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| import ast | |
| import math | |
| from PIL import Image | |
| def get_anyres_image_grid_shape(image_size, grid_pinpoints, patch_size): | |
| """ | |
| Calculate the shape of the image patch grid after the preprocessing for images of any resolution. | |
| Args: | |
| image_size (tuple): The size of the input image in the format (width, height). | |
| grid_pinpoints (str): A string representation of a list of possible resolutions. | |
| patch_size (int): The size of each image patch. | |
| Returns: | |
| tuple: The shape of the image patch grid in the format (width, height). | |
| """ | |
| if type(grid_pinpoints) is list: | |
| possible_resolutions = grid_pinpoints | |
| else: | |
| possible_resolutions = ast.literal_eval(grid_pinpoints) | |
| width, height = select_best_resolution(image_size, possible_resolutions) | |
| return width // patch_size, height // patch_size | |
| def select_best_resolution(original_size, possible_resolutions): | |
| """ | |
| Selects the best resolution from a list of possible resolutions based on the original size. | |
| Args: | |
| original_size (tuple): The original size of the image in the format (width, height). | |
| possible_resolutions (list): A list of possible resolutions in the format [(width1, height1), (width2, height2), ...]. | |
| Returns: | |
| tuple: The best fit resolution in the format (width, height). | |
| """ | |
| original_width, original_height = original_size | |
| best_fit = None | |
| max_effective_resolution = 0 | |
| min_wasted_resolution = float('inf') | |
| for width, height in possible_resolutions: | |
| scale = min(width / original_width, height / original_height) | |
| downscaled_width, downscaled_height = int(original_width * scale), int(original_height * scale) | |
| effective_resolution = min(downscaled_width * downscaled_height, original_width * original_height) | |
| wasted_resolution = (width * height) - effective_resolution | |
| if effective_resolution > max_effective_resolution or (effective_resolution == max_effective_resolution and wasted_resolution < min_wasted_resolution): | |
| max_effective_resolution = effective_resolution | |
| min_wasted_resolution = wasted_resolution | |
| best_fit = (width, height) | |
| return best_fit | |
| ## added by llava-1.6 | |
| def divide_to_patches(image, patch_size): | |
| """ | |
| Divides an image into patches of a specified size. | |
| Args: | |
| image (PIL.Image.Image): The input image. | |
| patch_size (int): The size of each patch. | |
| Returns: | |
| list: A list of PIL.Image.Image objects representing the patches. | |
| """ | |
| patches = [] | |
| width, height = image.size | |
| for i in range(0, height, patch_size): | |
| for j in range(0, width, patch_size): | |
| box = (j, i, j + patch_size, i + patch_size) | |
| patch = image.crop(box) | |
| patches.append(patch) | |
| return patches | |
| ## added by llava-1.6 | |
| def resize_and_pad_image(image, target_resolution): | |
| """ | |
| Resize and pad an image to a target resolution while maintaining aspect ratio. | |
| Args: | |
| image (PIL.Image.Image): The input image. | |
| target_resolution (tuple): The target resolution (width, height) of the image. | |
| Returns: | |
| PIL.Image.Image: The resized and padded image. | |
| """ | |
| original_width, original_height = image.size | |
| target_width, target_height = target_resolution | |
| scale_w = target_width / original_width | |
| scale_h = target_height / original_height | |
| if scale_w < scale_h: | |
| new_width = target_width | |
| new_height = min(math.ceil(original_height * scale_w), target_height) | |
| else: | |
| new_height = target_height | |
| new_width = min(math.ceil(original_width * scale_h), target_width) | |
| # Resize the image | |
| resized_image = image.resize((new_width, new_height)) | |
| new_image = Image.new('RGB', (target_width, target_height), (0, 0, 0)) | |
| paste_x = (target_width - new_width) // 2 | |
| paste_y = (target_height - new_height) // 2 | |
| new_image.paste(resized_image, (paste_x, paste_y)) | |
| return new_image | |
| def get_value_from_kwargs(kwargs, name): | |
| if name in kwargs: | |
| return kwargs.pop(name) | |
| else: | |
| return None |