I've been debugging for days now and I hope you can help me. I'm having trouble running tensorflow outside of my main script, and I'm wondering if there is a workaround.

So to isolate the issue I wrote a couple of test scripts to see what the problem is. This scripts works fine.

main.py

from tflite_support.task import core
from tflite_support.task import processor
from tflite_support.task import vision
from multiprocessing import Process

def start_ml():
    model = "efficientdet_lite0.tflite"
    numThreads = 4

    dispW = int(1280 / 2)
    dispH = int(720 / 2)

    picam2 = Picamera2()
    picam2.preview_configuration.main.size=(dispW, dispH)
    picam2.preview_configuration.main.format='RGB888'
    picam2.preview_configuration.align()
    picam2.configure("preview")
    picam2.start()

    baseOptions = core.BaseOptions(file_name=model, use_coral=False, num_threads=numThreads)
    detectionOptions = processor.DetectionOptions(max_results=3, score_threshold=0.5)
    options = vision.ObjectDetectorOptions(base_options=baseOptions, detection_options=detectionOptions)
    detector = vision.ObjectDetector.create_from_options(options)

    while True:
        im = picam2.capture_array()
        im = cv2.flip(im, -1)

        imRGB = cv2.cvtColor(im, cv2.COLOR_BGR2RGB) # convert from BGR to RGB image
        imTensor = vision.TensorImage.create_from_array(imRGB) # create a tensor image
        myDetections = detector.detect(imTensor) # get the objects that are detected by tensorflow
        image = utils.visualize(im, myDetections) # create a decorated image with detected objects

        cv2.imshow('Camera', im)
        if cv2.waitKey(1)==ord('q'):
            break

    cv2.destroyAllWindows()

process = Process(target=start_ml)
process.start()

As soon as I have the tensorflow code outside of main.py, it gets stuck at or around the tensorflow method calls. There is no error or any indication that anything went wrong, it just hangs.

main.py

from detector import Detector

detector = Detector()
detector.start_camera_feed(detector)

detector.py

from tflite_support.task import core
from tflite_support.task import processor
from tflite_support.task import vision
from multiprocessing import Process


class Detector:
    def __init__(self):
        dispW = int(1280 / 2)
        dispH = int(720 / 2)

        self._picam2 = Picamera2()
        self._picam2.preview_configuration.main.size = (dispW, dispH)
        self._picam2.preview_configuration.main.format = 'RGB888'
        self._picam2.preview_configuration.align()
        self._picam2.configure("preview")
        self._picam2.start()

        model = "efficientdet_lite0.tflite"
        numThreads = 4

        baseOptions = core.BaseOptions(file_name=model, use_coral=False, num_threads=numThreads)
        detectionOptions = processor.DetectionOptions(max_results=3, score_threshold=0.5)
        options = vision.ObjectDetectorOptions(base_options=baseOptions, detection_options=detectionOptions)
        self._detector = vision.ObjectDetector.create_from_options(options)

    def start_camera_feed(self):
        process = Process(target=self._show_camera_feed)
        process.start()

    def _show_camera_feed(self):
        iterator = 0
        while True:
            im = self._picam2.capture_array()
            im = cv2.flip(im, -1)

            imRGB = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)  # convert from BGR to RGB image
            imTensor = vision.TensorImage.create_from_array(imRGB)  # create a tensor image
            myDetections = self._detector.detect(imTensor)  # get the objects that are detected by tensorflow
            image = utils.visualize(im, myDetections)  # create a decorated image with detected objects

            cv2.imshow('Camera', im)
            if cv2.waitKey(1) == ord('q'):
                break

            iterator += 1
            if iterator == 100:
                break

        cv2.destroyAllWindows()

This problem actually occured when I tried to implement some tensorflow object detection in a hobby project I'm working on. I really want to keep the structure I have in that project and not have any tensorflow code in my main script, that's why I'm not just moving it all to main.py. I'd also like to keep the subprocesses.

解决方案

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