can you please send the link of the video that you used to demonstrate this project please !! thank you

Nice Vietnamese bro! I am here Vn too admire you

I think it's great, but it doesn't let me see that secondary menu that appears and when I upload a photo and ask about it, it gives me an error and closes on me.

did you release a v2, looks so cool

output xuất ra file json chứ không phải ảnh phải ko ạ

can we use model for tif format?

How can we save the annotation in YOLO format? Great software!

Dạ em chào anh, em đang muốn học về mảng này, không biết anh có khoá học hay video nào về xe tự hành này ko ạ. Em cảm ơn anh rất nhiều.

Great work! May i know display used?

mình xin lại link code để xem tham khảo với. link source code bị die rồi

Phần mềm rất hữu ích ạ. Cám ơn tác giả. Nhưng mình gặp một số khó khăn khi sử dụng câu lệnh 'pip install anylabeling 'để cài đặt ERROR: Cannot install anylabeling==0.0.9, anylabeling==0.1.0, anylabeling==0.1.1, anylabeling==0.1.2, anylabeling==0.1.4, anylabeling==0.1.5, anylabeling==0.1.6, anylabeling==0.2.10, anylabeling==0.2.11, anylabeling==0.2.12, anylabeling==0.2.13, anylabeling==0.2.14, anylabeling==0.2.16, anylabeling==0.2.18, anylabeling==0.2.19, anylabeling==0.2.2, anylabeling==0.2.20, anylabeling==0.2.21, anylabeling==0.2.22, anylabeling==0.2.23, anylabeling==0.2.24, anylabeling==0.2.3, anylabeling==0.2.4, anylabeling==0.2.6, anylabeling==0.2.7, anylabeling==0.2.8, anylabeling==0.2.9 and anylabeling==0.3.3 because these package versions have conflicting dependencies. The conflict is caused by: anylabeling 0.3.3 depends on onnxruntime==1.14.1 anylabeling 0.2.24 depends on onnxruntime==1.14.1 anylabeling 0.2.23 depends on onnxruntime==1.14.1 anylabeling 0.2.22 depends on onnxruntime==1.14.1 anylabeling 0.2.21 depends on onnxruntime==1.14.1 anylabeling 0.2.20 depends on onnxruntime==1.14.1 anylabeling 0.2.19 depends on onnxruntime==1.14.1 anylabeling 0.2.18 depends on onnxruntime-gpu==1.14.1 anylabeling 0.2.16 depends on onnxruntime-gpu==1.14.1; platform_system != "Darwin" anylabeling 0.2.14 depends on onnxruntime-gpu==1.14.1; platform_system != "Darwin" anylabeling 0.2.13 depends on onnxruntime==1.14.1 anylabeling 0.2.12 depends on onnxruntime==1.14.1 anylabeling 0.2.11 depends on onnxruntime==1.14.1 anylabeling 0.2.10 depends on onnxruntime==1.14.1 anylabeling 0.2.9 depends on onnxruntime==1.14.1 anylabeling 0.2.8 depends on onnxruntime==1.14.1 anylabeling 0.2.7 depends on onnxruntime==1.14.1 anylabeling 0.2.6 depends on onnxruntime==1.14.1 anylabeling 0.2.4 depends on onnxruntime==1.14.1 anylabeling 0.2.3 depends on onnxruntime==1.14.1 anylabeling 0.2.2 depends on onnxruntime==1.14.1 anylabeling 0.1.6 depends on onnxruntime==1.14.1 anylabeling 0.1.5 depends on onnxruntime==1.14.1 anylabeling 0.1.4 depends on onnxruntime==1.14.1 anylabeling 0.1.2 depends on onnxruntime==1.14.1 anylabeling 0.1.1 depends on onnxruntime==1.14.1 anylabeling 0.1.0 depends on onnxruntime==1.14.1 anylabeling 0.0.9 depends on onnxruntime==1.14.1 To fix this you could try to: 1. loosen the range of package versions you've specified 2. remove package versions to allow pip attempt to solve the dependency conflict ERROR: ResolutionImpossible: for help visit pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts

Góp ý, thêm cái rà sắt mà mấy ông rà sắt ak, bỏ bên dưới có thể bân loại kim loại,

excellent！

wow

Hi, I use this tool to annotate image,but I can't save my annotation result

Hi anh, cảm ơn anh đã open source một project rất thú vị. Theo em hiểu là việc label segment đang được thực hiện bởi 3 pre-train và phần mềm cho phép người dùng điều chỉnh lại cho chuẩn hơn, vậy đối với những object chưa được huấn luyện trong 3 pre-train đó thì sao ạ, liệu mình có thể cung cấp thêm 1 option cho phép người dùng load pre-train của họ vào rồi họ sẽ điều chỉnh label xong đó re-train lại để cải thiện chất lượng model ban đầu không anh nhỉ?

Awesome work! Thanks for sharing this and making it open source. Feature request: can you add an option to automatically generate bounding boxes (for training object detection models) from the segmented data?

gonna try it

Anh có thể dạy em làm được không ạ

source code link bị die rồi ạ, sẵn cho em hỏi cái này là dùng AI ạ, mà bên github có sẵn file train luôn à

anh có thể cho e xin code đc ko ạ e muốn phát triển cái máy này ạ

Really cool! FYI if anyone is looking to train (or fine-tune) their own pose estimation models (or rep counting models), my team and I created a free open-source dataset for this. It has 1k exercise videos with labels like 2D/3D keypoints, rep counts, segmentation, joint angles, etc. Pushups is actually one of the exercises! Check out the free dataset: toinfinity.ai/infiniterep Hope it’s useful to folks + happy building!

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🌹❤🌹❤🌹❤🌹❤🌹❤

🌹🌹🌹🌹🌹❤❤❤❤❤

🌹❤🌹❤🌹❤🌹❤🌹❤

IS in c++ ?

Bác cho e xin code này luôn đc ko ạ

This is Awesome! Thanks thanks for sharing. I've often wondered how to do this for industrial control cabinets. AR would be super useful in an industrial PLC setting.

cool

Hello? Thanks for the good video. What kind of camera did you use? Thank you.

Nice work! What is the procedure/code to connect a .wav-file to an object detection? E.g something is detected --> play "collision_warning.wav" Thanks!

Em chào anh ạ. Em có gặp vấn đề khi chạy thử code là yêu cầu CUDA capability là 3.5 nhưng máy em chỉ 3.0 (Quadro K2100M). Cho em hỏi có cách nào để chạy mà không cần downgrade xuống TF1 không ạ ?

Minh xin code dc ko a

Great video

can you post a blog of details

Watch out for the train :D very cool Video, do you think its possible to learn to setup the Code for this as a beginner with alot of motivation?

Não to 😂

cho mình hỏi bạn ở Sài Gòn hay Hà Nội vậy?

Please there is any github for the code ?

hay đó ông