How To Prepare Datasets For Training YOLOv5 Object Detection- Official - YOLOV5 Training
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- Опубліковано 29 чер 2024
- Watch this video to learn how to prepare a dataset for training a Custom Object Detector using the official YOLOv5.
We discuss the dataset format for YOLOv5 as well as provide tips on how you should prepare a dataset that allows your model to learn efficiently. We also talk about how to perform a train-val-test split and discuss how variance in data is a primary ingredient for learning a robust model.
❓ FAQ
How would you prepare a dataset for object detection?
How do I train my YOLOv5 with a custom dataset?
What is the name of the dataset YOLOv5 model used to detect objects?
How many epochs should I train YOLOv5?
📚 Link to the blog post of this video:
learnopencv.com/custom-object...
🎵 YOLO Master Class Playlist:
• YOLO Master Class: Mas...
⭐️ Time Stamps ⭐️
0:00-00:20: Introduction
00:20-2:38: How to prepare your data
2:38-6:12: How to create a Dataset
6:12-8:18: Directory Structure
8:18-9:02: Tools required
🖥️ On our blog - learnopencv.com we also share tutorials and code on topics like Image Processing, Image Classification, Object Detection, Face Detection, Face Recognition, YOLO, Segmentation, Pose Estimation, and many more using OpenCV(Python/C++), PyTorch, and TensorFlow.
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Hello Sir, I'm Wakil Kumar. Please tell me about ANPR --- Automatic Number plate detection and recognization step by step ... Please ...
using Yolov5 and Pytorch and ML models
Thank you Satya for clear information, your way to teach is the difference! Top!
I am watching the whole YOLOv5 series to learn how to customize my object detection model and I'm finding it incredibly useful. Thank you so much for the high quality content you share with us. Greetings from México!
Glad to hear that! Please subscribe to our channel to never miss out on the YOLO series!
Thank you so much. I really like your videos.
Amazing tutorial
good and clear explanation
THANKS for this video, can you tell me how you get around the "catastrophic forgetting" notice when adding new classes and training data to an existing model?
This is the second video of yours I have watched and you explain everything so beautifully. I am a complete beginner want to use a subset of Google's Open Images but can't figure out how to create YOLO format annotations.
Hi, our tutorial notebooks usually cover the dataset annotation conversion. You can also find datasets in YOLO format.
Thanks for informations
Chapters
0:00-00:20: Introduction
00:20-2:38: How to prepare your data
2:38-6:12: How to create a Dataset
6:12-8:18: Directory Structure
8:18-9:02: Tools required
📚 LINK TO BLOGPOST: learnopencv.com/custom-object-detection-training-using-yolov5/
▶ LINK TO YOLO MASTERCLASS PLAYLIST: ua-cam.com/play/PLfYPZalDvZDLALsG9o-cjwNelh-oW9Xc4.html
Thanks
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Very nice and well done explanation.. Congrats.. Do you do Consulting or custom trains ? How can I contact you? Thanks
We do AI consulting. Please send an email to contact@bigvision.ai with details of the project and we will follow up.
Satya, can you help me with one question? What is the best pratice when using zoom level in the step of mark the object, drawing the bounding boxes? For example I'm labeling a class that appears in front of the image and there's another class that is in the end (3d) of the image and for it I need to use the zoom. Sometimes I made this questions, until which level I can use the zoom because pixels will be explosed and than maybe It's not good to use a high level of zoom. Thanks.
I do not fully understand the question. Can you please share a link to an image so I can better understand it?
Hi! Thanks for the video. I trained custom object. But when two objects come too close it detecting as 1 object. How can I fix this?
i am not sure but you can do like if two object are above 70% similar with picture than write in log "Class_$"number_of_class" "+ " detected in picture"
Hello sir, what exactly does 1 file per image mentioned @ 01:20 means
I have prepared data set in XML format can be used for yolov5 algorithm
No, you cannot use XML format to train YOLOv5 models. Use the .txt format.
Is the picture of images matter? for example if i want training using img 640 can the data larger or smaller than training size?
Yes, it can be.
is there any script can do the same work so we don't waste time on doining this manually ?
Hello Rihab. Mostly, everyone writes their custom script depending on the raw dataset structure. But Roboflow already provides datasets in YOLO format and many other formats as well in case you need it.
Thank you so much, I just have a question, is that okay for txt file that has the information of annotation has the shape of a polygon not a rectangle?
I don't think so. How would YOLO understand what your measurements mean?
Great content (much appreciated) but very annoying background music.
Hi, thank you for the feedback. Your comments have been passed to the media team. We have much more videos on YOLO models. Check out the playlist section for the YOLO Master Class, or other playlists.
Do I really have to mark every picture with the object myself? That is a lot of non-automated work. Can I simply place pictures which include only the object and let the software do the labeling?
You can employ CVAT's automatic annotation tools. Checkout the video here: ua-cam.com/video/R-XXSn2ahOE/v-deo.html
@LearnOpenCV From this video it looks like I have to mark the points for the polygons. I wonder if there is a way to let the machine automatically identify the objects (assuming that I place in separate folders) and create Yolov5 model.
Yes. In the later parts of the video, we show annotating objects using ai models.
what about polygon annotation???
You can create polygon annotations in CVAT. Check this video tutorial: ua-cam.com/video/YL0l2MYUFC0/v-deo.html
CVAT Tool complete tutorial playlist: ua-cam.com/play/PLfYPZalDvZDLvFhjuflhrxk_lLplXUqqB.html