diff --git a/tests/e2e/test_diffusion.py b/tests/e2e/test_diffusion.py
index 90e3534..c953c68 100644
--- a/tests/e2e/test_diffusion.py
+++ b/tests/e2e/test_diffusion.py
@@ -50,10 +50,6 @@ from refiners.foundationals.latent_diffusion.style_aligned import StyleAlignedAd
 from ..weight_paths import get_path
 
 
-def _img_open(path: Path) -> Image.Image:
-    return Image.open(path)  # type: ignore
-
-
 @pytest.fixture(autouse=True)
 def ensure_gc():
     # Avoid GPU OOMs
@@ -68,132 +64,132 @@ def ref_path(test_e2e_path: Path) -> Path:
 
 @pytest.fixture(scope="module")
 def cutecat_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "cutecat_init.png").convert("RGB")
+    return Image.open(ref_path / "cutecat_init.png").convert("RGB")
 
 
 @pytest.fixture(scope="module")
 def kitchen_dog(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "kitchen_dog.png").convert("RGB")
+    return Image.open(ref_path / "kitchen_dog.png").convert("RGB")
 
 
 @pytest.fixture(scope="module")
 def kitchen_dog_mask(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "kitchen_dog_mask.png").convert("RGB")
+    return Image.open(ref_path / "kitchen_dog_mask.png").convert("RGB")
 
 
 @pytest.fixture(scope="module")
 def woman_image(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "woman.png").convert("RGB")
+    return Image.open(ref_path / "woman.png").convert("RGB")
 
 
 @pytest.fixture(scope="module")
 def statue_image(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "statue.png").convert("RGB")
+    return Image.open(ref_path / "statue.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_random_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_random_init.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_random_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_random_init_bfloat16(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_random_init_bfloat16.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_random_init_bfloat16.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_sde_random_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_sde_random_init.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_sde_random_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_sde_karras_random_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_sde_karras_random_init.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_sde_karras_random_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_random_init_euler(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_random_init_euler.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_random_init_euler.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_karras_random_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_karras_random_init.png").convert("RGB")
+    return Image.open(ref_path / "expected_karras_random_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_random_init_sag(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_random_init_sag.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_random_init_sag.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_init_image(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_init_image.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_init_image.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_ella_adapter(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_ella_adapter.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_ella_adapter.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_std_inpainting(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_std_inpainting.png").convert("RGB")
+    return Image.open(ref_path / "expected_std_inpainting.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_controlnet_stack(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_controlnet_stack.png").convert("RGB")
+    return Image.open(ref_path / "expected_controlnet_stack.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_ip_adapter_woman(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_ip_adapter_woman.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_ip_adapter_woman.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_ip_adapter_multi(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_ip_adapter_multi.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_ip_adapter_multi.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_ip_adapter_plus_statue(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_ip_adapter_plus_statue.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_ip_adapter_plus_statue.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_sdxl_ip_adapter_woman(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_sdxl_ip_adapter_woman.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_sdxl_ip_adapter_woman.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_sdxl_ip_adapter_plus_woman(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_sdxl_ip_adapter_plus_woman.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_sdxl_ip_adapter_plus_woman.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_ip_adapter_controlnet(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_ip_adapter_controlnet.png").convert("RGB")
+    return Image.open(ref_path / "expected_ip_adapter_controlnet.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_sdxl_ddim_random_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_cutecat_sdxl_ddim_random_init.png").convert("RGB")
+    return Image.open(ref_path / "expected_cutecat_sdxl_ddim_random_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_sdxl_ddim_random_init_sag(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_cutecat_sdxl_ddim_random_init_sag.png").convert("RGB")
+    return Image.open(ref_path / "expected_cutecat_sdxl_ddim_random_init_sag.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_sdxl_euler_random_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_cutecat_sdxl_euler_random_init.png").convert("RGB")
+    return Image.open(ref_path / "expected_cutecat_sdxl_euler_random_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_style_aligned(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_style_aligned.png").convert(mode="RGB")
+    return Image.open(ref_path / "expected_style_aligned.png").convert(mode="RGB")
 
