.10/dist-packages/tensorflow/python/util/dispatch.py:1082: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead. WARNING:tensorflow:From /usr/local/lib/python3.10/dist-packages/tensorflow/python/util/dispatch.py:1082: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: `seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead. W0619 11:13:46.410009 139697095886656 deprecation.py:337] From /usr/local/lib/python3.10/dist-packages/tensorflow/python/util/dispatch.py:1082: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: `seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead. WARNING:tensorflow:From /usr/local/lib/python3.10/dist-packages/tensorflow/python/util/dispatch.py:1082: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. W0619 11:13:48.317142 139697095886656 deprecation.py:337] From /usr/local/lib/python3.10/dist-packages/tensorflow/python/util/dispatch.py:1082: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead.

[@OsamaShamim]

@EdgeElectronics please fix this as it has become a persistent error for whoever runs he script now.

[@bxoz3352]

@@OsamaShamim The problem happens if you use softwares other than labelimg for annotations If you did so try to convert them to the same annotation as labelimg and it will work

[@OsamaShamim]

@@bxoz3352 i used labelimg to make annotations. my code just keeps running at the tf.cast line and never ends.

[@vvtt7490]

same problem too did you fix it?

[@aj-fh5ky]

hi did u find fix

[@abimbolaadeola1986]

Hello! Thanks for the tutorial. It really helped a lot. But, I'd like to ask, besides the mAP evaluation metrics, how do I include other metrics such as Kappa, F1, confusion matrix, etc in order to provide more information about the model. Thanks!

[@hyagovieira1701]

i need to kkkkk

[@adamK-pl4tq]

Hello, first thank you for sharing your workflow with us. How can I get the detected objected (as text) scripted when i run the model? Any tips?

[@inspirewithfact3303]

thanks for best video ever please make the application we are waiting you ...thanks

[@cahyo.prk15]

Thanks for the helpful tutorial, but I want to make an inference on the esp32 cam, can you provide a solution?

[@osamagawish7599]

Thanks for the great content. I have some doubts, the video displaying is running at 2.7 FPS with Raspberry Pi, with you it reaches about 5 FPS, why my one is slower?

[@PraiseTheLord527]

Hey bro, were you able to complete the custom object detection... I had an issue during the training process whereby it will stop after 50s. Usually it should take several hours. I also noticed that my system Ram reached about 12.1Gb before it stopped... did yours do the same? I would be really grateful for some guidance...

[@physicsbear18]

Hi did you figure it out...can you share your experience?​@@PraiseTheLord527

[@Blv379]

Do you need to upgrade to Colab Pro for 100 compute units to complete the training? I trained for 1.5 hours but I did not see any progress on the Tensor Dashboard. My dataset consists of 200 images with objects labelled and XML files and only one class object, I used the default "ssd-mobilenet-v2-fpnlite-320" tensor model with a batch size is 16 images and num steps is 40,000 steps. I left my dataset training overnight, but it timed out. Now I have 0 compute unit so I can not connect to the backend GPU. Google does not see when I will get free compute unit again but suggested that I either upgrade to Colab Pro or Google Cloud Platform marketplace.

[@BossCat-c3h]

Hello, this video is amazing, but do you know how this trained model work on ESP32 CAM?

[@abimbolaadeola1986]

Hello. Please, is there a way to change the label style (e.g., font and size) and the colour of the bounding boxes for each of the classes drawn on the test dataset (the detection results)? Thanks

[@rupertsobrevinas3857]

Great tutorial! I have a question though. Do I need to pre process my images to become accurate or no need? I've been training my model for a weeks and I already have a 1000+ datasets but some of the datasets are not accurate. Help please.