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import gradio as gr
import os
# Paths for images
yolov5_result = os.path.join(os.getcwd(), "data/xai/yolov5.png")
yolov8_result = os.path.join(os.getcwd(), "data/xai/yolov8.png")
yolov5_dff = os.path.join(os.getcwd(), "data/xai/yolov5_dff.png")
yolov8_dff = os.path.join(os.getcwd(), "data/xai/yolov8_dff.png")
# Netron HTML templates
def get_netron_html(model_url):
return f"""
<div style="background-color: black; padding: 10px; border: 2px solid white;">
<iframe
src="{model_url}"
width="100%"
height="800"
frameborder="0">
</iframe>
</div>
"""
# URLs for Netron visualizations
yolov5_url = "https://netron.app/?url=https://huggingface.co/FFusion/FFusionXL-BASE/blob/main/vae_encoder/model.onnx"
yolov8_url = "https://netron.app/?url=https://huggingface.co/spaces/BhumikaMak/NeuralVista/resolve/main/weight_files/yolov8s.pt"
custom_css = """
body {
background-color: white;
background-size: 1800px 1800px;
height: 100%;
margin: 0;
overflow-y: auto;
}
#neural-vista-title {
color: #800000 !important;
font-size: 32px;
font-weight: bold;
text-align: center;
}
#neural-vista-text {
color: #800000 !important;
font-size: 18px;
font-weight: bold;
text-align: center;
}
#highlighted-text {
font-weight: bold;
color: #1976d2;
}
"""
with gr.Blocks(css=custom_css) as demo:
gr.HTML("""
<div style="border: 2px solid #a05252; padding: 20px; border-radius: 8px;">
<span style="color: #E6E6FA; font-family: 'Papyrus', cursive; font-weight: bold; font-size: 32px;">NeuralVista</span><br><br>
<span style="color: black; font-family: 'Papyrus', cursive; font-size: 18px;">A harmonious framework of tools <span style="color: yellow; font-family: 'Papyrus', cursive; font-size: 18px;">☼</span> designed to illuminate the inner workings of AI.</span>
</div>
""")
with gr.Row():
with gr.Column():
gr.Markdown("Yolov5")
gr.Image(yolov5_result, label="Detections & Interpretability Map")
gr.Image(yolov5_dff, label="Feature Factorization & discovered concept")
gr.HTML(get_netron_html(yolov5_url))
with gr.Column():
gr.Markdown("Yolov8")
gr.Image(yolov8_result, label="Detections & Interpretability Map")
gr.Image(yolov8_dff, label="Feature Factorization & discovered concept")
gr.HTML(get_netron_html(yolov8_url))
demo.launch()
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