File size: 2,669 Bytes
5ce695c bb2ae93 5ce695c 0d30669 5ce695c 0d30669 84d90da 5ce695c 0d30669 5ce695c 0d30669 5ce695c 0d30669 18bc43a 0d30669 2cd6b7d 0d30669 5ce695c 0d30669 5ce695c 0d30669 5ce695c 0d30669 5ce695c 8252945 6adaa4f efcd777 0d30669 5ce695c 2cd6b7d 5ce695c 0d30669 5ce695c 0d30669 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
import gradio as gr
from datasets import load_dataset, Dataset
from PIL import Image
import io
import base64
import json
from graph_visualization import visualize_graph
# Load the dataset
dataset = load_dataset("Zaherrr/OOP_KG_Dataset", split='data')
print(f'This is the dataset: {dataset}')
def reshape_json_data_to_fit_visualize_graph(graph_data):
nodes = graph_data["nodes"]
edges = graph_data["edges"]
transformed_nodes = [
{"id": nodes["id"][idx], "label": nodes["label"][idx]}
for idx in range(len(nodes["id"]))
]
transformed_edges = [
{"source": edges["source"][idx], "target": edges["target"][idx], "type": "->"}
for idx in range(len(edges["source"]))
]
graph_data = {"nodes": transformed_nodes, "edges": transformed_edges}
return graph_data
def display_example(index):
example = dataset[index]
img = example["image"]
# Prepare the graph data
graph_data = {"nodes": example["nodes"], "edges": example["edges"]}
transformed_graph_data = reshape_json_data_to_fit_visualize_graph(graph_data)
# Generate the graph visualization
graph_html = visualize_graph(transformed_graph_data)
# Wrap the graph HTML in a div with fixed height and scrolling
graph_html_with_style = f"""
<div style="height: 500px;">
{graph_html}
</div>
"""
# Convert graph_data to a formatted JSON string
json_data = json.dumps(transformed_graph_data, indent=2)
return img, graph_html_with_style, json_data, transformed_graph_data
def create_interface():
with gr.Blocks() as demo:
gr.Markdown("# Knowledge Graph Visualizer")
with gr.Row():
index_slider = gr.Slider(
minimum=0,
maximum=len(dataset) - 1,
step=1,
label="Example Index"
)
with gr.Row():
image_output = gr.Image(type="pil", label="Image", height=300)
graph_output = gr.HTML(label="Knowledge Graph")
with gr.Row():
json_output = gr.Code(language="json", label="Graph JSON Data")
text_output = gr.Textbox(
label="Graph Text Data",
placeholder="Text data will appear here",
interactive=False,
)
index_slider.change(
fn=display_example,
inputs=[index_slider],
outputs=[image_output, graph_output, json_output, text_output],
)
return demo
# Create and launch the interface
if __name__ == "__main__":
demo = create_interface()
demo.launch() |