# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project import base64 import mimetypes import os from tempfile import NamedTemporaryFile, TemporaryDirectory from typing import TYPE_CHECKING, NamedTuple import numpy as np import pytest from PIL import Image, ImageChops from vllm.multimodal.image import convert_image_mode from vllm.multimodal.inputs import PlaceholderRange from vllm.multimodal.utils import MediaConnector, argsort_mm_positions if TYPE_CHECKING: from vllm.multimodal.inputs import MultiModalPlaceholderDict # Test different image extensions (JPG/PNG) and formats (gray/RGB/RGBA) TEST_IMAGE_ASSETS = [ "2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg", # "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" "Grayscale_8bits_palette_sample_image.png", # "https://upload.wikimedia.org/wikipedia/commons/f/fa/Grayscale_8bits_palette_sample_image.png", "1280px-Venn_diagram_rgb.svg.png", # "https://upload.wikimedia.org/wikipedia/commons/thumb/9/91/Venn_diagram_rgb.svg/1280px-Venn_diagram_rgb.svg.png", "RGBA_comp.png", # "https://upload.wikimedia.org/wikipedia/commons/0/0b/RGBA_comp.png", ] TEST_VIDEO_URLS = [ "https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4", "https://github.com/opencv/opencv/raw/refs/tags/4.12.0/samples/data/vtest.avi", ] @pytest.fixture(scope="module") def url_images(local_asset_server) -> dict[str, Image.Image]: return { image_url: local_asset_server.get_image_asset(image_url) for image_url in TEST_IMAGE_ASSETS } def get_supported_suffixes() -> tuple[str, ...]: # We should at least test the file types mentioned in GPT-4 with Vision OPENAI_SUPPORTED_SUFFIXES = ('.png', '.jpeg', '.jpg', '.webp', '.gif') # Additional file types that are supported by us EXTRA_SUPPORTED_SUFFIXES = ('.bmp', '.tiff') return OPENAI_SUPPORTED_SUFFIXES + EXTRA_SUPPORTED_SUFFIXES def _image_equals(a: Image.Image, b: Image.Image) -> bool: return (np.asarray(a) == np.asarray(convert_image_mode(b, a.mode))).all() @pytest.mark.asyncio @pytest.mark.parametrize("image_url", TEST_IMAGE_ASSETS, indirect=True) async def test_fetch_image_http(image_url: str): connector = MediaConnector() image_sync = connector.fetch_image(image_url) image_async = await connector.fetch_image_async(image_url) assert _image_equals(image_sync, image_async) @pytest.mark.asyncio @pytest.mark.parametrize("raw_image_url", TEST_IMAGE_ASSETS) @pytest.mark.parametrize("suffix", get_supported_suffixes()) async def test_fetch_image_base64(url_images: dict[str, Image.Image], raw_image_url: str, suffix: str): connector = MediaConnector() url_image = url_images[raw_image_url] try: mime_type = Image.MIME[Image.registered_extensions()[suffix]] except KeyError: try: mime_type = mimetypes.types_map[suffix] except KeyError: pytest.skip('No MIME type') with NamedTemporaryFile(suffix=suffix) as f: try: url_image.save(f.name) except Exception as e: if e.args[0] == 'cannot write mode RGBA as JPEG': pytest.skip('Conversion not supported') raise base64_image = base64.b64encode(f.read()).decode("utf-8") data_url = f"data:{mime_type};base64,{base64_image}" data_image_sync = connector.fetch_image(data_url) if _image_equals(url_image, Image.open(f)): assert _image_equals(url_image, data_image_sync) else: pass # Lossy format; only check that image can be opened data_image_async = await connector.fetch_image_async(data_url) assert _image_equals(data_image_sync, data_image_async) @pytest.mark.asyncio @pytest.mark.parametrize("image_url", TEST_IMAGE_ASSETS, indirect=True) async def test_fetch_image_local_files(image_url: str): connector = MediaConnector() with TemporaryDirectory() as temp_dir: local_connector = MediaConnector(allowed_local_media_path=temp_dir) origin_image = connector.fetch_image(image_url) origin_image.save(os.path.join(temp_dir, os.path.basename(image_url)), quality=100, icc_profile=origin_image.info.get('icc_profile')) image_async = await local_connector.fetch_image_async( f"file://{temp_dir}/{os.path.basename(image_url)}") image_sync = local_connector.fetch_image( f"file://{temp_dir}/{os.path.basename(image_url)}") # Check that the images are equal assert not ImageChops.difference(image_sync, image_async).getbbox() with pytest.raises(ValueError, match="must be a subpath"): await local_connector.fetch_image_async( f"file://{temp_dir}/../{os.path.basename(image_url)}") with pytest.raises(RuntimeError, match="Cannot load local files"): await connector.fetch_image_async( f"file://{temp_dir}/../{os.path.basename(image_url)}") with pytest.raises(ValueError, match="must be a subpath"): local_connector.fetch_image( f"file://{temp_dir}/../{os.path.basename(image_url)}") with pytest.raises(RuntimeError, match="Cannot load local files"): connector.fetch_image( f"file://{temp_dir}/../{os.path.basename(image_url)}") @pytest.mark.asyncio @pytest.mark.parametrize("image_url", [TEST_IMAGE_ASSETS[0]], indirect=True) async def test_fetch_image_local_files_with_space_in_name(image_url: str): connector = MediaConnector() with TemporaryDirectory() as temp_dir: local_connector = MediaConnector(allowed_local_media_path=temp_dir) origin_image = connector.fetch_image(image_url) filename = "file