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you're the best Felipe! short videos straight to the point, great explanations

The way you explained this topic is amazing, I enjoyed watching the video and I didn't even feel the length of it.

Thank you, very clear and easy to follow tutorial

ultimate teaching style, this was the best computer vision introduction tutorial I have ever seen on youtube as it was very easy to understand , thanks a lot Philip!!

AWESOME! Made my first working ML model. Thank you so much!!!!

Amazing job Felipe, you are helping me so much on my studies! I'm from Brazil and I will definitely use your videos to help on my completion of course work

I love the explanation and you helped me so much!

Thank you very much, Felipe, for these very clear explanations. Until now, I was making predictions for numerical values. Before watching your videos, I thought image classification was more complicated (even though this is a relatively straightforward use case). I have just one perhaps silly question: How did you create the image captures for the dataset? Was it done manually, or did you use specific software for this somewhat tedious task? Thanks again!

Thank you so much for your time, you did a great job.

You are use category_index for labels ?? I think the labels is category

Thank you so much for this Video. Makes fun and have learning effect.

Thanks a lot for your content Felipe, you're a great teacher! I'm new to machine learning so there's one thing that confuses me: how can I now utilize the the model that I've created? I understand that Pickle transforms the data into byte form and that it can be read somehow, but could you give me an example of what to now do with this data?

amazing tutorial indeed! ❤️ 👌 can you suggest me some resources where i can find some free data for training models?

Hello Sir, can we use this scikit in egg sexing for our incubator?

Your tutorial is very cool, thank you very much for helping me with your tutorial

Amazing tutorial !!, Just a question, there are many classifiers in sklearn. Why did you choose SVC specifically ?

i need your advice i have task where i need to find avarage pixal value of x-ray image object in x-ray image i have many object like pen paper palstic and so on and each intesity is different some are overlap some have no clear edegs and mixed edges can i detect or draw a boundry box around each object is it possible without ml model i am newbew in this field specially in image processing can it can be done by image process alone can i segement object if intesity of each object is different and edges are not so clear please help me i am single develpoer in my team

Could you release the data of empty and not empty for us? Thank you very much for your amazing tutorials on OpenCV and Machine Learning. It is beneficial for me to construct my own project!

Thank you for a great clear video. I am going to run it through. Yet something is missing for me: I would like to train a set of specific toy car recognition. For that I need to take pictures of the toy car , and pictures of the floor/table (where the car can be placed) for the "empty' part. Can you recommend: 1) how many pictures of each? 2) What resolution? does it matter? 3) Any other guide line you would recommend?

Hello , can u help me to know how go use my own data but i want to put an image and the code classify the image belong to any class , thank you

Great video. Is there a follow up on this to show how you can use the classifier and display the annotated image with green box and red box representing occupied and unoccupied spots in a parking lot image?

hi um i dont know why i dont know how to get data i did get from desc but i still didnt know if you could tell me that would really help

Felipe the Legend 👏🏽

Hi, please I have a project that is similar to yours and I would please like your assistance in some questions. The label being passed into the training and testing set, is it numerical or in string format? Cause I have to use labelencoder for my label before passing it into the function. Then the data being saved in the data variable is there any way I can convert them into a 4D array to be able to pass it into a CNN model? Thank you.

amazing tutorial, thanks! I had a question about the model.p file, is there some way I can open it and view its contents, I want to know how it classified, or maybe to see if the task was done as I wanted it to be done.

Very helpful ❤

Hi, great tutorial! I seem to be stuck on a problem when I execute the "grid_search.fit(x_train, y_train)" part of the code. This is the issue "FitFailedWarning: Estimator fit failed. The score on this train-test partition for these parameters will be set to nan. Details: TypeError: only size-1 arrays can be converted to Python scalars". Do you know how to fix this? I have ensured to use the correct versions (scikit learn, scikit image, and numpy) as shown in video, and followed the video step by step. This is the code for importing images i have (i had to add dtype=object when converting lists to numpy array as it was giving me visibleDeprecationWarning): for category_idx, category in enumerate(categories): for file in os.listdir(os.path.join(input_dir, category)): img_path = os.path.join(input_dir, category, file) img = imread(img_path) print(len(data)) img = resize(img, (200, 200)) data.append(img.flatten()) labels.append(category_idx) data = np.asarray(data, dtype=object) labels = np.asarray(labels, dtype=object). Finally, do you have an instagram or other site to discuss this issue, if possible?

