Hi @GalibaSashi,
please check /opt/nvidia/deepstream/deepstream-5.0/sources/objectDetector_Yolo , there is YoloV2, YoloV3 and its INT8 calibration file, but no YoloV2 int8 calibration file.
HI @GalibaSashi,
You should build it by yourself.
To get good inference accuracy, user need to build the INT8 calibration with typical inference pictures of their inference targets, that means, even there is INT8 calibration file in DeepStream, it may not work for you.
Hi @mchi
can you give out the steps on how to build calibration table for the yolov2 or yolov3. If one example is given I can replicate the same for all?
Hi @mchi
I had already checked the same and only for classification models the samples are there and the sample datasets given to create the calibration table are also in classifiction type labels
Can you give out the specific steps to follow.
2)Can you tell me if the calibratio table is absolutely necessary and what will be the effects if I dont use it and ryn thee deepstream-app in INT8 mode
Yes I have checked the same ,there are two types sampleINT8 and sampleINT8API right . sampleINT8API specifically says it supports resnet 50 type classification models.While in sampleINT8 the dataset given is in ubyte or binary file and the type of dataset is classification. No detection type examples are there.
Hi @mchi
The dataset given for calibration is in binary form which is used for classification and the labels are classification type and not coordinates. I want to use detection dataset for calibration
No actually the dataset given in sample is train-images-idx3-ubyte which is a binary form wherethe labels are of classification. The same can not be used for calibration of detector models right?
I have the dataset in jpg as well as png and its supporting label files… and in what format should I supply the same?? should I make it into binary or can I give it diectly. How should I approach the same.