name with space.jpg" origin_image.save(os.path.join(temp_dir, filename), quality=100, icc_profile=origin_image.info.get('icc_profile')) try: image_async = await local_connector.fetch_image_async( f"file://{temp_dir}/{filename}") image_sync = local_connector.fetch_image( f"file://{temp_dir}/{filename}") except FileNotFoundError as e: pytest.fail( "Failed to fetch image with space in name: {}".format(e)) # Check that the images are equal assert not ImageChops.difference(image_sync, image_async).getbbox() @pytest.mark.asyncio async def test_fetch_image_error_conversion(): connector = MediaConnector() broken_img = "data:image/png;base64,aGVsbG9fdmxsbV9jb21tdW5pdHkK" # PIL.UnidentifiedImageError should be converted to ValueError with pytest.raises(ValueError): await connector.fetch_image_async(broken_img) with pytest.raises(ValueError): connector.fetch_image(broken_img) @pytest.mark.asyncio @pytest.mark.parametrize("video_url", TEST_VIDEO_URLS) @pytest.mark.parametrize("num_frames", [-1, 32, 1800]) async def test_fetch_video_http(video_url: str, num_frames: int): connector = MediaConnector( media_io_kwargs={"video": { "num_frames": num_frames, }}) video_sync, metadata_sync = connector.fetch_video(video_url) video_async, metadata_async = await connector.fetch_video_async(video_url) assert np.array_equal(video_sync, video_async) assert metadata_sync == metadata_async @pytest.mark.asyncio @pytest.mark.parametrize("video_url", TEST_VIDEO_URLS) @pytest.mark.parametrize("max_duration", [1, 60, 1800]) @pytest.mark.parametrize("requested_fps", [2, 24]) async def test_fetch_video_http_with_dynamic_loader( video_url: str, max_duration: int, requested_fps: int, monkeypatch: pytest.MonkeyPatch): with monkeypatch.context() as m: m.setenv("VLLM_VIDEO_LOADER_BACKEND", "opencv_dynamic") connector = MediaConnector( media_io_kwargs={ "video": { "max_duration": max_duration, "requested_fps": requested_fps, } }) video_sync, metadata_sync = connector.fetch_video(video_url) video_async, metadata_async = await connector.fetch_video_async( video_url) assert np.array_equal(video_sync, video_async) assert metadata_sync == metadata_async assert metadata_sync["video_backend"] == "opencv_dynamic" # Used for `test_argsort_mm_positions`. class TestCase(NamedTuple): mm_positions: "MultiModalPlaceholderDict" expected_modality_idxs: list[tuple[str, int]] def test_argsort_mm_positions(): test_cases = [ # Single modality ## Internally sorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=0, length=2), PlaceholderRange(offset=3, length=2), ] }, expected_modality_idxs=[ ("image", 0), ("image", 1), ], ), ## Internally unsorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=3, length=2), PlaceholderRange(offset=0, length=2), ] }, expected_modality_idxs=[ ("image", 1), ("image", 0), ], ), # Two modalities ## Internally sorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=7, length=4), PlaceholderRange(offset=11, length=5), ], "audio": [ PlaceholderRange(offset=0, length=2), PlaceholderRange(offset=2, length=3), ] }, expected_modality_idxs=[ ("audio", 0), ("audio", 1), ("image", 0), ("image", 1), ], ), ## Interleaved, internally sorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=0, length=4), PlaceholderRange(offset=8, length=2), ], "audio": [ PlaceholderRange(offset=5, length=2), PlaceholderRange(offset=11, length=4), ] }, expected_modality_idxs=[ ("image", 0), ("audio", 0), ("image", 1), ("audio", 1), ], ), ## Interleaved, internally unsorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=8, length=2), PlaceholderRange(offset=0, length=4), ], "audio": [ PlaceholderRange(offset=11, length=4), PlaceholderRange(offset=5, length=2), ] }, expected_modality_idxs=[ ("image", 1), ("audio", 1), ("image", 0), ("audio", 0), ], ), # Three modalities ## Internally sorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=15, length=7), PlaceholderRange(offset=22, length=8), ], "audio": [ PlaceholderRange(offset=0, length=2), ], "video": [ PlaceholderRange(offset=3, length=4), PlaceholderRange(offset=7, length=5), PlaceholderRange(offset=12, length=6), ] }, expected_modality_idxs=[ ("audio", 0), ("video", 0), ("video", 1), ("video", 2), ("image", 0), ("image", 1), ], ), ## Interleaved, internally sorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=0, length=2), PlaceholderRange(offset=2, length=3), PlaceholderRange(offset=20, length=4), ], "audio": [ PlaceholderRange(offset=5, length=2), ], "video": [ PlaceholderRange(offset=8, length=5), ] }, expected_modality_idxs=[ ("image", 0), ("image", 1), ("audio", 0), ("video", 0), ("image", 2), ], ), ## Interleaved, internally sunorted TestCase( mm_positions={ "image": [ PlaceholderRange(offset=0, length=2), PlaceholderRange(offset=20, length=4), PlaceholderRange(offset=2, length=3), ], "audio": [ PlaceholderRange(offset=5, length=2), ], "video": [ PlaceholderRange(offset=8, length=5), ] }, expected_modality_idxs=[ ("image", 0), ("image", 2), ("audio", 0), ("video", 0), ("image", 1), ], ), ] for mm_positions, expected_modality_idxs in test_cases: modality_idxs = argsort_mm_positions(mm_positions) assert modality_idxs == expected_modality_idxs