YOLOv5 training with custom data
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- čas přidán 5. 09. 2024
- YOLOv5 training with custom data.
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YOLOv5 chicken detection.
YOLOv5 working with single class.
YOLOv5 image labeling/bounding box
chicken detection YOLOv5
YOLOv5 train on cloud (google colab)
Turn any camera into A.I object detection camera:
• Turn your IP camera in...
#YOLOv5
#customDataset
#imageAnnotation
#makesenseAi
Thanks a lot for this video! Not only did you present everything really well, but also there wasn't anything in this video that I missed or didn't understand. It's good to be learning such complicated implementations with such ease!
Please do you know how i can display number of objects in the video
@@umarmuhammadi429 I think you should count number of objects in each frame
Yes
Please do you know how i can do that
@@umarmuhammadi429 I am interested in this too
Wow, this explaination is one of the best I can find on CZcams! Thanks for your effort!
For the first time I could execute something in the very attempt! Thanks to you Sir!!! This was seriously awesome.
Thank you for such a amazing video about YOLO, had almost everything needed in it ❤
You explained this quite well man. Thanks a lot for such a great video. I do not comment on any channel but I couldn't stop myself from commenting on this video of yours. You are doing great man, best of luck for the future. Please do make videos on object detection using Reinforcement learning, it would help me a lot. I subscribed to your channel and liked your video, thanks man.
The official colab notebook has changed since this video was made but still very useful! Thank you for your work!
Thank you for the great tutorial and extra points for the chickens. I LOVE chickens!
Thank you soooo much. Finally after two days, I was able to do my class project ❤
Thank you very much! You helped me a lot with your clear explanation. I spent my whole day trying to get YOLOv5 up and running. Then I found your guide, followed it and everything works now.
dear can you plz tell me how he unzipped the file i wrote the same code but it says unzip: cannot find or open ../train_data.zip, ../train_data.zip.zip or ../train_data.zip.ZIP.
i encounter the same error ,and the problem maybe we compress all the files together. and it works well when i seperate this files to upload ,hope this can help you.@@abprojects7477
Yup I've also similar error is there any sol
@@abprojects7477did u get the solution
@@nandininandu8375did u get the solution
Thank you so much bro. I can't believe that I have done an object detection model in just one day.
lol.....I got that memory error too, but I paused the video and never saw that you got it too and I spent an hour figuring out the same fix. Then I came back and resumed the video and in probably 10 seconds you changed the batch size lol....
Life🙃
Wow, the explanation is so clear and straightforward! Thank you sir!!!
Gracias por tomarte el tiempo de hacer este vídeo, no sabes lo útil que me fue, te juro, no tienes ni idea. Te amo.
1thanks a lot!! was looking for a simple way to detect object and found this channel. Subscribed
BEST TUTORIAL I EVER FOLLOWED! THANK YOUUUU!!!
Wow best explanation really am so happy by watching this video and many students get some thing especial.
Thank you very much, been looking for this explanation. Many thanks
It's brilliant.!! Thanks for the amazing video!! Really helpful!!
Thank you for this great video, all the best 👍🏻
bro, I did this more than 4 hours and repeated many mistakes but I finally succeeded, that's an achievement for me :).
I have no words to express my gratitude towards you. Thanks a ton.
Thank you! This is just what I was looking for!
Wow
Thank you very much for this tutorial it helps alot
It's very clear and straightforward 🤗🤗
excellent man,thank you for this video.look forward more such videos.
Thank you so much. Very clear explanation!
Thankss. This video was really helpful in my project 😃.
My man, you absolutely murdered this explanation. I would add #objectdetection, etc. to the description to help youtube/other people find this video faster (I was riding the struggle bus hard until I found this video lol). Cannot thank you enough!!!
Very well done. Easy to follow.. you’ve got a new subscriber
wahoo I'm stupefy, very good explanation. Thanks to you, I more learned about this topic
Thankyou for this video! How to turn on Webcam and do object detection in real-time...can please say what changes should be done?
What a great Explanation. very thanks it help me a lot in sport analysis matches.!)
This TUTORIAL IS 100% WORKING GOOD TUTORIAL
Thanks man, very helpful video.
