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!
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.
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....
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
Great video! I'm new to this. So with "val" you basically do the same thing again, just to train the model better? Which means, you could also put "negative" images that the model should exclude? I ask because I want to recognize sprocket holes on a film strip that are completely visible only, and the "half" ones should be recognized as invalid.
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. .
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.
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...
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
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!!!
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
thanks for the explaination , i wanted to know that how can i count the objects detected in the image , I have trained my model with your tutorial now want to count the objects detected in the image how can i do it ?
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?
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
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?
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
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.
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.
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
When you trained the model with the custom dataset, will it still be able to detect the existing COCO objects like person, bus, car etc? Or after training will it ONLY detect chicken, f yes, then what to do so that it detects COCO objects + chicken ?
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.
How can you display the number of chiken in the video Thanks for the video I have a task which is pedestrian detection and congestion measurement I need to build a model that can detect pedestrian and also be able to say if the frame is congested For example let's say in a frame greater than 20 people means congested
Thnaks for a wonderful video... Im done training the model, but to use the file in my opencv project, i need it in .weight format..... where do I get the file??
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
Your algorithm is working very fine, it gives outstanding results. But I also want to count the detected objects('bearings'). How can I do the same please reply as soon as possible.
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?
Hey, great explanation. I have a doubt that how can we use the same detection file to run on multiple sources at the same time like you used 1 video source file can we detect objects in different videos together by using just one detection file instead of separate detection files for each video
we didn't used labels while training the data, how it detected without taking our labels. If we want to use this for any other custom data how is it possible
You are welcome, you can find trained weight at location: yolov5/runs/train/exp/weights/last.pt you will find exact path of your saved model, printed at last line when training completes.
@@SoftwaresAI sorry for the next stupid question. The model was downloaded with the extension .pl Earlier I opened models with h5 extension like this: detector = ObjectDetection () detector.setModelTypeAsTinyYOLOv3 () detector.setModelPath ('yolo-tiny.h5') detector.loadModel () How to open last.pt file in python?
No problem, Here is solution: Watch my this video th-cam.com/video/Qs_kMvU1IIo/w-d-xo.html here simply replace yolov5s.pt with your runs/train/exp/weights/last.pt model. like this: --weights runs/train/exp/weights/last.pt instead of --weights yolov5s.pt
The prediction which you were telling at 16:01 , it doesn't pridict anything.. can you give me the solution. bonding box was not created in prediction.
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
@@umar_muhammad_yaree I think you should count number of objects in each frame
Yes
Please do you know how i can do that
@@umar_muhammad_yaree I am interested in this too
For the first time I could execute something in the very attempt! Thanks to you Sir!!! This was seriously awesome.
The official colab notebook has changed since this video was made but still very useful! Thank you for your work!
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.
Thank you for such a amazing video about YOLO, had almost everything needed in it ❤
Thank you soooo much. Finally after two days, I was able to do my class project ❤
Wow, this explaination is one of the best I can find on TH-cam! Thanks for your effort!
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🙃
Thank you for the great tutorial and extra points for the chickens. I LOVE chickens!
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
Wow, the explanation is so clear and straightforward! Thank you sir!!!
BEST TUTORIAL I EVER FOLLOWED! THANK YOUUUU!!!
Great video! I'm new to this. So with "val" you basically do the same thing again, just to train the model better? Which means, you could also put "negative" images that the model should exclude? I ask because I want to recognize sprocket holes on a film strip that are completely visible only, and the "half" ones should be recognized as invalid.
Thankyou for this video! How to turn on Webcam and do object detection in real-time...can please say what changes should be done?
1thanks a lot!! was looking for a simple way to detect object and found this channel. Subscribed
Gracias por tomarte el tiempo de hacer este vídeo, no sabes lo útil que me fue, te juro, no tienes ni idea. Te amo.
I have no words to express my gratitude towards you. Thanks a ton.
Wow best explanation really am so happy by watching this video and many students get some thing especial.
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 :).
Thank you very much, been looking for this explanation. Many thanks
Thank you! This is just what I was looking for!
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. .
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.
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...
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
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!!!
hello sir please do the same video for yolov8 also using webcam I mean for real time detection also
you are so good at teaching!
thank you for the video!
I cannot Thank You enough for this.
Hello, thank you so much for this beautiful tutorial. Please, could you also do a tutorial on how to deploy this model live?
Thankss. This video was really helpful in my project 😃.
It's brilliant.!! Thanks for the amazing video!! Really helpful!!
Very well done. Easy to follow.. you’ve got a new subscriber
This TUTORIAL IS 100% WORKING GOOD TUTORIAL
thank you, finally, I am able to identify chickens.
excellent man,thank you for this video.look forward more such videos.
Wow
Thank you very much for this tutorial it helps alot
It's very clear and straightforward 🤗🤗
This is wonderful easy to follow tutorial. How can we tell the validation loss please
Thank you so much for this useful tutorial!
