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from typing import cast
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import numpy as np
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import PIL
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import pytest
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from gradio_client import media_data
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from gradio_client import utils as client_utils
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import gradio as gr
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from gradio.data_classes import FileData
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class TestImage:
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def test_component_functions(self, gradio_temp_dir):
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"""
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Preprocess, postprocess, serialize, get_config, _segment_by_slic
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type: pil, file, filepath, numpy
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"""
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img = FileData(path="test/test_files/bus.png")
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image_input = gr.Image()
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image_input = gr.Image(type="filepath")
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image_temp_filepath = image_input.preprocess(img)
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assert image_temp_filepath in [
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str(f) for f in gradio_temp_dir.glob("**/*") if f.is_file()
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]
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image_input = gr.Image(type="pil", label="Upload Your Image")
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assert image_input.get_config() == {
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"image_mode": "RGB",
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"sources": ["upload", "webcam", "clipboard"],
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"name": "image",
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"show_share_button": False,
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"show_download_button": True,
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"show_fullscreen_button": True,
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"streaming": False,
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"show_label": True,
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"label": "Upload Your Image",
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"container": True,
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"min_width": 160,
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"scale": None,
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"height": None,
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"width": None,
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"elem_id": None,
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"elem_classes": [],
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"visible": True,
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"value": None,
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"interactive": None,
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"format": "webp",
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"proxy_url": None,
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"mirror_webcam": True,
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"_selectable": False,
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"key": None,
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"streamable": False,
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"type": "pil",
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"placeholder": None,
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}
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assert image_input.preprocess(None) is None
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image_input = gr.Image()
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assert image_input.preprocess(img) is not None
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image_input.preprocess(img)
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file_image = gr.Image(type="filepath")
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assert isinstance(file_image.preprocess(img), str)
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with pytest.raises(ValueError):
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gr.Image(type="unknown")
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string_source = gr.Image(sources="upload")
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assert string_source.sources == ["upload"]
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image_output = gr.Image(type="pil")
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processed_image = image_output.postprocess(
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PIL.Image.open(img.path)
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).model_dump()
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assert processed_image is not None
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if processed_image is not None:
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processed = PIL.Image.open(cast(dict, processed_image).get("path", ""))
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source = PIL.Image.open(img.path)
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assert processed.size == source.size
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def test_in_interface_as_output(self):
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"""
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Interface, process
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"""
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def generate_noise(height, width):
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return np.random.randint(0, 256, (height, width, 3))
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iface = gr.Interface(generate_noise, ["slider", "slider"], "image")
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assert iface(10, 20).endswith(".webp")
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def test_static(self):
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"""
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postprocess
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"""
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component = gr.Image("test/test_files/bus.png")
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value = component.get_config().get("value")
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base64 = client_utils.encode_file_to_base64(value["path"])
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assert base64 == media_data.BASE64_IMAGE
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component = gr.Image(None)
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assert component.get_config().get("value") is None
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def test_images_upright_after_preprocess(self):
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component = gr.Image(type="pil")
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file_path = "test/test_files/rotated_image.jpeg"
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im = PIL.Image.open(file_path)
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assert im.getexif().get(274) != 1
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image = component.preprocess(FileData(path=file_path))
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assert image == PIL.ImageOps.exif_transpose(im)
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def test_image_format_parameter(self):
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component = gr.Image(type="filepath", format="jpeg")
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file_path = "test/test_files/bus.png"
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assert (image := component.postprocess(file_path))
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assert image.path.endswith("png")
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assert (
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image := component.postprocess(
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np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
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)
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)
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assert image.path.endswith("jpeg")
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assert (image_pre := component.preprocess(FileData(path=file_path)))
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assert isinstance(image_pre, str)
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assert image_pre.endswith("webp")
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image_pre = component.preprocess(
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FileData(path="test/test_files/cheetah1.jpg", orig_name="cheetah1.jpg")
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)
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assert isinstance(image_pre, str)
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assert image_pre.endswith("jpeg")
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