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Hello guys, there is a BIG MISTAKE IN VIDEO - this guy made incorect link to the yaml file. here is the correct linking an yaml: results = model.train(data=os.path.join(ROOT_DIR, "/content/gdrive/My Drive/Datadata/config.yaml"), epochs=20) instead of linking like he - without writing a directory to yaml file, typing only the name of yaml.
if i want to train object detection for multiple object classes, then if i just dump all the images into the images/train and all the labels under labels/train will that do? Or do i have to have seperate folders for each and every object class?
Permission to ask sir, how do you label data automatically?, because if the amount of data is labeled manually, for example 80 thousand, it will take a long time.
There are different strategies; one of them is to annotate only a subset of your data (1% for example) and train a model with that data, then use the model you trained to make predictions on 10% of the data, and then manually fix those annotations (it will take you less time fixing them than annotating them from scratch). Then do the same increasing the size of the curated annotated dataset incrementally until it reaches 100%. 🙌
Hi! We are creating a system that classifies tomato ripeness levels using image processing in CNN architecture with the YOLOv8 model. We are using Raspberry Pi 4 OS with 4GB RAM and we have encountered a problem - the system has 2-3 minute delay/lag in classifying the ripeness level. Would you happen to have any recommendation/suggestion sir on this problem?
Thanks for this tutorial. I didn't see how you normalized the images before training. Could you please explain more about image normalization for YOLOv8 training?
I am a student from Sri Lanka. can you please let me know how to download the data from open images. but I don't have money. sir can you please help me 🙄
Can you tell me or point to a resource that will explain how to train a custom model that can detect two different objects using separate images of one thing (say one set of images of cats and one set of dogs ) . Please and thank you.
really helpful video! I just ran onto one problem. When I run the 5th cell, there's an error saying "NotImplementedError: A UTF-8 locale is required. Got ANSI_X3.4-1968". Please help mee
Hi. I downloaded a dataset from roboflow with three folders: train, valid, and test. 1. First question: Do I need to transfer my test images and labels to the valid folder? 2. The code of "model.train" is not working. It's probably because of the yaml file. The error says, "Dataset '/content/gdrive/My Drive/Object Detection project/data.yaml' images not found ⚠, missing path '/content/datasets/content/gdrive/My Drive/Object Detection project/valid/images' Note dataset download directory is '/content/datasets'. You can update this in '/root/.config/Ultralytics/settings.yaml' ". What should I do now?
How can we download images from Open Image Datasets? There is no download option. And also how can we train our custom dataset without using Google Collab. I want to use pycharm ide. By the way, thank you
Hi, take a look at my other video on how to train a model with yolov8, I explain how to do it without using a Google colab. The instructions on how to download images from the open images dataset are available in my Patreon. 🙌
Very good video, but I have a question how can I make it predict or detect with a video that I have in google drive and show me the result with the tags in it?
Try with this script from my github repository github.com/computervisioneng/train-yolov8-custom-dataset-step-by-step-guide/blob/master/local_env/predict_video.py Edit video_path and video_path_out to the locations in your google drive. 🙌
Hi are you able to use cuda cores of the tesla t4 gpu while training. It should automatically detect a gpu if it is present...as given in the ultralytics documentation...thats not happening for me and by default a cpu is being selected which are increasing the training time...do yo have any solution for the same?
Hi, I dont have a problem when using a Google colab, but if I train in an ec2 instance with gpu I need to install the cuda drivers first and also need to install a specific version of pytorch. I explain it in my video on training yolov8 in the cloud. 🙌
Thanks for the prompt reply....I was somehow able to circumvent the problem....thanks for the info regarding ec2 instance too... that was very helpful...will check the video...@@ComputerVisionEngineer
Love the simplicity of the way you teach, it's training right now I hope it works. One question, after training the model how can we test on Colab like giving it other images and see if they detect the object ?
Thank you! This is a script you can take as a reference on how to make inferences github.com/computervisioneng/train-yolov8-custom-dataset-step-by-step-guide/blob/master/local_env/predict_video.py 🙌
Permission to ask sir, I caught a problem with my training session, I tried to train the module with "epoches=300"( I was told that its the ideal value), but when I run that training session, It just reaches into epoches 189/300 and then it stopped automatically. Is there a way to fix it sir? Thank you for the really helpful tutorial.
Hi, there are some limitations with google colab, after a few hours the session is interrupted. Maybe that is what is going on. You could train the model using a cloud server, for example an EC2 instance in AWS.
Thanx for the tutorial. As far as i know on your example you have results for training and validation data. what if we want to test it on another test dataset and get the results (f1 score, recall etc. l) from it? I mean if we have test dataset as a whole and we want to get performance results on that dataset? What do we do?
If not mistaken I think you can specify a test set in the yaml config file. If that is not possible, you would need to inference the entire test directory and compute your desired metrics yourself. 😃🙌
How do i feed test data into this model? Like if I want to put random images from the internet that the model has never seen before for it to identify objects in the image?
Take a look here docs.ultralytics.com/hub/inference_api/#detect-model-format. Basically, you need to do: model = YOLO(model_path) results = model(image_url)
Vscode you mean the ide? Take a look at my other video on object detection + tracking using yolov8, I used Pycharm in that video but it s pretty much the same.
@@SalwaZiada Technically, yes, you would need to check the performance of your model on a test set. In practice, I just check the accuracy by looking how it performs on the validation set, I consider this is enough for most projects.
Thank you so much for the tutorial. I have trained the model and it gives satisfied results on images that I now give it. Please tell me (or please make a video about this) the process that how do i save that model and use it in a mobile application in Python that uses this model to detect the ingredients and then processes that list of those ingredients to generate further results. Also which platforms should I use for the coding and stuff. Please let me know, I have a project to complete, by the end of this week.
Thank you for your support! You can send me an email, but sometimes I am a little too busy to reply, I receive too many emails. If you have a question about the tutorials please post it on Discord. 😃🙌
