jakaskerl Hi SwapnilBhole Usually, tiles of the same kind will have the same texture, since factories create them in large batches to save money. Consider using something like pattern matching to achieve classification. Thoughts? Jaka
SwapnilBhole Thanks. Can you send any link? Also, I have to understand image processing from very basic, so is there source to learn ?
jakaskerl Hi SwapnilBhole Try something like this. For image processing tutorials I'd suggest youtube; you have a bunch of high quality tutorials there. Hope this helps, Jaka
SwapnilBhole Hi, I tried Template matching. But, tiles are very much similar to each other. Only little shade difference as shown in above images. Can you suggest any other algorithm?
jakaskerl Hi SwapnilBhole The idea is to template match using edge/canny frames. This way the color has no effect on the end result. SwapnilBhole But, tiles are very much similar to each other. Only little shade difference as shown in above images. Perhaps I understood you wrong. You are saying that tiles have the same pattern, but vary slightly in the shade of the whole tile? In that case, you need to make sure the lightning conditions are the same in all cases and you could classify based on color/grayscale histograms of the image. Thoughts? Jaka
SwapnilBhole We have keep lightening condition exactly same for all dataset. But, not able to detect difference. If you share mail id, I will share dataset. so, you can see images very clearly.
jakaskerl Hi SwapnilBhole Best to create a google drive and set to manually give access. Thanks, Jaka
SwapnilBhole Hi jakaskerl ,Here is dataset https://drive.google.com/drive/folders/1X17cYgmraRZ23CGBQJLociY9Uq141vYi?usp=sharing
jakaskerl Hi SwapnilBhole The tiles seem the same to me, but there are very very slight differences in color intensity and contrast. Since they all have the same pattern, template matching won't work. The only thing I can think of is to look at color histograms and detect from subtle changes in color spread. But keep in mind the conditions should be the exact same and even then It will be difficult to tell (also considering the dynamic range of OAK cameras is not the best). Thanks, Jaka
SwapnilBhole Hi jakaskerl , any deep learning model using CNN will help in this. If yes, please suggest best model, so, I can try & let u know results.
jakaskerl Hi SwapnilBhole I'd start simple with something like resnet18 or resnet50, though I'm unsure of the end accuracy you will achieve as the tiles are very difficult to tell apart by looking at an image. Perhaps the model is less colorblind than I am 🙂 Thanks, Jaka
SwapnilBhole Hi jakaskerl , If Resnet50 does not work then which things or which deep learning model should I try???
SwapnilBhole jakaskerl I have OAK D pro POE kit. I have object at 4 cm apart from camera. How can I take clear photo from OAK kit? Is there any minimum working distance ? Please share necessary doument. What is minimum working distance OAK-1 or OAK-1 lite?
jakaskerl SwapnilBhole I have OAK D pro POE kit. I have object at 4 cm apart from camera. How can I take clear photo from OAK kit? Is there any minimum working distance ? Please share necessary doument. If by clear photo you mean a focused RGB image - AF variant of IMX378 starts at 8cm (described in product page on shop.luxonis.com). If you mean minimum depth perception, I suggest looking here. SwapnilBhole What is minimum working distance OAK-1 or OAK-1 lite? 8 cm for AF 50cm for FF https://docs.luxonis.com/projects/hardware/en/latest/pages/NG9096/#camera-module-specifications Thanks, Jaka
