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48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
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import pytest
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import torch
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from PIL import Image
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from refiners.foundationals.segment_anything.utils import (
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compute_scaled_size,
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image_to_scaled_tensor,
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pad_image_tensor,
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preprocess_image,
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)
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@pytest.fixture
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def image_encoder_resolution() -> int:
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return 1024
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def test_compute_scaled_size(image_encoder_resolution: int) -> None:
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w, h = (1536, 768)
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scaled_size = compute_scaled_size((h, w), image_encoder_resolution)
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assert scaled_size == (512, 1024)
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def test_image_to_scaled_tensor() -> None:
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image = Image.new("RGB", (1536, 768))
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tensor = image_to_scaled_tensor(image, (512, 1024))
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assert tensor.shape == (1, 3, 512, 1024)
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def test_preprocess_image(image_encoder_resolution: int) -> None:
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image = Image.new("RGB", (1536, 768))
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preprocessed = preprocess_image(image, image_encoder_resolution)
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assert preprocessed.shape == (1, 3, 1024, 1024)
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def test_pad_image_tensor(image_encoder_resolution: int) -> None:
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w, h = (1536, 768)
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image = Image.new("RGB", (w, h), color="white")
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scaled_size = compute_scaled_size((h, w), image_encoder_resolution)
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scaled_image_tensor = image_to_scaled_tensor(image, scaled_size)
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padded_image_tensor = pad_image_tensor(scaled_image_tensor, scaled_size, image_encoder_resolution)
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assert padded_image_tensor.shape == (1, 3, 1024, 1024)
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assert torch.all(padded_image_tensor[:, :, 512:, :] == 0)
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