Hope you enjoy this video! Here's what I cover: 00:00 | Intro 00:55 | Preview what we will build 01:35 | Creatung a Custom Vision project 03:01 | Upload & tag the images 05:41 | Train the model 06:30 | Evaluate / test the model 07:42 | Export & download the model 09:10 | A first look inside the web app 10:32 | Integrating the model with TensorFlow.js 15:45 | Checking the results 16:12 | Performance Optimizations … and more info here: The GitHub repository github.com/SaschaDittmann/tfjs-cv-objectdetection The dataset I used to train the model, can be downloaded here github.com/microsoft/AIVisualProvision/tree/master/Documents/Images/Training_DataSet TensorFlow.js Image Classification Made Easy ua-cam.com/video/WFUL_oRT3nk/v-deo.html
Hello Friend. tanks for the tutorial. I have an error to tray to run you proyect, in the console appeear this Uncaught Error: Based on the provided shape, [3,3,3,16], the tensor should have 432 values but has 363 and the proyect dont work. how i can solve this. Tanks and regards.
He sascha, nice tutorial! Thank you, that's what I actually needed. Too bad azure don't allow my debit card for the free trial. Do you have another approach?( Without azure)
Getting this error in console. Model is loaded. Did not changes to the clone git Uncaught (in promise) Error: Cannot infer the missing size in [-1,0] when there are 0 elements
Hello Thanks for your tutorial can you help me with one little problem i am getting this error with my own Model Uncaught (in promise) Error: TensorList shape mismatch: Shapes -1 and 3 must match at lv (util_base.js:108:11) at OO (tensor_utils.js:28:3) at e.t.setItem (tensor_list.js:229:5) at control_executor.js:241:18 at u (runtime.js:45:40) at Generator._invoke (runtime.js:274:22) at Generator.forEach.e. [as next] (runtime.js:97:21) at Um (runtime.js:728:43) at o (runtime.js:728:43) at runtime.js:728:43
Hey Sascha, I'm struggling to get you project running correctly with an own model. I trained a new model in CustomVision and just replaced your model in the project with my own new one, and I do get results, but the probabilty is a lot different from when I quicktest the exactly same image directly in Custom Vision. A prediction that gets a probability of 92.1% via the quicktest only gets a probability of 55%.
Nevermind, I found the problem: if (is_new_od_model) { console.log( "Object Detection Model V2 detected." ); image = is_new_od_model ? image : image.reverse(-1); // RGB->BGR for old models } With the wrapping if statement the image never gets converted to BGR for an old model. I moved the line and now the precision ist a lot better. (Still not exactly as good as directly within CustomVision, but they probably do even more pre-processing.) I created a Pull-Request in your github repository moving that line 😊
There are two different model versions, which might be created by the Custom Vision service. I use the output of the prediction (length of the array) to check which model version was used.
Thanks for this tutorial. But I had a little problem, the predictions could not be made, localhost continued to show "running predictions" but it never finished. I don't know why, is it because of my big model? My model reaches 61 bin files. Please help me
@@SaschaDittmann same here as Arib Bachmid I get I got "Error : Activation leakyrelu has not been implemented for the WebGL backend" can you help? I get this after optimization. In the json file it seems that leakyrelu changed to leakyrelu_alpha, maybe this is the problem? Thanks in Advance and for this awesome video
Hi! sorry to reach out to you in this rather awkward way but im really at the end of my rope and cant find help anywhere. Ive got a problem with azure customvision regarding your video about simple image recognition. I am adding my images (of fruits) and after training my model has 100% precision/recall and ap ... this makes the model completely useless. Do you have any idea what im doing wrong or where to find help?
@@SaschaDittmann Hello! thank you so much for answering. 1. 400 images total, 2. 200 images per category (banana/apple) 3. I am not aware if i do, so probably not. Images of fruits are downloaded from www.kaggle.com/moltean/fruits
Hi Tom, there is a free, as well as a paid, offering for Azure Custom Vision. The free instance currently contains: - Up to 2 projects - Up to 1 hour training per month - Up to 5000 training images per project For more details about both offerings, please have a look here azure.microsoft.com/en-us/pricing/details/cognitive-services/custom-vision-service/
Херня какая то, при регистрации пришлось засветить карту банка. И там нет тарифа бесплатного, есть тариф "с оплатой по мере использования". В ролике много вырезано. Интерфейс отличается координально. После регистрации сразу начнутся проблемы с пониманием и попытками повторить. Забейте, не тратьте время...
@@SaschaDittmann Ты на своём "бесплатном" аккаунте демонстрируешь тренировку 24 часа, хотя бесплатно только 1 час в месяц, судя по данным из твоей ссылки.
Hope you enjoy this video! Here's what I cover:
00:00 | Intro
00:55 | Preview what we will build
01:35 | Creatung a Custom Vision project
03:01 | Upload & tag the images
05:41 | Train the model
06:30 | Evaluate / test the model
07:42 | Export & download the model
09:10 | A first look inside the web app
10:32 | Integrating the model with TensorFlow.js
15:45 | Checking the results
16:12 | Performance Optimizations
… and more info here:
The GitHub repository
github.com/SaschaDittmann/tfjs-cv-objectdetection
The dataset I used to train the model, can be downloaded here
github.com/microsoft/AIVisualProvision/tree/master/Documents/Images/Training_DataSet
TensorFlow.js Image Classification Made Easy
ua-cam.com/video/WFUL_oRT3nk/v-deo.html
And that's what I need. Thank you very much Sascha.. And I am asking for more.
