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Its not just how you relay and explain information, its your whole personality and energy that just makes your videos feel relaxed and easier to understand. 10/10 mad props. Thank you so much Phillipe, you're amazing !
brother you did a great work. its really helpful content especially for the beginner. I watch your whole video, your way of teaching and explaining is very nice. Now i will implement this by watching your video. At the end i have two question for you first, how many images we can select for annotation in this tool? and 2nd question how we can download the open image v7 dataset for specific category ?
Thank you! I am not aware of any limit on the number of images you can annotate using CVAT, please take a look at its specs to make sure! About how to download images using open image v7, the instructions are listed in this github repository github.com/computervisioneng/train-yolov8-custom-dataset-step-by-step-guide. I may make a video about that in the future. 🙌
Hi Felipe, first of all thank you for the amazing tutorial! I'm a complete newbie and I'm learning from scratch. I need to ask you thou where did you get the file "google_colab_config.yaml", because I can't wrap my head around it
eventually high quality content detected :) thank you sir It would be great to see high-performance low-power applications, for autonomous robots and drones. you did not mention fps performance but it is crucial for real-time applications, is there any optimization method for increasing fps?
@computerVisionEngineer I would like to ask you how the class background appears in a confusion matrix if you have only trained one class or one object with one data set thank you for your help
Your videos are amazing! Clear explanations, easy to follow, and super helpful. Thanks for all you do! Can you please bring a video explaining Anomalib too?
Thank youuuu the video is just perfect, clear, detailed enough to cover all the needed parts. So thank you so much I have 2 questions please; Can we use YOLOV8 for instance segmentation/ What is the format you exported the duck mask with and to which file format you have changed it? Thanks again ❤
Hello. I have several objects in one photo for segmentation from one class. Now, when I want to convert the production mask to a binary image (0,1), it only displays one object of that class, if you have to display all the objects of that class. My code is as follows. results = model(image_1,classes=2, show=True) for result in results: for j, mask in enumerate(result.masks.data): mask = mask.numpy()*25 mask = cv2.convertScaleAbs(mask) cv2.imshow('mask', mask) I want all the objects of a class to be displayed in the binary image. please guide me.
64gb of ram, task manager shows 15% of memory being used. I run training it stays at 25% then BOOM goes through the ceiling and crashes. I tried bringing the batch to 1 but it doesn't change anything, same exact result. Wild Edit: okay, command line worked without modifying batch or anything. It trained in like 10 seconds. Don't know why it's in such a rush
Hi, do you have a video for yolo beginners where they can learn how to use the existing model? I need to make a solution where an ipcamera is connected to a rp5 or other computer to detect if there are both a person+bike on the image. Could you help? thx
Hiii, great video, but i want to seek a help from u in my master's thesis work as im planning to use yolo for peach fruit detection, I've taken around 250 images having fruits using iphone but the fruits are overlapping as well as occluded by each other and leaves and no one is guiding me how to deal with annotating in such condition, also i have to increase my datatset using augmentation..., So please guide me with this, if i could somehow connect with u on e-mail or something i would share my dataset with u for reference. It would an immense help from u... Waiting for ur positive response 🌝!!!
Hey, great content there I have been watching your videos and learning alot, do you have any tutorials on how to train Faster RCNN using a custom dataset locally? Thanks
Hey thank you! Glad you find the videos useful! 💪💪 You can train a Fast R-CNN on your custom data using detectron2, take a look at my video on detectron2 here ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-I7O4ymSDcGw.html. Go to detectron2 model zoo (github.com/facebookresearch/detectron2/blob/main/MODEL_ZOO.md) and look for the one that says 'Fast R-CNN'. 😃🙌
Please help, I downloaded the data from OID toolkit, but the labels containing .txt files has the name of the class instead of a float/int and hence during training it throws an error of cannot convert string to int. What to do in such case
maaf pak, izin tanya setelah data berhasil di latih untuk dapat digunakan sebagai tracking objek langkah selanjutnya bagaimana pada tutorial pertama custom dataset alpacha.. 🙏
Hello, thank you so much for this video ! I trained my model, but the labels can't be found and I do not know why. The labels have the same names as the images, they are in .txt , yolo format and in the folder "labels". And I have used the ultimate path. Do you have any idea why ?
@@abhisheknegi2888 I have found a solution. In my case, I have the "images" and "labels" folders. In both of them, I have "train", "val" and "test". Then I put all the labels in the three folders present in the "labels" folder. I hope my explanation is clear. Good luck
Very nice , As for the segmentation , How can I generate this label folder of txt files if the images is not binary , but contain for example 3 different segmented objects in the same images ?
