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from grounded_sam_demo import grounded_sam_demo |
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import numpy as np |
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from PIL import Image |
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from scipy.ndimage import convolve |
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from scipy.ndimage import binary_dilation |
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def get_sd_mask(color_mask_pil, target=(72, 4, 84), tolerance=50): |
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image_array = np.array(color_mask_pil) |
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target = np.array(list(target) + [255] * |
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(image_array.shape[-1] - len(target))) |
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mask = np.abs(image_array - target) <= tolerance |
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mask = np.all(mask, axis=-1) |
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new_image_array = np.ones_like(image_array) * 255 |
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new_image_array[mask] = [0] * image_array.shape[-1] |
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return Image.fromarray(new_image_array) |
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def expand_white_pixels(input_pil, expand_by=1): |
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img_array = np.array(input_pil) |
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is_white = np.all(img_array == 255, axis=-1) |
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kernel = np.ones((2*expand_by+1, 2*expand_by+1), bool) |
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expanded_white = binary_dilation(is_white, structure=kernel) |
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expanded_array = np.where(expanded_white[..., None], 255, img_array) |
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expanded_pil = Image.fromarray(expanded_array.astype('uint8')) |
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return expanded_pil |
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config_file = "GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py" |
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grounded_checkpoint = "groundingdino_swint_ogc.pth" |
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sam_checkpoint = "sam_hq_vit_h.pth" |
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def just_get_sd_mask(input_pil, text_prompt, padding): |
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print("Doing sam") |
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colored_mask_pil = grounded_sam_demo( |
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input_pil, config_file, grounded_checkpoint, sam_checkpoint, text_prompt) |
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print("doing to white") |
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sd_mask_pil = get_sd_mask(colored_mask_pil) |
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print("expanding white pixels") |
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sd_mask_withpadding_pil = expand_white_pixels(sd_mask_pil, padding) |
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return sd_mask_withpadding_pil |
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