You're welcome!
I'll be sending out a poll later this week on my community tab, what I should create next. 😉
Hello Friend. tanks for the tutorial. I have an error to tray to run you proyect, in the console appeear this Uncaught Error: Based on the provided shape, [3,3,3,16], the tensor should have 432 values but has 363 and the proyect dont work. how i can solve this. Tanks and regards.
Did you clone the repo or download it as zip file. I use Got LFS which messes up the model bin files when using Download as ZIP
I can't get past the error:
"Error: The shape of dict['Placeholder'] provided in model.execute(dict) must be [-1,416,416,3], but was [1,2560,1440,3]"
Great Job Sascha!
He sascha, nice tutorial! Thank you, that's what I actually needed. Too bad azure don't allow my debit card for the free trial. Do you have another approach?( Without azure)
Getting this error in console. Model is loaded. Did not changes to the clone git
Uncaught (in promise) Error: Cannot infer the missing size in [-1,0] when there are 0 elements
Hello Thanks for your tutorial can you help me with one little problem i am getting this error with my own Model
Uncaught (in promise) Error: TensorList shape mismatch: Shapes -1 and 3 must match
at lv (util_base.js:108:11)
at OO (tensor_utils.js:28:3)
at e.t.setItem (tensor_list.js:229:5)
at control_executor.js:241:18
at u (runtime.js:45:40)
at Generator._invoke (runtime.js:274:22)
at Generator.forEach.e. [as next] (runtime.js:97:21)
at Um (runtime.js:728:43)
at o (runtime.js:728:43)
at runtime.js:728:43
Hi, i got the same error, did you find a solution?
is there anyway to
1. change box style (which one around image)
2. crop and save detected area to image file
Hey Sascha,
I'm struggling to get you project running correctly with an own model. I trained a new model in CustomVision and just replaced your model in the project with my own new one, and I do get results, but the probabilty is a lot different from when I quicktest the exactly same image directly in Custom Vision. A prediction that gets a probability of 92.1% via the quicktest only gets a probability of 55%.
Nevermind, I found the problem:
if (is_new_od_model) {
console.log( "Object Detection Model V2 detected." );
image = is_new_od_model ? image : image.reverse(-1); // RGB->BGR for old models
}
With the wrapping if statement the image never gets converted to BGR for an old model. I moved the line and now the precision ist a lot better. (Still not exactly as good as directly within CustomVision, but they probably do even more pre-processing.) I created a Pull-Request in your github repository moving that line 😊
awesome...
what is version 1 or version 2 @_@" how do we know the version?
There are two different model versions, which might be created by the Custom Vision service. I use the output of the prediction (length of the array) to check which model version was used.
Hello, Do you have a tutorial to implement this to node-red?
I‘m sorry but no. But I‘m happy to add that to my list of ideas
Thanks for this tutorial. But I had a little problem, the predictions could not be made, localhost continued to show "running predictions" but it never finished. I don't know why, is it because of my big model? My model reaches 61 bin files.
Please help me
Might be the large model. Please check with the developer tools in your browser, if you get an error message.
@@SaschaDittmann In console I got "Error : Activation leakyrelu has not been implemented for the WebGL backend"
@@SaschaDittmann same here as Arib Bachmid I get I got "Error : Activation leakyrelu has not been implemented for the WebGL backend" can you help? I get this after optimization. In the json file it seems that leakyrelu changed to leakyrelu_alpha, maybe this is the problem? Thanks in Advance and for this awesome video
got this: replace the thensflow script with
Hi! sorry to reach out to you in this rather awkward way but im really at the end of my rope and cant find help anywhere.
Ive got a problem with azure customvision regarding your video about simple image recognition. I am adding my images (of fruits) and after training my model has 100% precision/recall and ap ... this makes the model completely useless. Do you have any idea what im doing wrong or where to find help?
Hi Jeremiasz,
How many images are you using?
Do you have a fair amount for each kind of fruits?
Are you using any kind of Image Data Augmentation?
@@SaschaDittmann
Hello! thank you so much for answering.
1. 400 images total,
2. 200 images per category (banana/apple)
3. I am not aware if i do, so probably not.
Images of fruits are downloaded from www.kaggle.com/moltean/fruits
make a video on runtime detection on webcam
Great idea! Thank you!
is it free for azure training model ?
Hi Tom,
there is a free, as well as a paid, offering for Azure Custom Vision.
The free instance currently contains:
- Up to 2 projects
- Up to 1 hour training per month
- Up to 5000 training images per project
For more details about both offerings, please have a look here
azure.microsoft.com/en-us/pricing/details/cognitive-services/custom-vision-service/
Херня какая то, при регистрации пришлось засветить карту банка. И там нет тарифа бесплатного, есть тариф "с оплатой по мере использования". В ролике много вырезано. Интерфейс отличается координально. После регистрации сразу начнутся проблемы с пониманием и попытками повторить. Забейте, не тратьте время...
If you are looking for the free offer details, checkout this link:
azure.microsoft.com/en-us/pricing/details/cognitive-services/custom-vision-service/
@@SaschaDittmann Ты на своём "бесплатном" аккаунте демонстрируешь тренировку 24 часа, хотя бесплатно только 1 час в месяц, судя по данным из твоей ссылки.
@@АнатолийП-я2н I'm sorry that it came across that way. I should have emphasized this more clearly.