同时,我们可以看到以下的两种不同技术配置的代码块示例: # 快速AI技术配置fromfastai.vision.allimport*path=untar_data(URLs.PETS)/'images'dls=ImageDataLoaders.from_name_re(path,get_image_files(path),valid_pct=0.2)# PyTorch技术配置importtorchimporttorchvision.datasetsasdatasetsimporttorchvision.transformsast...
Define a loader object: camvid = DataBlock(blocks = c(ImageBlock(), MaskBlock(codes)), get_items = get_image_files, splitter = FileSplitter('camvid/valid.txt'), get_y = function(x) {paste('camvid/labels/',x$stem,'_P',x$suffix,sep = '')}, batch_tfms = list(Normalize_from_st...
I have the same issue when using the foreground_acc metric on a segmentation data loader. dataloaders = SegmentationDataLoaders.from_label_func( SEGMENTATION_IMAGE_DIR, fnames = train_val_images, label_func = get_lung_mask, valid_pct=train_val_split, seed=42, codes=codes, batch_tfms=batch...
DataBunch.show_batch and Learner.show_results handle rows=1 (thanks to xnutsive) LanguageModelPreLoader is way faster (thanks to kasparlund) 1.0.41 (2019-01-22) Breaking change: sep (in ImageDataBunch factory methods) is now called label_delim New: Changed: Clearer representation of Flatten...
ImageItemList becomes ImageList for consistency with TextList and TabularList load_learner will fail for exported (pickled) models with error "AttributeError: Can't get attribute 'ImageItemList' on module 'fastai.vision.data'". You will need to re-export with version 1.0.46 or use 1.0.44 ...
PILBase.create starting from /root/.fastai/data/mnist_tiny/train/7/8791.png applying PILBase.create gives PILImage mode=RGB size=28x28 Pipeline: parent_label -> Categorize -- {'vocab': None, 'sort': True, 'add_na': False} starting from /root/.fastai/data/mnist_tiny/train/7/8791...
PILBase.create starting from /root/.fastai/data/mnist_tiny/train/7/8791.png applying PILBase.create gives PILImage mode=RGB size=28x28 Pipeline: parent_label -> Categorize -- {'vocab': None, 'sort': True, 'add_na': False} starting from /root/.fastai/data/mnist_tiny/train/7/8791...