Thank you Felipe. Your videos are always top-notch. Please can you make video on Online Exam proctor, i.e preventing online examination malpractices and cheating through computer vision? We would like you to make the video ASAP
hello, I'm have a question, if do more than one class in CVAT, how I use the code "mask to polygon"? because apparently the binary segmentation just use in two classes, therefore 3 classes will appear (2 CVAT classes and background)
If your data is comprised of more than one class, you would need to make some edits in the script. If you need assistance you could try creating an issue in the github repository. 🙌
By the way yolov8 works, the labels will be loaded from a directory called 'labels'. If not mistaken there is no way to change this from the config file. 🙌
Hey i am having issues, after training the model when i apply it to the video it detects nothing, like no object detection. i am using a dataset of 100 images
Hey, you may need to use more images, 100 images may not be enough to train an object detector. Also, how many epochs are you using? Make sure you are not overfiting or underfiting. 🙌
Hi , for the object detection part , can you make a video on how you download the data from open images dataset , i tried the steps but have error . Thank you in advance
Is this method actually used? Annotating by hand? Because for actually training a simple model you need at least 10k of images and for more complex ones up to a million
Yes, sure, manually annotation of images is actually used. There are some technics to 'automate' the annotation process, but they usually require some degree of manual intervention too.
@ComputerVisionEngineer I don't think manually annotating is used anywhere for a real project. Next time definitely show how to automate the process by generating the dataset. For example get 100 alpaca images and 100 background images and make 10000 combinations with them for the model to train
Very good video, really appreciate the effort. I am doing a project to detect the car's fuel pannel is open or closed, how many images should i train the model for?
Take a look at the github repository of object detection tutorial. You will find instructions regarding how to download the data from open images dataset v7.
Can anyone explain why confidence score is coming "0" after training ( 3 epochs ) and NO bounding box in coming in validation prediction? @ComputerVisionEngineer
@@ComputerVisionEngineer i have done step by step exactly same as u have done in this video ( object detection ). I have downloaded the same dataset as of yours
Great, great, only in segmentation we can change the color of the mask? Because the color of my object is very similar to the color of the mask and this is not very interesting in the display.
@@ComputerVisionEngineer when i test the training network. It defines the border and the object with one color, for example, in your training video, you defined the ducks with pink color (in the output). Can this color be changed?
That's a good tutorial. I have a question. If there is coffee when several foods or drinks are classified into large categories in yolo, is it possible to classify them in coffee? For example, can we do object detection like espresso, americano, cafe latte, etc?
Yes, it is possible to do object detection using espresso, americano, cafe latte, etc. as labels. It all depends on the data, if the drinks are served in transparent cups I would say it is possible. 💪🙌
Great video! I was just wondering how were you able to get the predictions for the prediction image? I've been running more data and epochs, but I still don't get any predictions... do you have any tips?
Classification is the process by which you want to categorize or group something based on some features or properties. Example: imagine you have a soccer ball and a tennis ball and you want to classify it. Obviously, a soccer ball is bigger than a tennis ball, so SIZE is what you used in grouping them. Detection on the other hand is the process of identifying if a particular thing is present in a time space. Example: imagine you want to know whether a soccer ball or tennis ball or both balls are present on a pitch. This does not group the balls, it tries to determine whether they are present or not. I hope that helps
Image classification focuses on assigning a single label to an entire image, while object detection detects and localizes multiple objects within an image, providing both object presence and spatial information. 💪🙌
@@ComputerVisionEngineer If I check the box 'save images' I've this error: Could not export dataset for the task 210656 Error: exporting task dataset with images is not available. Upgrade the account to extend the limits. I'm trying image recognition to identify mathematical curves 🙂
@@ComputerVisionEngineer 225, I think is not a lot. And It's not possible to add additional images in the CVAT task detail page? If I've annotated 225 images and I want to add 200 other, how do?
Thanks for sharing a great video. I have a question if I have 4 classes: person, car, truck, dog. In which I only want to get the keypoint of the person class and the rest of the classes will not have the keypoint, how do I need to build the data to train? Looking forward to your answer.
Do you want to detect keypoints for the person class and only bounding boxes for the remaining classes? You could apply 2 models; a keypoint detector for the person class and an object detector for the remaining 3 classes.
Please, did you use annotation for the videos you used to test the trained model? I wished you really showed that part. Also, does it make any difference using a totally different data to test the model? Also, is there a reason why you used the same training set as your validation set? Did you make use of the output of the training for the prediction?
@@olanrewajuatanda533 I downloaded the dataset from the open images dataset v7. In that tutorial I used the same set for both training and validation just for simplicity, it is obviously better to use a separate set for validation.
@@ComputerVisionEngineer yes, I am referring to the object detection tutorial. Please, can you drop a snippet of how the test video can output the number of objects it detected in the video and the inference as well?
Brother please help me I have a problem I have a problem I have been trying to solve for three months and I could not solve it please I want to contact you on Facebook or Instagram or Telegram