Thank you so much for this useful tutorial!
hello sir please do the same video for yolov8 also using webcam I mean for real time detection also
Bro you're a god
Thanks a lot for this amazing easy to follow tutorial
thank you, finally, I am able to identify chickens.
good tutorial, keep going on man!
come on man... you forgot a chicken in tha cage🍌
I cannot Thank You enough for this.
thank you for the video!
Thank you very much! Nice video!
Hello, thank you so much for this beautiful tutorial. Please, could you also do a tutorial on how to deploy this model live?
I have followed all the steps in the video, but my training only has 66% accuracy and when I try to predict and their is no prediction/bounding boxes. The results image has no labels.
Does anybody know why is it? thanks in advance
Thank you Sir... It is really to the point and informative... Really too helpful
Hello Instructor, thanks for this amazing tutorial, please give us that video link of chickens, please upload it somewhere and provide us with link.
Help appreciated...
Hi this video was really good i found out i really like machine learning and that i chose my middle school right also i love the way you say chicken
you are so good at teaching!
Thank you bro for this tutorial ,you're Amazing
thankyou sir that was useful. i trained using my own dataset but no matter how long i trained it the m@p will not get improved from 0.34 something like that i have used same data for yolov4 but it performs well
Thank you. It's settled thanks to you.
could you please help me? i tried to unzip train data few times, it always comes out like this: unzip: cannot find or open ../train_data.zip, ../train_data.zip.zip or ../train_data.zip.ZIP.
what should i do?
Really a lifesaver 👍
If you like to support my channel, here is link www.buymeacoffee.com/biplob004
Thank you so much........for sharing your knowledge.............
great video and explaining. I did everything as you mentioned but the model can't detect any image from the video. although it does detect it in the runs. .
thank you so much. Very good tutorials.
ı got error
AssertionError: train: No labels in /content/yolov5/../TryMe/İmages/train.cache. Can not train without labels.
can u help me ?
iam facing the same issue can u help?
you got the fix or not
Thank you so much bro. God bless you.
I love you ♥
Hello good man.
I quickly tested your video, I like how you explain and kudos to you for your knowledge.
I took a picture of a table lamp 10 times, 3 pictures are for validation and I recorded a video for 10 seconds, with an iPhone 13 Pro. I didn't succeed in processing the video, the pictures are trained... I don't know if it's because I converted MOV to MP4...or if there's something else at play.
i am getting an error. can you please help me with it? 'IndexError: boolean index did not match indexed array along dimension 0; dimension is 0 but corresponding boolean dimension is 4'
hey have you found solution
Same problem...
@@DeepanshuBCS no not yet
Thank you for this amazing tutorial....................
I need guidance for Final year project how I detect and recognize multiple faces from single image. thank you in advance
hi, i can help you in this. Contact me on google chat / google hangout , at biplob00110011@gmail.com
how to unzip train data, sir? i can't do it in step .
Very useful, tks for sharing!
Hello. I am trying to follow your video but some things have changed on colab
This is my yaml file.
train: ../train_data/images/train # train images (relative to 'path') 128 images
val: ../train_data/images/val # val images (relative to 'path') 128 images
test: # test images (optional)
# Classes
names:
0: pothole
This is the error I get in training part.
Transferred 739/745 items from yolov5x.pt
AMP: checks passed ✅
optimizer: SGD(lr=0.01) with parameter groups 123 weight(decay=0.0), 126 weight(decay=0.0005), 126 bias
albumentations: Blur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))
train: Scanning '/content/train_data/labels/train' images and labels...0 found, 500 missing, 0 empty, 0 corrupt: 100% 500/500 [00:00 0 or not augment, f'{prefix}No labels found in {cache_path}, can not start training. {HELP_URL}'
AssertionError: train: No labels found in /content/train_data/labels/train.cache, can not start training. See github.com/ultralytics/yolov5/wiki/Train-Custom-Data
Please help me out. I really want to get this done for course project. Thank you
Did you find any solution for this. I'm also getting this error.
That's the great one. Thanks!!!
Great video, thanks man!
It was great👍 thank you , keep it up
Excellent Work Brother..!!
Thanks ✌️
Please support my channel here www.buymeacoffee.com/biplob004
Brilliant Video, how to fine tune the model for face recognition?
