Hi niloofarsabouri
I think the voc is used here for ease of use. since the dataset is pre-made. Also it helps show how to convert between formats since many datasets exist in VOC. According to yolov6 training notebook:

If you are using a custom dataset, you will have to prepare your dataset for training YOLOv6 Wiki. Once you have set up YAML and sorted labels and images into the right directories, you can continue with the next step.
Luckily, we are using VOC, for which YAML already exists. If you inspect the YAML. We'll be the following tutorial on how to train YOLOV6 on the VOC data set.

Thanks,
Jaka

      jakaskerl

      Hi,

      Thanks for your reply.

      Can you explain what these lines are talking about?

      wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar -O ./VOCdevkit/VOCtrainval_06-Nov-2007.tar

      I think by this line, we can download a data set and I don't understand this part" -O ./VOCdevkit/VOCtrainval_06-Nov-2007.tar"

      If I want to substitute my own data set what should I do?

      can you explain more.

      Thanks

          Hi niloofarsabouri

          wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar -O ./VOCdevkit/VOCtrainval_06-Nov-2007.tar

          Let's break it down:

          1. wget - This is a command-line utility to download files from the internet. It supports downloading via HTTP, HTTPS, and FTP.
          2. http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar - The URL of the file you want to download, in this case, the PASCAL VOC 2007 training/validation data.
          3. -O - An option for wget that allows you to specify the output filename and path.
          4. ./VOCdevkit/VOCtrainval_06-Nov-2007.tar - Where you want the downloaded file to be saved. The . indicates the current directory, so it will save in the VOCdevkit subdirectory with the provided filename.

          If you wish to substitute your data, just place the data some folder on your machine and point to it later in the tutorial when path for the dataset is used.

          Thanks,
          Jaka

              jakaskerl

              Hi,

              as it mentioned on site.

              we have to make 2 paths for test and trian.

              my dataset is already in yolo format so i ignore the cells which are discussing about converting VOC to YOLO.

              but I got this error:

              I don't understand what to do…

              can you explain and help me more?

                @jakaskerl

                Hi again,

                I just skipped and now faced with a new error I think:

                I think in last line which is relating to a class is not correct!

                my class has not been recognized and these two files in exp5 are not exist!

                jakaskerl

                sorry for replying too much…

                the main problem is:

                I don't know where the problem is!

                Thanks all for help

                    niloofarsabouri

                    If you've got it trained, path to weights should likely be runs/train/exp5/weights/best.pt. Notice the 5 in exp5 (not just exp). Which number it is should be based on the experiment that was successful. Assuming it was the last run, check what the exp with the highest number is in runs/train folder.

                        Matija

                        Hi..

                        and thanks alot!

                        I got the result folder..

                        i mean go to the Luxions page and convert best.pt to the file

                        now to clone to git I got this error. I googled it but it does not make sense.

                        can you help me?

                        Thanks

                            jakaskerl

                            Matija

                            Hi,

                            Thanks for your help

                            I faced with a new problem…

                            requests.exceptions.HTTPError: 400 Client Error: BAD REQUEST for url: https://blobconverter.luxonis.com/compile?version=2021.4&no_cache=False

                            why this is happening?

                            I renamed my file to 2021.4, but I still got the errors again.

                            I am still trying to solve the problem but get new error lines…

                            as you had mentioned in your repository:

                            python3 main_api.py -m <model_name> --config <config_json>

                            I put yolov7 in <model name> also I tried putting yolo but the same error…

                            and best.json for rest, and I got this error:

                            python3 main_api.py -m <model_name> --config <config_json>

                            can you explain more

                            I appreciate for your helps.

                                  niloofarsabouri

                                  When you specify -m yolo it tries to download it from our cloud. You should pass the path to your .blob path there. So, in .zip from tools.luxonis.com you will get the .json (which you are using correctly) and a .blob file. -m should be path to that blobfile.

                                      Matija

                                      Hi,

                                      sorry I am new in these commands .

                                      Would you mind explaining more … you are great.

                                      I want to write the command.

                                      If I don't mixed it up I have to specify my own path from this folder??

                                      I use this commad:

                                      python3 main.py --config best.json

                                      it gives me an error 400 bad request!!

                                          Matija

                                          sorry for my questions…

                                          it finally works by your help.

                                          how can I make it more accurate?

                                          I used 114 images to train it.

                                          and my oak can not detect good.

                                            114 images is barely the minimum. You should try to use more. The quality of annotations will also affect how well the model works.

                                            3 months later

                                            @Matija

                                            Hello and Thank you for your time.

                                            I was about to test my custom model by oak but in real the device (oak) could not detect the object.(false detection)

                                            I think all of you are super expert machine vision engineers , so I want if you mind helping me to solve my problem.

                                            the question is:

                                            I want to detect a blue window that drone should detect it and pass in central of window.

                                            I have searched and want your opinion that, window has 4 corners and these features are not enough to be detected… each object which has 4 corners is detected and labeled blue- window.

                                            in order to detect the window what should I do with Oak?

                                            for custom dataset how many pictures and do I need images with background?

                                            If you were in my place what would you do?

                                            Thanks in advance.

                                              Hi niloofarsabouri
                                              Do you absolutely need the NN to perform this task? Can you modify the windows in any way?

                                              We had a competition where the goal was to as quickly as possible, fly a drone through a series of hoops. But each hoop had an Aruco marker glued on the pole on which the hoop was mounted. By using a marker, you would know the distance from the hoop center to the drone.

                                              Would this be possible in your case?

                                              Thanks,
                                              Jaka

                                                  jakaskerl

                                                  Hi

                                                  Thank you for your response.

                                                  No, We are not allowed to use Aruco markers.

                                                  I am thinking about Is it possible for Oak to get a non-processing fram in RGB ?

                                                  just like a normal camera.

                                                      Hi niloofarsabouri
                                                      Not really sure what you mean by non-processing, but you can get frames straight from the device, without any manipulations done to the image.

                                                      Thanks,
                                                      Jaka