main.py

from development.Detector import *

# Enable GPU dynamic memory allocation
gpus = tf.config.experimental.list_physical_devices('GPU')
for gpu in gpus:
    tf.config.experimental.set_memory_growth(gpu, True)

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'    # Suppress TensorFlow logging (1)

tf.get_logger().setLevel('ERROR')           # Suppress TensorFlow logging (2)

#Even faster
# modelURL = "http://download.tensorflow.org/models/object_detection/tf2/20200711/ssd_mobilenet_v2_fpnlite_640x640_coco17_tpu-8.tar.gz"

#Faster but less accurate model
# modelURL = "http://download.tensorflow.org/models/object_detection/tf2/20200711/ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8.tar.gz" took 17.60349702835083

#took 11.92548394203186
modelURL = "http://download.tensorflow.org/models/object_detection/tf2/20200711/efficientdet_d4_coco17_tpu-32.tar.gz" 

#Slower but more accurate model
# modelURL = "http://download.tensorflow.org/models/object_detection/tf2/20200711/faster_rcnn_inception_resnet_v2_1024x1024_coco17_tpu-8.tar.gz"

classFile = "development\models\exported-models\pretrainedModels\coco.names"
imagePath = "test\\strangeJake.jpg"

detector = Detector()

detector.readClasses(classFile)

detector.downLoadModel(modelURL)

detector.loadModel()


image = detector.predictImage(imagePath, threshold = 0.5)