Thank you so much. Very clear explanation!
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
wahoo I'm stupefy, very good explanation. Thanks to you, I more learned about this topic
Thank you very much! Nice video!
come on man... you forgot a chicken in tha cage🍌
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
thanks for the explaination , i wanted to know that how can i count the objects detected in the image ,
I have trained my model with your tutorial now want to count the objects detected in the image how can i do it ?
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?
Thank you. It's settled thanks to you.
Can you please make a tutorial about integrating DeepSORT with YOLOv5 for multiple-object tracking? Thx!!!
Thank you bro for this tutorial ,you're Amazing
Thank you for this amazing tutorial....................
What a great Explanation. very thanks it help me a lot in sport analysis matches.!)
Thank you so much........for sharing your knowledge.............
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
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?
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
Thank you so much bro. God bless you.
I love you ♥
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.
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"
good tutorial, keep going on man!
Really a lifesaver 👍
If you like to support my channel, here is link www.buymeacoffee.com/biplob004
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..
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
Thanks man, very helpful video.
When you trained the model with the custom dataset, will it still be able to detect the existing COCO objects like person, bus, car etc? Or after training will it ONLY detect chicken, f yes, then what to do so that it detects COCO objects + chicken ?
From VietNam. Thanks
Great video, thanks man!
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
How can you display the number of chiken in the video
Thanks for the video
I have a task which is pedestrian detection and congestion measurement
I need to build a model that can detect pedestrian and also be able to say if the frame is congested
For example let's say in a frame greater than 20 people means congested
Thnaks for a wonderful video...
Im done training the model, but to use the file in my opencv project, i need it in .weight format.....
where do I get the file??
Thank you very much. Very useful. Can I build a front end app to use it for users?
It was great👍 thank you , keep it up
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.
Bro you are the best . You are the damnnn best
Great video ! How can I train my dataset with YOLO v3-tiny by using this guide ?
Same way he did it here, but its better for you to just train your model on your IDE.
Excellent tutorial.
Why do you not need a "test" folder? Aren't we supposed to have train, val and test sets? I'm confused.
You are amazing thank u so much ❤❤❤❤❤❤❤
Your algorithm is working very fine, it gives outstanding results. But I also want to count the detected objects('bearings'). How can I do the same please reply as soon as possible.
you can get the results from detection and write them to a List. Then the len(yourlist) is the number of things detected
@@cosmilitebar6772 can you explain a bit more?
how to unzip train data, sir? i can't do it in step .
thank you! I have a question, why in the beginning you have train and val, but later you get train and test?
Any tips on increasing the confidence level of detected objects? Thanks
Thank you Sir... It is really to the point and informative... Really too helpful
Excellent Work Brother..!!
Thanks ✌️
Please support my channel here www.buymeacoffee.com/biplob004
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?
For the same, how to use for live detection. That is using our own camera instead of a video!?
Thanks for the video. Is it possible to annotate semantically or with polygons? Thanks
Hey, great explanation. I have a doubt that how can we use the same detection file to run on multiple sources at the same time like you used 1 video source file can we detect objects in different videos together by using just one detection file instead of separate detection files for each video
one of the best videos i used for my project, really thanks
Glad it helped!
Great Video!! Is it possible to do this for Thermal Images as well. I would like to detect object in thermal images. Please advise.
Can you do a new video but with Yolov8? Ultralytics just released Yolov8
You have Train and validation but where is the test set ?
Very useful, tks for sharing!
we didn't used labels while training the data, how it detected without taking our labels. If we want to use this for any other custom data how is it possible
thank you so much. Very good tutorials.
Thank you very much for the helpful video.
How to download the final file with the trained model to your computer so that you can use it locally?
You are welcome, you can find trained weight at location:
yolov5/runs/train/exp/weights/last.pt
you will find exact path of your saved model, printed at last line when training completes.
@@SoftwaresAI sorry for the next stupid question. The model was downloaded with the extension .pl
Earlier I opened models with h5 extension like this:
detector = ObjectDetection ()
detector.setModelTypeAsTinyYOLOv3 ()
detector.setModelPath ('yolo-tiny.h5')
detector.loadModel ()
How to open last.pt file in python?
No problem,
Here is solution:
Watch my this video th-cam.com/video/Qs_kMvU1IIo/w-d-xo.html here simply replace yolov5s.pt with your runs/train/exp/weights/last.pt model.
like this: --weights runs/train/exp/weights/last.pt instead of --weights yolov5s.pt
@@ДмитрийБолховский why you need to save model in .h5 format ?
its automatically saved in .pt format, simply use that on your local computer.
@@SoftwaresAI is it possible to save the trained model in h5 format
The prediction which you were telling at 16:01 , it doesn't pridict anything.. can you give me the solution. bonding box was not created in prediction.