Vision utils

Vision utils

Some utils function to quickly download a bunch of images, check them and pre-resize them

/usr/local/lib/python3.8/dist-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx (Triggered internally at  /pytorch/c10/cuda/CUDAFunctions.cpp:100.)
  return torch._C._cuda_getDeviceCount() > 0

with tempfile.TemporaryDirectory() as d:
    d = Path(d)
    url = "https://www.fast.ai/images/jh-head.jpg"
    _download_image_inner(d, (125,url))
    assert (d/'00000125.jpg').is_file()
with tempfile.TemporaryDirectory() as d:
    d = Path(d)
    url = "https://www.fast.ai/images/jh-head.jpg"
    _download_image_inner(d, (125,url), preserve_filename=True)
    assert (d/'jh-head.jpg').is_file()
    assert not (d/'jh-head.jpg1').exists()
    _download_image_inner(d, (125,url), preserve_filename=True)
    assert (d/'jh-head.jpg').is_file()
    assert (d/'jh-head1.jpg').is_file()

`download_images`[source]

download_images(dest, url_file=None, urls=None, max_pics=1000, n_workers=8, timeout=4, preserve_filename=False)

Download images listed in text file url_file to path dest, at most max_pics

with tempfile.TemporaryDirectory() as d:
    d = Path(d)
    url_file = d/'urls.txt'
    url_file.write_text("n".join([f"https://www.fast.ai/images/{n}" for n in "jh-head.jpg thomas.JPG sg-head.jpg".split()]))
    download_images(d, url_file)
    for i in [0,2]: assert (d/f'0000000{i}.jpg').is_file()
    assert (d/f'00000001.JPG').is_file()
with tempfile.TemporaryDirectory() as d:
    d = Path(d)
    url_file = d/'urls.txt'
    url_file.write_text("n".join([f"https://www.fast.ai/images/{n}" for n in "jh-head.jpg thomas.JPG sg-head.jpg".split()]))
    download_images(d, url_file, preserve_filename=True)
    assert (d/'jh-head.jpg').is_file()
    assert (d/'thomas.JPG').is_file()
    assert (d/'sg-head.jpg').is_file()
    assert not (d/'jh-head1.jpg').exists()
    assert not (d/'thomas1.JPG').exists()
    assert not (d/'sg-head1.jpg').exists()
    download_images(d, url_file, preserve_filename=True)
    assert (d/'jh-head.jpg').is_file()
    assert (d/'thomas.JPG').is_file()
    assert (d/'sg-head.jpg').is_file()
    assert (d/'jh-head1.jpg').is_file()
    assert (d/'thomas1.JPG').is_file()
    assert (d/'sg-head1.jpg').is_file()

`resize_to`[source]

resize_to(img, targ_sz, use_min=False)

Size to resize to, to hit targ_sz at same aspect ratio, in PIL coords (i.e w*h)

class _FakeImg():
    def __init__(self, size): self.size=size
img = _FakeImg((200,500))
test_eq(resize_to(img, 400), [160,400])
test_eq(resize_to(img, 400, use_min=True), [400,1000])

`verify_image`[source]

verify_image(fn)

Confirm that fn can be opened

`verify_images`[source]

verify_images(fns)

Find images in fns that can’t be opened

`resize_image`[source]

resize_image(file, dest, max_size=None, n_channels=3, ext=None, img_format=None, resample=2, resume=False, **kwargs)

Resize file to dest to max_size

file = Path('images/puppy.jpg')
dest = Path('.')
resize_image(file, max_size=400, dest=dest)
im = Image.open(dest/file.name)
test_eq(im.shape[1],400)
(dest/file.name).unlink()

`resize_images`[source]

resize_images(path, max_workers=2, max_size=None, recurse=False, dest=Path('.'), n_channels=3, ext=None, img_format=None, resample=2, resume=None, **kwargs)

Resize files on path recursively to dest to max_size

with tempfile.TemporaryDirectory() as d:
    dest = Path(d)/'resized_images'
    resize_images('images', max_size=100, dest=dest)

/Users/hamelsmu/anaconda3/lib/python3.8/site-packages/PIL/Image.py:962: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images
  warnings.warn(