I have a tflite modelthat runs in coral USB, but I it to run also in CPU (as an alternative to pass some tests when coral USB is not phisicaly available).
I found this very similar question but the answers given are not useful.
My code looks like this:
class CoralObjectDetector(object):
def __init__(self, model_path: str, label_path: str):
"""
CoralObjectDetector, this object allows to pre-process images and perform object detection.
:param model_path: path to the .tflite file with the model
:param label_path: path to the file with labels
"""
self.label_path = label_path
self.model_path = model_path
self.labels = dict() # type: Dict[int, str]
self.load_labels()
self.interpreter = tflite.Interpreter(model_path),
experimental_delegates=[tflite.load_delegate('libedgetpu.so.1')])
# more code and operations
Where model and labels are downloaded from here.
I would like to load an alternative version of the same model that let me execute without the coral USB accelerator (i.e. only in CPU). My goal is something as follows:
class CoralObjectDetector(object):
def __init__(self, model_path: str, label_path: str, run_in_coral: bool):
"""
CoralObjectDetector, this object allows to pre-process images and perform object detection.
:param model_path: path to the .tflite file with the model
:param label_path: path to the file with labels
:param run_in_coral: whether or not to run it on coral (use CPU otherwise)
"""
self.label_path = label_path
self.model_path = model_path
self.labels = dict() # type: Dict[int, str]
self.load_labels()
if run_in_coral:
self.interpreter = tflite.Interpreter(model_path),
experimental_delegates=[tflite.load_delegate('libedgetpu.so.1')])
else:
# I expect somethig like this
self.interpreter = tflite.CPUInterpreter(model_path)
# more code and operations
I'm not sure if I need just this or something else in the inference/prediction methods.
.