@Frank I tried with the latest released SDK-6.4.4.3 and I got an output for my Yolov3 model like this.
This is diffreent to what I had got before. Can you please tell me what does the below statement mean?
Does the below statement mean that the object belongs to the class type 0(Since I have only 1 class)?
Unlike the demo, why is it not printing the bounding box co-ordinates?
I expected the output to be detect_num = 4, as I have 5 holes in the image.
result type is 0, as I have just one class.
Do you have any reason, why am I not able to detect objects in the image? On PC, with the same weight and config file, I am able to detect the objects in the image! Please help me in this regard!
Whatâs the resolution of your test image?
@numbqq Resolution = 800*600
I just tried with 416*416. But I am getting error âSegmentation Faultâ!
But with resolution 800*600, I am not getting error, but the output is wrong as it says â0â.
Our demo is for 1080P image input, I think you need to modify the code for other resolutions.
@numbqq Thank you for your input.
Please correct me if I am wrong.
I have trained the yolov3 model with 800*600 image. But I guess, however, the model takes input as 416x416 itself. So there is no problem with the training of the model.
Since there are many files, can you please tell me which file do I have to modify?
As an alternative, if I reshape the test image to a resolution of 1080P (1980x1080), will it work?
Thank you for your inputs!
Maybe you can try to specify the width and height:
$ ./detect_demo_x11 -p 1080p.bmp -m 2 -w 800 -h 600
By default, it should work, the test image 1080p.bmp is 1080P.
@numbqq I tried to reshape the image to a resolution of 1080P (1980x1080). Yet, I am getting the same output as shown below. 
OK, could you please provide your orignal test image (800x600) to us to check ?
@Frank Can you please help me with this? I have resized the image to 1080P, yet I am not able to detect the objects on my image.
@Akkisony I also donât have any problem, the code error can help you check it, but there is no error message here, I donât know
@Frank How would you suggest me to overcome this problem. Itâs very important that I need to get this running! 
As per @numbqq suggestion, I resized the image size to even 1080P resolution, yet I am getting the same output.
@Akkisony I think this is related to darknet. If you want to detect a single object, it is not recommended that you use the yolo model. If you want to test whether this problem is caused, it is recommended that you train a 5-category yolo model to see if this is normal jobs
@Frank I tested the model on PC, everything works fine. After that, I decided to move to use the NPU on VIM3.
What do you mean by 5 category yolo model?
Do you have any other reccomendation for single object detection model, which works fine with NPU?
@Akkisony Yes , you can run it with PC.But adter convert , everything is different.
Not necessarily 5, you can also try 3
I havenât tried it, but I believe there is a model for this kind of detection
Do you mean 3 classes?
Can you tell me where is the file, where I can save the image and visualize it? I would like to visualize the detected object. Since there are many files involved, It would be great if you could tell me which file needs to be modified, so that I can visualize the detected object on screen (I have not connected the vim3 board to the monitor).
@Frank validation_tf.txt can you please tell me how many images are supposed to be placed in this folder? I had placed only one image. Should I try placing more images?
Also can you please tell me what does this file validation_tf.txt do?
One imge is enough. The number of pictures verified here will slightly affect your accuracy, but will not cause unrecognized situations
