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developer0hye / Yolo_Label

GUI for marking bounded boxes of objects in images for training neural network YOLO
MIT License
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The bounding box values are wrong #40

Closed ajaysurya1221 closed 3 years ago

ajaysurya1221 commented 3 years ago

Hi, I completed my annotation and had a look at the .txt files. All the values of my bounding boxes start with 0.

For eg : 0 0.485048 0.334155 0.253589 0.059186 1 0.449761 0.529593 0.180622 0.060419 2 0.437799 0.739211 0.153110 0.053021 3 0.550239 0.215783 0.250000 0.054254 This is for a single image with 4 classes.

I used PIL and OpenCV to crop my image using these values considering they are [xmin ymin xmax ymax] and I got the results wrong. When I reopen Yolo_Label, the boxes are perfectly there. Is there anything I need to do? any solution?

The code I used to crop the boxes :

from PIL import Image import matplotlib.pyplot as plt bbox=(int(0.485048), int(0.334155), int(0.253589), int(0.059186)) #for one bounding box of an image im=Image.open('sample.jpg') im=im.crop(bbox) plt.subplot(3,3,i+1) plt.axis("off") plt.imshow(im)

developer0hye commented 3 years ago

Refer to https://github.com/developer0hye/Yolo_Label/issues/39#issuecomment-731696641

ajaysurya1221 commented 3 years ago

Thank you so much