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99 lines
3.0 KiB
Python
99 lines
3.0 KiB
Python
from pathlib import Path
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import numpy as np
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import pytest
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import gradio as gr
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from gradio import FileData
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class TestLabel:
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def test_component_functions(self):
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"""
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Process, postprocess, deserialize
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"""
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y = "happy"
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label_output = gr.Label()
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label = label_output.postprocess(y).model_dump() # type: ignore
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assert label == {"label": "happy", "confidences": None}
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y = {3: 0.7, 1: 0.2, 0: 0.1}
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label = label_output.postprocess(y).model_dump() # type: ignore
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assert label == {
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"label": 3,
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"confidences": [
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{"label": 3, "confidence": 0.7},
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{"label": 1, "confidence": 0.2},
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{"label": 0, "confidence": 0.1},
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],
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}
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label_output = gr.Label(num_top_classes=2)
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label = label_output.postprocess(y).model_dump() # type: ignore
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assert label == {
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"label": 3,
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"confidences": [
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{"label": 3, "confidence": 0.7},
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{"label": 1, "confidence": 0.2},
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],
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}
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with pytest.raises(ValueError):
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label_output.postprocess([1, 2, 3]).model_dump() # type: ignore
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test_file_dir = Path(__file__).parent.parent / "test_files"
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path = str(test_file_dir / "test_label_json.json")
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label_dict = label_output.postprocess(path).model_dump() # type: ignore
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assert label_dict["label"] == "web site"
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assert label_output.get_config() == {
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"name": "label",
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"show_label": True,
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"num_top_classes": 2,
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"value": {},
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"label": None,
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"container": True,
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"min_width": 160,
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"scale": None,
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"elem_id": None,
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"elem_classes": [],
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"visible": True,
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"proxy_url": None,
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"color": None,
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"_selectable": False,
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"key": None,
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"preserved_by_key": ["value"],
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"show_heading": True,
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"buttons": [],
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}
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def test_color_argument(self):
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label = gr.Label(value=-10, color="red")
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assert label.get_config()["color"] == "red"
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def test_in_interface(self):
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"""
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Interface, process
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"""
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x_img = FileData(path="test/test_files/bus.png")
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def rgb_distribution(img):
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rgb_dist = np.mean(img, axis=(0, 1))
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rgb_dist /= np.sum(rgb_dist)
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rgb_dist = np.round(rgb_dist, decimals=2)
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return {
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"red": rgb_dist[0],
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"green": rgb_dist[1],
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"blue": rgb_dist[2],
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}
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iface = gr.Interface(rgb_distribution, "image", "label")
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output = iface(x_img)
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assert output == {
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"label": "red",
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"confidences": [
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{"label": "red", "confidence": 0.44},
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{"label": "green", "confidence": 0.28},
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{"label": "blue", "confidence": 0.28},
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],
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}
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