 
 @pytest.fixture(scope="module", params=["canny", "depth", "lineart", "normals", "sam"])
@@ -207,8 +203,8 @@ def controlnet_data(
     request: pytest.FixtureRequest,
 ) -> Iterator[tuple[str, Image.Image, Image.Image, Path]]:
     cn_name: str = request.param
-    condition_image = _img_open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
-    expected_image = _img_open(ref_path / f"expected_controlnet_{cn_name}.png").convert("RGB")
+    condition_image = Image.open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
+    expected_image = Image.open(ref_path / f"expected_controlnet_{cn_name}.png").convert("RGB")
 
     weights_fn = {
         "depth": controlnet_depth_weights_path,
@@ -229,8 +225,8 @@ def controlnet_data_scale_decay(
     request: pytest.FixtureRequest,
 ) -> Iterator[tuple[str, Image.Image, Image.Image, Path]]:
     cn_name: str = request.param
-    condition_image = _img_open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
-    expected_image = _img_open(ref_path / f"expected_controlnet_{cn_name}_scale_decay.png").convert("RGB")
+    condition_image = Image.open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
+    expected_image = Image.open(ref_path / f"expected_controlnet_{cn_name}_scale_decay.png").convert("RGB")
 
     weights_fn = {
         "canny": controlnet_canny_weights_path,
@@ -245,8 +241,8 @@ def controlnet_data_tile(
     ref_path: Path,
     controlnet_tiles_weights_path: Path,
 ) -> tuple[Image.Image, Image.Image, Path]:
-    condition_image = _img_open(ref_path / f"low_res_dog.png").convert("RGB").resize((1024, 1024))  # type: ignore
-    expected_image = _img_open(ref_path / f"expected_controlnet_tile.png").convert("RGB")
+    condition_image = Image.open(ref_path / f"low_res_dog.png").convert("RGB").resize((1024, 1024))  # type: ignore
+    expected_image = Image.open(ref_path / f"expected_controlnet_tile.png").convert("RGB")
     return condition_image, expected_image, controlnet_tiles_weights_path
 
 
@@ -256,8 +252,8 @@ def controlnet_data_canny(
     controlnet_canny_weights_path: Path,
 ) -> tuple[str, Image.Image, Image.Image, Path]:
     cn_name = "canny"
-    condition_image = _img_open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
-    expected_image = _img_open(ref_path / f"expected_controlnet_{cn_name}.png").convert("RGB")
+    condition_image = Image.open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
+    expected_image = Image.open(ref_path / f"expected_controlnet_{cn_name}.png").convert("RGB")
     return cn_name, condition_image, expected_image, controlnet_canny_weights_path
 
 
@@ -267,8 +263,8 @@ def controlnet_data_depth(
     controlnet_depth_weights_path: Path,
 ) -> tuple[str, Image.Image, Image.Image, Path]:
     cn_name = "depth"
-    condition_image = _img_open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
-    expected_image = _img_open(ref_path / f"expected_controlnet_{cn_name}.png").convert("RGB")
+    condition_image = Image.open(ref_path / f"cutecat_guide_{cn_name}.png").convert("RGB")
+    expected_image = Image.open(ref_path / f"expected_controlnet_{cn_name}.png").convert("RGB")
     return cn_name, condition_image, expected_image, controlnet_depth_weights_path
 
 
@@ -336,12 +332,12 @@ def controllora_sdxl_config(
 ) -> tuple[Image.Image, dict[str, ControlLoraResolvedConfig]]:
     name: str = request.param[0]
     configs: dict[str, ControlLoraConfig] = request.param[1]
-    expected_image = _img_open(ref_path / name).convert("RGB")
+    expected_image = Image.open(ref_path / name).convert("RGB")
 
     loaded_configs = {
         config_name: ControlLoraResolvedConfig(
             scale=config.scale,
-            condition_image=_img_open(ref_path / config.condition_path).convert("RGB"),
+            condition_image=Image.open(ref_path / config.condition_path).convert("RGB"),
             weights_path=get_path(config.weights, use_local_weights),
         )
         for config_name, config in configs.items()
@@ -356,8 +352,8 @@ def t2i_adapter_data_depth(
     t2i_depth_weights_path: Path,
 ) -> tuple[str, Image.Image, Image.Image, Path]:
     name = "depth"
-    condition_image = _img_open(ref_path / f"cutecat_guide_{name}.png").convert("RGB")
-    expected_image = _img_open(ref_path / f"expected_t2i_adapter_{name}.png").convert("RGB")
+    condition_image = Image.open(ref_path / f"cutecat_guide_{name}.png").convert("RGB")
+    expected_image = Image.open(ref_path / f"expected_t2i_adapter_{name}.png").convert("RGB")
     return name, condition_image, expected_image, t2i_depth_weights_path
 
