我是使用 Detectron2 的新手。我想从本地驱动器加载视频。然后,使用我训练有素的模型使用 Detectron2 的 VideoVisualizer 进行检测。
我试图找到一个关于这个的教程。但它不存在。请问我该怎么办?
谢谢
import detectron2
from detectron2.utils.logger import setup_logger
setup_logger()
# import some common libraries
import numpy as np
import tqdm
import cv2
# import some common detectron2 utilities
from detectron2 import model_zoo
from detectron2.engine import DefaultPredictor
from detectron2.config import get_cfg
from detectron2.utils.video_visualizer import VideoVisualizer
from detectron2.utils.visualizer import ColorMode, Visualizer
from detectron2.data import MetadataCatalog
import time
video = cv2.VideoCapture('gdrive/My Drive/video.mp4')
width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
cfg = get_cfg()
cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml"))
cfg.OUTPUT_DIR = 'gdrive/My Drive/mask_rcnn/'
cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, "model_final.pth")
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.7 # set threshold for this model
predictor = DefaultPredictor(cfg)
v = VideoVisualizer(MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), ColorMode.IMAGE)