Turns out that loading the PNG was not the issue. I am now testing with the Coral USB Accelerator, and I need to re-shape the array this way for it to fit my model file:
image = Image.open(args.input)
img = np.array(image)
img.shape = (224,224,1)
common.set_input(interpreter, img)
I can do this from the linux PC I’m working on. I do not remember if I had tried exactly that on the Coral Dev board.
I notice that processing these images require ~65ms, as opposed to the ~5ms requires to process the “bird” example images, despite the example parrot image being much larger. I guess if TFlite is optimized for 8bit input values (RGB) instead of 16 bit values.