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我保存了我在 colab 的输出文件中训练的名为 final_model 的模型，但它给出了一个元组索引超出范围错误。我该如何解决这个错误。另外，我想从谷歌驱动器导入输出文件。如何编辑图片中的代码。

#visualize training data
my_dataset_train_metadata = MetadataCatalog.get("my_dataset_train")
dataset_dicts = DatasetCatalog.get("my_dataset_train")

import random
from detectron2.utils.visualizer import Visualizer

for d in random.sample(dataset_dicts, 3):
    img = cv2.imread(d["file_name"])
    visualizer = Visualizer(img[:, :, ::-1], metadata=my_dataset_train_metadata, scale=0.5)
    vis = visualizer.draw_dataset_dict(d)
    cv2_imshow(vis.get_image()[:, :, ::-1])
    from detectron2.data import DatasetCatalog, MetadataCatalog, build_detection_test_loader
    from detectron2.evaluation import COCOEvaluator, inference_on_dataset

#train

from detectron2.config import get_cfg
import os

cfg = get_cfg()
cfg.merge_from_file(model_zoo.get_config_file("COCO-Detection/faster_rcnn_X_101_32x8d_FPN_3x.yaml"))
cfg.DATASETS.TRAIN = ("my_dataset_train",)
cfg.DATASETS.TEST = ("my_dataset_val",)

cfg.DATALOADER.NUM_WORKERS = 2
cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-Detection/faster_rcnn_X_101_32x8d_FPN_3x.yaml") 
cfg.SOLVER.IMS_PER_BATCH = 2
cfg.SOLVER.BASE_LR = 0.001


cfg.SOLVER.WARMUP_ITERS = 3
cfg.SOLVER.STEPS = []
cfg.SOLVER.GAMMA = 0.05




cfg.MODEL.ROI_HEADS.BATCH_SIZE_PER_IMAGE = 128
cfg.MODEL.ROI_HEADS.NUM_CLASSES = 33 

cfg.TEST.EVAL_PERIOD = 500


os.makedirs(cfg.OUTPUT_DIR, exist_ok=True)
trainer = CocoTrainer(cfg)
trainer.resume_or_load(resume=False)
trainer.train()

cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, "model_final.pth")
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.3

pred = DefaultPredictor(cfg) #predictor
eva = COCOEvaluator("test_dataset", cfg, False, output_dir = "./output/") # evaluator
val_loader = build_detection_test_loader(cfg, "test_dataset")
inference_on_dataset(trainer.model, val_loader, Eva)

错误信息

4

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