TRAIN YOLOV5 OBJECT DETECTION MODEL ON CUSTOM DATASET 🔥🔥🔥

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#yolov5 #deeplearning #objectdetection #computervision

So in this video, I will show you how to train the YoloV5 object detection algorithm on a custom dataset.

Steps involved:-

switch to google colab (if you don't have a good PC like me :D)

8.) %cd /content/yolov5
9.) Add a yaml file inside data folder of yolov5 cloned repo, so that yolov5 wud be able to find the class images for training.

I hope you LIKE the video and do SUBSCRIBE to the channel because it will motivate me to create more of these videos!

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another great video thanks alot Sir for helping us (Students) in the object detection field.

Can you please also make a video on a Multi-label object dection in a single bounding box. I have a dataset that involves images with bounding boxes which have more than 1 label.
For example, I have 5 classes (0-4), then an image might have a bounding box with label "2" and another might have a bounding box with two labels "2, 4" ie it belongs to both categories. so how can we show two labels or classes on a single bounding box? please make a video on this or atleast provide some solution in your ans here i will be very thankful to you.

abrarluvrabit

Hello sir your explanation regarding the video is great. Keep doing more videos. But sir i tried to implement this but i can't because in git hub ultralytics for yolov5 no weight folder is available. How to train model without weight? Pls reply sir

yasminbanu

Thank you for your effort but man try to slow down when speaking and upgrade the sound quality cause I can barely understand what you are saying..

dhifallahmoemen

sir can you please provide colab notebook

chinmaymishra

Hye, Its good, Can i know are you using any some pretrained weights??

karthickraja

Wow thanks for the video
How do I train to detect pedestrian in a video using YOLO v5?

umarmuhammadi

how to run the codes using local pc like jupyter

brijeshb.r

hello can you help me
in my case after train is shows error. the error massage is:
File "train.py", line 219, in train
assert mlc < nc, f'Label class {mlc} exceeds nc={nc} in {data}. Possible class labels are 0-{nc - 1}'
AssertionError: Label class 20 exceeds nc=12 in Possible class labels are 0-11

kanamachi

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