1. I'm getting 2 boxes on the same face for face recognition, for classes where the data was not sufficient
2. Some faces are just labelled wrong
Thank you very much for the video it really helps me,
I have a small question: if my computer does not support cuda how can I solve the errors due to the layers: dnn and fft?
I would really appreciate it if you could help me, I really need it
Thank you so much
From VietNam. Thanks
you saved me bro, thanks!
very helpful... thank you sir
Great video. Subscribed. I have 2 questions: 1. All images in train val dataset should be of same size. if it is not what to do? also, testing image size should be same or not?
You are amazing thank u so much ❤❤❤❤❤❤❤
great video thank you
This is wonderful easy to follow tutorial. How can we tell the validation loss please
Hi every one. Thanks a lot for this short and sweet Tutorial .
I have a question and it is about image size in YOLOv5. is it in 640 *640 ? and can we use another size? if so , HOW?
Thank you in advance
Yes, you can use any size you want
do you want to take live tuition from me? If interested then reply to this comment.
thank you very much for the tutorial it was very beneficial. though i have a question @DeepLearning. how can i extract the custom_weights and custom_config files for deployment in object detection on a raspberry pi.
You can use your weight file (last.pt or best.pt) and load this trained models using pytorch. After loading you can use it combined with opencv.
@@marcelofsouza1 how can I get best.pt file. I cannot find it..
Bro you are the best . You are the damnnn best
Excellent tutorial.
Thanks man, really good example! Can you make video or give source that can be trained on local computer with gpu on custom dataset?
If you have installed PyTorch on your local computer and have a GPU, you can train model exact same way as i did in here. If you need any help contact me, i can help you on this project.
@@SoftwaresAI how can i contact with you
@@SoftwaresAI need help with this too
Thank you very much !!!
Thanks for your video, really helpful! I am doing multiple objects detection, and want to show the result pictures without any object name and object probability on the bounding box, how shall I change for this? Appreciate if you can share.
Try passing the command with "--hide-labels" and "--hide-conf"
thank you for this!
Bro, u saved me. Thx you so much!!!!
Thank you, it's ery helpful
Thanks, a lot.
Very helpful
Excellent tutorial,
Hi thank you for this video. I have a question , it just first time I will learn about this . after detection is that number showed with detection is it a feature of chicken? Is it its length?
Thank you
Thank you so much!
Traceback (most recent call last):
File "segment/train.py", line 658, in
main(opt)
File "segment/train.py", line 554, in main
train(opt.hyp, opt, device, callbacks)
File "segment/train.py", line 283, in train
for i, (imgs, targets, paths, _, masks) in pbar: # batch ------------------------------------------------------
File "/usr/local/lib/python3.8/dist-packages/tqdm/std.py", line 1195, in __iter__
for obj in iterable:
File "/content/yolov5/utils/dataloaders.py", line 172, in __iter__
yield next(self.iterator)
File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/dataloader.py", line 628, in __next__
data = self._next_data()
File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/dataloader.py", line 1333, in _next_data
return self._process_data(data)
File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/dataloader.py", line 1359, in _process_data
data.reraise()
File "/usr/local/lib/python3.8/dist-packages/torch/_utils.py", line 543, in reraise
raise exception
IndexError: Caught IndexError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/_utils/fetch.py", line 58, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/content/yolov5/utils/segment/dataloaders.py", line 115, in __getitem__
img, labels, segments = self.load_mosaic(index)
File "/content/yolov5/utils/segment/dataloaders.py", line 255, in load_mosaic
img4, labels4, segments4 = random_perspective(img4,
File "/content/yolov5/utils/segment/augmentations.py", line 102, in random_perspective
new_segments = np.array(new_segments)[i]
IndexError: boolean index did not match indexed array along dimension 0; dimension is 0 but corresponding boolean dimension is 15
got this too..
Hii.. Did you this resolve this error?? I'm getting the same..
Did you resolve??? Please respond
Thank you Very Much . You are a Life Saver
You're welcome!
Great work bro!
Thanks, Please support my channel www.buymeacoffee.com/biplob004
Thanks for the video. Is it possible to annotate semantically or with polygons? Thanks
great video i clear all my douts 😊😊