For calibration, it’s not advised to use many images. From past experiece 64 images is a good size of dataset for calibration. The reason is, that during the calibration profcess the qunatizer collects max/min/zero-point data of each layer. Using large calibration set pushes the max and the min farther away, thus makeing more outlier nodes. This in turn force a large dynamic range that increases the quantization noise.
but i geting waring if i use the below 1024 images not in the accepted size @Nadav
[warning] Reducing optimization level to 1 (the accuracy won’t be optimized and compression won’t be used) because there’s less data than the recommended amount (1024) i geting this waring
As said, 1024 is recommended, it will enable more optimization options.