fastai split_by idxs

fastai_split_by_idx.py

#その３
#fastai/fastai/vision/data.py
'''
data = ImageDataBunch.from_csv(path, ds_tfms=tfms, size=128)
print(data)
'''

'''
@classmethod
    def from_csv(cls, path:PathOrStr, folder:PathOrStr=None, label_delim:str=None, csv_labels:PathOrStr='labels.csv',
                 valid_pct:float=0.2, fn_col:int=0, label_col:int=1, suffix:str='', delimiter:str=None,
                 header:Optional[Union[int,str]]='infer', **kwargs:Any)->'ImageDataBunch':
        "Create from a csv file in `path/csv_labels`."
        path = Path(path)
        df = pd.read_csv(path/csv_labels, header=header, delimiter=delimiter)
        return cls.from_df(path, df, folder=folder, label_delim=label_delim, valid_pct=valid_pct,
                fn_col=fn_col, label_col=label_col, suffix=suffix, **kwargs)
'''

'''
path2 = Path(path)
df = pd.read_csv(path2/csv_labels, header=header, delimiter=delimiter)
data2 = ImageDataBunch.from_df(
    path2, df, folder=folder,
    label_delim=label_delim,
    valid_pct=valid_pct,
    fn_col=fn_col,
    label_col=label_col,
    suffix=suffix)
print(data2)
'''

'''
    @classmethod
    def from_df(cls, path:PathOrStr, df:pd.DataFrame, folder:PathOrStr=None, label_delim:str=None, valid_pct:float=0.2,
                fn_col:IntsOrStrs=0, label_col:IntsOrStrs=1, suffix:str='', **kwargs:Any)->'ImageDataBunch':
        "Create from a `DataFrame` `df`."
'''

folder      = None
label_delim = None
csv_labels  = 'labels.csv'
valid_pct   = 0.2
fn_col      = 0
label_col   = 1
suffix      = '' 
delimiter   = None
header      ='infer'

path2 = Path(path)
df = pd.read_csv(path2/csv_labels, header=header, delimiter=delimiter)

'''
src = (ImageList.from_df(df, path=path, folder=folder, suffix=suffix, cols=fn_col)
    .split_by_rand_pct(valid_pct)
    .label_from_df(label_delim=label_delim, cols=label_col))
'''


src1 = ImageList.from_df(df, path=path, folder=folder, suffix=suffix, cols=fn_col)
print(src1)

train_idx = list(range(100,1000))
valid_idx = list(range(2000,))
src2 = src1.split_by_idxs(train_idx, valid_idx)


#src2 = src1.split_by_rand_pct(valid_pct)
#src3 = src2.label_from_df(label_delim=label_delim, cols=label_col)
#ImageDataBunch.create_from_ll(src3)