 
@@ -367,8 +363,8 @@ def t2i_adapter_xl_data_canny(
     t2i_sdxl_canny_weights_path: Path,
 ) -> tuple[str, Image.Image, Image.Image, Path]:
     name = "canny"
-    condition_image = _img_open(ref_path / f"fairy_guide_{name}.png").convert("RGB")
-    expected_image = _img_open(ref_path / f"expected_t2i_adapter_xl_{name}.png").convert("RGB")
+    condition_image = Image.open(ref_path / f"fairy_guide_{name}.png").convert("RGB")
+    expected_image = Image.open(ref_path / f"expected_t2i_adapter_xl_{name}.png").convert("RGB")
     return name, condition_image, expected_image, t2i_sdxl_canny_weights_path
 
 
@@ -377,7 +373,7 @@ def lora_data_pokemon(
     ref_path: Path,
     lora_pokemon_weights_path: Path,
 ) -> tuple[Image.Image, dict[str, torch.Tensor]]:
-    expected_image = _img_open(ref_path / "expected_lora_pokemon.png").convert("RGB")
+    expected_image = Image.open(ref_path / "expected_lora_pokemon.png").convert("RGB")
     tensors = load_tensors(lora_pokemon_weights_path)
     return expected_image, tensors
 
@@ -387,7 +383,7 @@ def lora_data_dpo(
     ref_path: Path,
     lora_dpo_weights_path: Path,
 ) -> tuple[Image.Image, dict[str, torch.Tensor]]:
-    expected_image = _img_open(ref_path / "expected_sdxl_dpo_lora.png").convert("RGB")
+    expected_image = Image.open(ref_path / "expected_sdxl_dpo_lora.png").convert("RGB")
     tensors = load_from_safetensors(lora_dpo_weights_path)
     return expected_image, tensors
 
@@ -411,62 +407,62 @@ def lora_sliders(
 
 @pytest.fixture
 def scene_image_inpainting_refonly(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "inpainting-scene.png").convert("RGB")
+    return Image.open(ref_path / "inpainting-scene.png").convert("RGB")
 
 
 @pytest.fixture
 def mask_image_inpainting_refonly(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "inpainting-mask.png").convert("RGB")
+    return Image.open(ref_path / "inpainting-mask.png").convert("RGB")
 
 
 @pytest.fixture
 def target_image_inpainting_refonly(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "inpainting-target.png").convert("RGB")
+    return Image.open(ref_path / "inpainting-target.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_inpainting_refonly(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_inpainting_refonly.png").convert("RGB")
+    return Image.open(ref_path / "expected_inpainting_refonly.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_refonly(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_refonly.png").convert("RGB")
+    return Image.open(ref_path / "expected_refonly.png").convert("RGB")
 
 
 @pytest.fixture
 def condition_image_refonly(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "cyberpunk_guide.png").convert("RGB")
+    return Image.open(ref_path / "cyberpunk_guide.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_textual_inversion_random_init(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_textual_inversion_random_init.png").convert("RGB")
+    return Image.open(ref_path / "expected_textual_inversion_random_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_multi_diffusion(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_multi_diffusion.png").convert(mode="RGB")
+    return Image.open(ref_path / "expected_multi_diffusion.png").convert(mode="RGB")
 
 
 @pytest.fixture
 def expected_multi_diffusion_dpm(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_multi_diffusion_dpm.png").convert(mode="RGB")
+    return Image.open(ref_path / "expected_multi_diffusion_dpm.png").convert(mode="RGB")
 
 
 @pytest.fixture
 def expected_restart(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_restart.png").convert(mode="RGB")
+    return Image.open(ref_path / "expected_restart.png").convert(mode="RGB")
 
 
 @pytest.fixture
 def expected_freeu(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_freeu.png").convert(mode="RGB")
+    return Image.open(ref_path / "expected_freeu.png").convert(mode="RGB")
 
 
 @pytest.fixture
 def expected_sdxl_multi_loras(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_sdxl_multi_loras.png").convert(mode="RGB")
+    return Image.open(ref_path / "expected_sdxl_multi_loras.png").convert(mode="RGB")
 
 
 @pytest.fixture
@@ -476,10 +472,10 @@ def hello_world_assets(ref_path: Path) -> tuple[Image.Image, Image.Image, Image.
     image_prompt = assets / "dragon_quest_slime.jpg"
     condition_image = assets / "dropy_canny.png"
     return (
-        _img_open(dropy).convert(mode="RGB"),
-        _img_open(image_prompt).convert(mode="RGB"),
-        _img_open(condition_image).convert(mode="RGB"),
-        _img_open(ref_path / "expected_dropy_slime_9752.png").convert(mode="RGB"),
+        Image.open(dropy).convert(mode="RGB"),
+        Image.open(image_prompt).convert(mode="RGB"),
+        Image.open(condition_image).convert(mode="RGB"),
+        Image.open(ref_path / "expected_dropy_slime_9752.png").convert(mode="RGB"),
     )
 
