def get_YOLOv2_Predictor():
# has been trained with coco
file_yolov2_cfg = getDataFile("yolov2/yolov2.cfg")
yolov2_training_ctx = TrainingContext(
n_classes = 80,
trainfile = "/home/pjreddie/data/coco/trainvalno5k.txt",
validfile = "coco_testdev",
namefile = getDataFile("yolov3/coco.names"), # all the other values don't make any difference when predicting
backup_dir ="/home/pjreddie/backup/",
setname = "coco"
)
return Predictor(training_ctx = yolov2_training_ctx, weight_file = get_yolov2_weights_file(), config_file = file_yolov2_cfg, thresh = 0.6)
def test1():
st="""Empty test
"""
pre=pre_mod+"test1 :"
print(pre,st)
ctx = TrainingContext(
n_classes = 80,
trainfile = "/home/pjreddie/data/coco/trainvalno5k.txt",
validfile = "coco_testdev",
namefile = "/home/sampsa/C/darknet/data/coco.names",
backup_dir ="/home/pjreddie/backup/",
setname = "coco"
)
predictor = Predictor(training_ctx = ctx, weight_file = "/home/sampsa/C/darknet/yolov3.weights", config_file = "/home/sampsa/C/darknet/cfg/yolov3.cfg")