mirror of
https://github.com/finegrain-ai/refiners.git
synced 2024-11-25 07:38:45 +00:00
53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
import pytest
|
|
import torch
|
|
from PIL import Image
|
|
|
|
from refiners.foundationals.segment_anything.utils import (
|
|
compute_scaled_size,
|
|
image_to_scaled_tensor,
|
|
pad_image_tensor,
|
|
preprocess_image,
|
|
)
|
|
|
|
|
|
@pytest.fixture
|
|
def image_encoder_resolution() -> int:
|
|
return 1024
|
|
|
|
|
|
def test_compute_scaled_size(image_encoder_resolution: int) -> None:
|
|
w, h = (1536, 768)
|
|
scaled_size = compute_scaled_size((h, w), image_encoder_resolution)
|
|
|
|
assert scaled_size == (512, 1024)
|
|
|
|
|
|
def test_rgb_image_to_scaled_tensor() -> None:
|
|
image = Image.new("RGB", (1536, 768))
|
|
tensor = image_to_scaled_tensor(image, (512, 1024))
|
|
assert tensor.shape == (1, 3, 512, 1024)
|
|
|
|
|
|
def test_grayscale_image_to_scaled_tensor() -> None:
|
|
image = Image.new("L", (1536, 768))
|
|
tensor = image_to_scaled_tensor(image, (512, 1024))
|
|
assert tensor.shape == (1, 1, 512, 1024)
|
|
|
|
|
|
def test_preprocess_image(image_encoder_resolution: int) -> None:
|
|
image = Image.new("RGB", (1536, 768))
|
|
preprocessed = preprocess_image(image, image_encoder_resolution)
|
|
|
|
assert preprocessed.shape == (1, 3, 1024, 1024)
|
|
|
|
|
|
def test_pad_image_tensor(image_encoder_resolution: int) -> None:
|
|
w, h = (1536, 768)
|
|
image = Image.new("RGB", (w, h), color="white")
|
|
scaled_size = compute_scaled_size((h, w), image_encoder_resolution)
|
|
scaled_image_tensor = image_to_scaled_tensor(image, scaled_size)
|
|
padded_image_tensor = pad_image_tensor(scaled_image_tensor, scaled_size, image_encoder_resolution)
|
|
|
|
assert padded_image_tensor.shape == (1, 3, 1024, 1024)
|
|
assert torch.all(padded_image_tensor[:, :, 512:, :] == 0)
|