 
@@ -2639,7 +2635,7 @@ def test_multi_upscaler_small(
 
 @pytest.fixture(scope="module")
 def expected_ic_light(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_ic_light.png").convert("RGB")
+    return Image.open(ref_path / "expected_ic_light.png").convert("RGB")
 
 
 @pytest.fixture(scope="module")
diff --git a/tests/e2e/test_doc_examples.py b/tests/e2e/test_doc_examples.py
index 4e6d4ef..10c08f7 100644
--- a/tests/e2e/test_doc_examples.py
+++ b/tests/e2e/test_doc_examples.py
@@ -13,10 +13,6 @@ from refiners.foundationals.latent_diffusion.lora import SDLoraManager
 from refiners.foundationals.latent_diffusion.stable_diffusion_xl.model import StableDiffusion_XL
 
 
-def _img_open(path: Path) -> Image.Image:
-    return Image.open(path)  # type: ignore
-
-
 @pytest.fixture(autouse=True)
 def ensure_gc():
     # Avoid GPU OOMs
@@ -51,27 +47,27 @@ def sdxl(
 
 @pytest.fixture
 def image_prompt_german_castle(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "german-castle.jpg").convert("RGB")
+    return Image.open(ref_path / "german-castle.jpg").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_guide_adapting_sdxl_vanilla(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_guide_adapting_sdxl_vanilla.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_guide_adapting_sdxl_vanilla.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_guide_adapting_sdxl_single_lora(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_guide_adapting_sdxl_single_lora.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_guide_adapting_sdxl_single_lora.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_guide_adapting_sdxl_multiple_loras(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_guide_adapting_sdxl_multiple_loras.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_guide_adapting_sdxl_multiple_loras.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_guide_adapting_sdxl_loras_ip_adapter(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_image_guide_adapting_sdxl_loras_ip_adapter.png").convert("RGB")
+    return Image.open(ref_path / "expected_image_guide_adapting_sdxl_loras_ip_adapter.png").convert("RGB")
 
 
 @no_grad()
diff --git a/tests/e2e/test_lcm.py b/tests/e2e/test_lcm.py
index c2e03e3..69863be 100644
--- a/tests/e2e/test_lcm.py
+++ b/tests/e2e/test_lcm.py
@@ -15,10 +15,6 @@ from refiners.foundationals.latent_diffusion.stable_diffusion_xl.lcm_lora import
 from refiners.foundationals.latent_diffusion.stable_diffusion_xl.model import StableDiffusion_XL
 
 
-def _img_open(path: Path) -> Image.Image:
-    return Image.open(path)  # type: ignore
-
-
 @pytest.fixture(autouse=True)
 def ensure_gc():
     # Avoid GPU OOMs
@@ -33,17 +29,17 @@ def ref_path(test_e2e_path: Path) -> Path:
 
 @pytest.fixture
 def expected_lcm_base(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_lcm_base.png").convert("RGB")
+    return Image.open(ref_path / "expected_lcm_base.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_lcm_lora_1_0(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_lcm_lora_1_0.png").convert("RGB")
+    return Image.open(ref_path / "expected_lcm_lora_1_0.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_lcm_lora_1_2(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_lcm_lora_1_2.png").convert("RGB")
+    return Image.open(ref_path / "expected_lcm_lora_1_2.png").convert("RGB")
 
 
 @no_grad()
diff --git a/tests/e2e/test_lightning.py b/tests/e2e/test_lightning.py
index 0acf358..3547cf4 100644
--- a/tests/e2e/test_lightning.py
+++ b/tests/e2e/test_lightning.py
@@ -14,10 +14,6 @@ from refiners.foundationals.latent_diffusion.stable_diffusion_xl.lcm_lora import
 from refiners.foundationals.latent_diffusion.stable_diffusion_xl.model import StableDiffusion_XL
 
 
-def _img_open(path: Path) -> Image.Image:
-    return Image.open(path)  # type: ignore
-
-
 @pytest.fixture(autouse=True)
 def ensure_gc():
     # Avoid GPU OOMs
@@ -32,17 +28,17 @@ def ref_path(test_e2e_path: Path) -> Path:
 
 @pytest.fixture
 def expected_lightning_base_4step(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_lightning_base_4step.png").convert("RGB")
+    return Image.open(ref_path / "expected_lightning_base_4step.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_lightning_base_1step(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_lightning_base_1step.png").convert("RGB")
+    return Image.open(ref_path / "expected_lightning_base_1step.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_lightning_lora_4step(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_lightning_lora_4step.png").convert("RGB")
+    return Image.open(ref_path / "expected_lightning_lora_4step.png").convert("RGB")
 
