Analysis Layers
"""
layers_info = [
(1, "Source Type", l1.get('source_type'), l1.get('confidence', 0)),
(2, "Object & Brand", f"{l2.get('brand')} / {l2.get('category')}", l2.get('confidence', 0)),
(3, "Confidence Signal", l3.get('signal_label'), l3.get('confidence_score') / 100),
(4, "Provenance Check", l4.get('provenance_status'), 0.95 if l4.get('provenance_status') == 'Clean' else 0),
(5, "Recommendations", f"Severity: {l5.get('severity', 'info').title()}", 0.5),
]
# Display each layer
for layer_num, label, value, conf_raw in layers_info:
if isinstance(conf_raw, float) and conf_raw <= 1:
conf_pct = int(conf_raw * 100)
else:
conf_pct = int(conf_raw)
icon = "✓" if conf_pct >= 75 else "⚠" if conf_pct >= 50 else "✗"
result_html += f"""
{icon}
{label}: {value}
{conf_pct}%
"""
# Add warnings if any
for warning in result.get('warnings', []):
result_html += f"""
⚠ Warning: {warning}
"""
# Add disclaimer
result_html += f"""
Disclaimer: {result.get('global_disclaimer', '')}
"""
result_html += "
"
return result_html
except ValueError as e:
return f"""
Upload a clear photo of the luxury item. Analysis will begin automatically.
')
analyze_btn = gr.Button(
"🔍 Run Analysis",
elem_classes="btn-primary",
variant="primary"
)
# Right Column - Output Panel
with gr.Column(scale=1, elem_classes="output-panel"):
gr.HTML('
Upload an image and click "Run Analysis" to see results
Analysis powered by AI-driven verification across 5 verification layers
"""
)
# Event Handlers
def on_analyze(image):
return analyze_image(image)
analyze_btn.click(
fn=on_analyze,
inputs=[image_input],
outputs=[results_output]
)
# Allow automatic analysis on image upload
image_input.change(
fn=on_analyze,
inputs=[image_input],
outputs=[results_output]
)
if __name__ == "__main__":
demo.launch(share=False, server_name="127.0.0.1", server_port=7860)