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import cv2 |
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import PIL |
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import requests |
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import numpy as np |
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from lama_cleaner.model.lama import LaMa |
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from lama_cleaner.schema import Config |
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def download_image(url): |
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image = PIL.Image.open(requests.get(url, stream=True).raw) |
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image = PIL.ImageOps.exif_transpose(image) |
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image = image.convert("RGB") |
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return image |
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img_url = "https://raw.githubusercontent.com/Sanster/lama-cleaner/main/assets/dog.jpg" |
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mask_url = "https://user-images.githubusercontent.com/3998421/202105351-9fcc4bf8-129d-461a-8524-92e4caad431f.png" |
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image = np.asarray(download_image(img_url)) |
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mask = np.asarray(download_image(mask_url).convert("L")) |
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model = LaMa("cpu") |
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result = model(image, mask, Config(hd_strategy="Original", ldm_steps=20, hd_strategy_crop_margin=128, hd_strategy_crop_trigger_size=800, hd_strategy_resize_limit=800)) |
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cv2.imwrite("lama_inpaint_demo.jpg", result) |
