Add application file

.gitignore

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+.vscode
+.gradio

.pre-commit-config.yaml

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+repos:
+-   repo: https://github.com/psf/black
+    rev: 22.3.0
+    hooks:
+    - id: black
+      args: [--line-length=120]
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v3.2.0
+    hooks:
+      - id: check-json
+      - id: end-of-file-fixer
+      - id: trailing-whitespace
+      - id: requirements-txt-fixer

app.py

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+# -*- encoding: utf-8 -*-
+
+"""
+@File    :   app.py
+@Time    :   2025/8/29 15:25:00
+@Author  :   lh9171338
+@Version :   1.0
+@Contact :   2909171338@qq.com
+"""
+
+import os
+import gradio as gr
+import cv2
+from PIL import Image
+import io
+import matplotlib.pyplot as plt
+import numpy as np
+from datasets import load_dataset
+
+ds = None
+
+
+def get_dataset():
+    """
+    get dataset
+
+    Args:
+        None
+
+    Returns:
+        ds (datasets.Dataset): dataset
+    """
+    global ds
+    if ds is None:
+        # ds = load_dataset("parquet", data_files={"train": "train/metadata.parquet", "test": "test/metadata.parquet"})
+        ds = load_dataset("lh9171338/Wireframe")
+    return ds
+
+
+def selector_change_callback(value):
+    """
+    callback function for split selector
+
+    Args:
+        value (str): selected split, value must be one of ["train", "test"]
+
+    Returns:
+        slider_info (dict): updated slider info
+        image (np.ndarray): updated image
+    """
+    ds = get_dataset()
+    maximum = len(ds[value]) - 1
+    slider_info = gr.update(minimum=0, maximum=maximum, value=0)
+    image = show_image(split=value, index=0)
+    return slider_info, image
+
+
+def draw_lines(image, lines):
+    """
+    draw lines on image
+
+    Args:
+        image (np.ndarray): input image
+        lines (np.ndarray): list of lines, with shape [N, 2, 2]
+
+    Returns:
+        image (PIL.Image): drawn image
+    """
+    height, width = image.shape[:2]
+    fig = plt.figure()
+    fig.set_size_inches(width / height, 1, forward=False)
+    ax = plt.Axes(fig, [0.0, 0.0, 1.0, 1.0])
+    ax.set_axis_off()
+    fig.add_axes(ax)
+    plt.xlim([-0.5, width - 0.5])
+    plt.ylim([height - 0.5, -0.5])
+    plt.imshow(image[:, :, ::-1])
+    for pts in lines:
+        pts = pts - 0.5
+        plt.plot(pts[:, 0], pts[:, 1], color="orange", linewidth=0.5)
+        plt.scatter(pts[[0, -1], 0], pts[[0, -1], 1], color="#33FFFF", s=1.2, edgecolors="none", zorder=5)
+
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=height, bbox_inches=0)
+    buf.seek(0)
+    plt.close(fig)
+    image = Image.open(buf)
+    return image
+
+
+def show_image(split, index):
+    """
+    show image
+
+    Args:
+        split (str): split name, value must be one of ["train", "test"]
+        index (int): index of the example
+
+    Returns:
+        image (PIL.Image): drawn image
+    """
+    ds = get_dataset()
+    example = ds[split][index]
+    image_file = os.path.join(split, example["file_name"])
+    image = cv2.imread(image_file)
+    lines = np.array(example["lines"])
+    image = draw_lines(image, lines)
+    return image
+
+
+if __name__ == "__main__":
+    with gr.Blocks() as demo:
+        split_selector = gr.Dropdown(["train", "test"], label="Split", value="train")
+        index_slider = gr.Slider(0, 1, step=1, label="Index", value=0)
+        output = gr.Image()
+
+        split_selector.change(selector_change_callback, split_selector, [index_slider, output])
+        index_slider.change(show_image, [split_selector, index_slider], output)
+        demo.load(selector_change_callback, split_selector, [index_slider, output])
+        demo.launch(share=False)

requirements.txt

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+datasets
+matplotlib
+numpy
+opencv-python
+pillow