ZengyuanYu
ZengyuanYu
I trained my own data use Mask RCNN。Now, I want to calculate mask area through pixel. How to do that?
It's a really great study,but i want to generate pt and use Netron visualization,display as this: Please help answer this question,thx。 
Now I have some pictures, but how i create label(labelme?) ? And then how I train this datasets?
/usr/src/tensorrt/bin/trtexec --onnx= models/efficidet/efficientdet-lite0/efficientdet-lite0-bs1.onnx --explicitBatch --int8 --workspace=1024 --sparsity=enable
苏AZ3A25 1.0 苏AZ3A25 1.0 苏AJ3H16 1.0 苏AJ3H16 1.0 苏AC0378 1.0 苏AS0377 1.0 苏AY9L95 1.0 苏AX9L15 1.0 苏AZ1W57 1.0 苏AZ7X17 1.0 苏AR3595 1.0 苏AR0195 1.0 苏AI0P50 1.0 苏AI0P59 1.0 苏AE8J34 1.0...
code: def read_data(img_glob): for fname in sorted(glob.glob(img_glob)): # fname = fname.decode('utf-8') # fname = fname.encode('utf-8') im = cv2.imread(fname)[:, :, 0].astype(numpy.float32) / 255. code = fname.split("/")[1][9:16] p = fname.split("/")[1][17] == '1'...