Spaces:
Running on Zero
Running on Zero
| """Shared aspect-preserving resize and center crop for external images.""" | |
| from torchvision.transforms import functional as TF | |
| def resize_center_crop(image, height, width): | |
| """Scale to cover the target, then crop its center; report pixel geometry.""" | |
| source_width, source_height = image.size | |
| if source_width * height >= width * source_height: | |
| resized_height = height | |
| resized_width = (source_width * height + source_height - 1) // source_height | |
| else: | |
| resized_width = width | |
| resized_height = (source_height * width + source_width - 1) // source_width | |
| left = (resized_width - width) // 2 | |
| top = (resized_height - height) // 2 | |
| image = TF.resize(image, [resized_height, resized_width], antialias=True) | |
| image = TF.crop(image, top, left, height, width) | |
| return image, { | |
| "resized_size": {"width": resized_width, "height": resized_height}, | |
| "crop_box": [left, top, left + width, top + height], | |
| "cropped": resized_width != width or resized_height != height, | |
| } | |
| class ResizeCenterCrop: | |
| """Callable transform using the same preprocessing as single-image input.""" | |
| def __init__(self, height, width): | |
| self.height = height | |
| self.width = width | |
| def __call__(self, image): | |
| return resize_center_crop(image, self.height, self.width)[0] | |