Thumbs up for this video. I just noticed a small mistake . I think you accidentally switched the parameters for the accuracy_score function. It should be accuracy_score(y_test, y_prediction) instead of accuracy_score(y_prediction, y_test).

A great session by you sir , sir pls also share the code to input a photo in it and put it in the trained model to show the results of analysation

It helped a lot for me.

Great video, could I use this same code to classify more than 2 categories? or does it only classify in binary, like e.g empty not empty.

Im confused, which part of the code tells it that the picture has a car or not?

This is really anazing.can you make a video on how to apply GAN and use it or make it from scartch?

Great video!

Could you make another video when you test out this classifier?. Like host this online and let the user upload images of parking spaces and the program outputs 'empty' or 'not empty'. Thanks

Hi Felipe, Actually I wanted to ask that is this model build using pretrained model or not? and If it is build on pre trained model can you suggest me a video of yours where I can learn building a model with using a pretrained model

Sir, I have facing some error while training the classifier. It says : ValueError: Found input variables with inconsistent numbers of samples: [4872, 1218] It would be of great help if you solve this problem🙏

not able to download dataset

I have a task to classify cat and dog so i tried the same way you do it but the accuracy its very low i used gray scale to minimize the complicity but didont work , i want to used like this approach if you has any advice

cool video! can i possibly import this model to like a huskylens? thanks!

hi, qq how did you split the images to empty and not empty? I saw the other video where you cropped images, but how did you separate 6K+ images into empty and not empty, its not clear.

Can this prediction model be used for any set of data?

hey , great Tutorial thank you , but how do i use it now to classify new images ?

Why don't you annotate the images using bounding box or any methoda ? Is it not compulsory ? 🥲

Thanks. Is there a way I can convert the model to a tflite

How do you build up your trainig data? You won‘t have decided for 6000 pictures whether they are empty or not? Did you use kind of a „step by step“ classification? So that with lets say with 50 pictures you built up a classifier, that builds up further (and of course checked it then whether it worked properly? Thanks for your videos!

Hello, can you help me to come up with python code that classify duck eggs such as balot, penoy, abnoy according to it's classification?

Hello Sir, i used the same code, but its not giving me the output result, like don't print the accuracy... kindly help! thats what it is showing in the notification area. Shared indexes are downloaded for Python packages in 1 min, 12 sec (20.48 MB)

thank you felipe

where do i get model.p file?? it is not available in code nor data link given in description

If I have more that 2 categories of images, can I name “x_train” and “x_test” whatever I want? For example “car_train”, “car_test”, “bus_train”, “bus_test”, and “limo_train”, “limo_test”?

When i was trying to convert data and labels into numpy array, i got this error😢 ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (84,) + inhomogeneous part. What is this ? Thanks for the amazing tutorial ❤

how if I need to use CNN network? Example AlexNet?

Thank you, sir. Could you share the dataset used?

Great stuf!

how to deploy your pickle model on android app?

Ciao Fillippe, I have question about this profession in 2024 and want to know your opinion. Do I need to study any course in online platforms to become a good on it and of course finde a job(take certificate for CV). And is it easy to find a job as Comp.Vision engineer nowadays(2024 and maybe future). What can you advise me to become an engineer as you (online courses, books ect...) P.S. I really appreciate your contents, thank you for your time and effort. Hope to become a professional com.vision engineer and send you a gift from my 1st salary(but now i dont know, how to become it)

Que crack

I have 100.0% of samples were correctly classified 😁