 
 @no_grad()
diff --git a/tests/e2e/test_mvanet.py b/tests/e2e/test_mvanet.py
index 0022f71..2ee5ce1 100644
--- a/tests/e2e/test_mvanet.py
+++ b/tests/e2e/test_mvanet.py
@@ -10,10 +10,6 @@ from refiners.fluxion.utils import image_to_tensor, no_grad, normalize, tensor_t
 from refiners.foundationals.swin.mvanet import MVANet
 
 
-def _img_open(path: Path) -> Image.Image:
-    return Image.open(path)  # type: ignore
-
-
 @pytest.fixture(scope="module")
 def ref_path(test_e2e_path: Path) -> Path:
     return test_e2e_path / "test_mvanet_ref"
@@ -21,12 +17,12 @@ def ref_path(test_e2e_path: Path) -> Path:
 
 @pytest.fixture(scope="module")
 def ref_cactus(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "cactus.png").convert("RGB")
+    return Image.open(ref_path / "cactus.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_cactus_mask(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_cactus_mask.png")
+    return Image.open(ref_path / "expected_cactus_mask.png")
 
 
 @pytest.fixture
diff --git a/tests/e2e/test_preprocessors.py b/tests/e2e/test_preprocessors.py
index c5c9ae6..f8c7c00 100644
--- a/tests/e2e/test_preprocessors.py
+++ b/tests/e2e/test_preprocessors.py
@@ -9,10 +9,6 @@ from refiners.fluxion.utils import image_to_tensor, no_grad, tensor_to_image
 from refiners.foundationals.latent_diffusion.preprocessors.informative_drawings import InformativeDrawings
 
 
-def _img_open(path: Path) -> Image.Image:
-    return Image.open(path)  # type: ignore
-
-
 @pytest.fixture(scope="module")
 def diffusion_ref_path(test_e2e_path: Path) -> Path:
     return test_e2e_path / "test_diffusion_ref"
@@ -20,12 +16,12 @@ def diffusion_ref_path(test_e2e_path: Path) -> Path:
 
 @pytest.fixture(scope="module")
 def cutecat_init(diffusion_ref_path: Path) -> Image.Image:
-    return _img_open(diffusion_ref_path / "cutecat_init.png").convert("RGB")
+    return Image.open(diffusion_ref_path / "cutecat_init.png").convert("RGB")
 
 
 @pytest.fixture
 def expected_image_informative_drawings(diffusion_ref_path: Path) -> Image.Image:
-    return _img_open(diffusion_ref_path / "cutecat_guide_lineart.png").convert("RGB")
+    return Image.open(diffusion_ref_path / "cutecat_guide_lineart.png").convert("RGB")
 
 
 @pytest.fixture
diff --git a/tests/e2e/test_solutions.py b/tests/e2e/test_solutions.py
index 5dc47ca..892d5ba 100644
--- a/tests/e2e/test_solutions.py
+++ b/tests/e2e/test_solutions.py
@@ -8,10 +8,6 @@ from tests.utils import ensure_similar_images
 from refiners.solutions import BoxSegmenter
 
 
-def _img_open(path: Path) -> Image.Image:
-    return Image.open(path)  # type: ignore
-
-
 @pytest.fixture(scope="module")
 def ref_path(test_e2e_path: Path) -> Path:
     return test_e2e_path / "test_solutions_ref"
@@ -19,22 +15,22 @@ def ref_path(test_e2e_path: Path) -> Path:
 
 @pytest.fixture(scope="module")
 def ref_shelves(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "shelves.jpg").convert("RGB")
+    return Image.open(ref_path / "shelves.jpg").convert("RGB")
 
 
 @pytest.fixture
 def expected_box_segmenter_plant_mask(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_box_segmenter_plant_mask.png")
+    return Image.open(ref_path / "expected_box_segmenter_plant_mask.png")
 
 
 @pytest.fixture
 def expected_box_segmenter_spray_mask(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_box_segmenter_spray_mask.png")
+    return Image.open(ref_path / "expected_box_segmenter_spray_mask.png")
 
 
 @pytest.fixture
 def expected_box_segmenter_spray_cropped_mask(ref_path: Path) -> Image.Image:
-    return _img_open(ref_path / "expected_box_segmenter_spray_cropped_mask.png")
+    return Image.open(ref_path / "expected_box_segmenter_spray_cropped_mask.png")
 
 
 def test_box_segmenter(