| |
| |
|
|
| """Image preprocessing utilities (resize with padding, etc.). |
| |
| Vendored from openpi_client.image_tools (original at |
| ``openpi/packages/openpi-client/src/openpi_client/image_tools.py``) so that |
| inference clients can share the same resize behavior without forcing |
| ``openpi_client`` as a runtime dep for non-openpi backends. Kept |
| semantically identical to the upstream. |
| """ |
|
|
| import numpy as np |
| from PIL import Image |
|
|
|
|
| def convert_to_uint8(img: np.ndarray) -> np.ndarray: |
| """Convert a float image to uint8. |
| |
| Reduces the size of the image when sending it over the network. |
| """ |
| if np.issubdtype(img.dtype, np.floating): |
| img = (255 * img).astype(np.uint8) |
| return img |
|
|
|
|
| def resize_with_pad( |
| images: np.ndarray, height: int, width: int, method=Image.BILINEAR |
| ) -> np.ndarray: |
| """Replicates ``tf.image.resize_with_pad`` for a batch of images using PIL. |
| |
| Resizes while preserving aspect ratio and pads the remainder with zeros. |
| |
| Args: |
| images: Batch of images in ``[..., height, width, channel]`` format. |
| height: Target height. |
| width: Target width. |
| method: PIL interpolation method. Default is bilinear. |
| |
| Returns: |
| Resized images in ``[..., height, width, channel]``. |
| """ |
| if images.shape[-3:-1] == (height, width): |
| return images |
|
|
| original_shape = images.shape |
| images = images.reshape(-1, *original_shape[-3:]) |
| resized = np.stack( |
| [_resize_with_pad_pil(Image.fromarray(im), height, width, method=method) for im in images] |
| ) |
| return resized.reshape(*original_shape[:-3], *resized.shape[-3:]) |
|
|
|
|
| def _resize_with_pad_pil(image: Image.Image, height: int, width: int, method: int) -> Image.Image: |
| """Resize one PIL image to target size without distortion, padding with zeros. |
| |
| Note: PIL uses ``(width, height, channel)`` ordering. |
| """ |
| cur_width, cur_height = image.size |
| if cur_width == width and cur_height == height: |
| return image |
|
|
| ratio = max(cur_width / width, cur_height / height) |
| resized_height = int(cur_height / ratio) |
| resized_width = int(cur_width / ratio) |
| resized_image = image.resize((resized_width, resized_height), resample=method) |
|
|
| zero_image = Image.new(resized_image.mode, (width, height), 0) |
| pad_height = max(0, int((height - resized_height) / 2)) |
| pad_width = max(0, int((width - resized_width) / 2)) |
| zero_image.paste(resized_image, (pad_width, pad_height)) |
| assert zero_image.size == (width, height) |
| return zero_image |
|
|
