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['random_FCN','learned_pixel_readout','trained_FCN','condition_nearest_logits','condition_scale_045','condition_RGB_blur5','readout_RGB_blur5']:\n    r=R[key];print(key,{k:round(v,5) for k,v in r.items() if 'IoU' in k or k=='pixel_accuracy'})\nprint(R['provenance'])\nfrom IPython.display import Image,display\nfor filename in ['sampling-warmup.png','heldout-segmentation.png','failure-segmentation.png','small-object-segmentation.png','blur-segmentation.png']:\n    display(Image(filename='lab11-results-rerun/'+filename))\n```","sha256":"511f953428fc36f69fb5ac6a0e012f4337791cd5195b05446ab91ccb7a45db98","chapter":{"id":"course","title":"运行：模型输出必须和输入、真值一起看 · 实现代码"},"unit":{"id":"notebook-blocks/54cfa2249229431fa7e651cfd5d0244a","title":"运行：模型输出必须和输入、真值一起看 · 实现代码"},"page":{"id":"reading-opening","title":"运行：模型输出必须和输入、真值一起看 · 实现代码","number":1},"sectionTitle":"运行：模型输出必须和输入、真值一起看 · 实现代码","currentQuestion":"运行：模型输出必须和输入、真值一起看 · 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