Anujagr/mcapro

1import gradio as gr2from PIL import Image3 4# Simulate AI analysis of uploaded image5def analyze_image(image):6    # Fake detection logic (you can replace with real AI model later)7    detected_parts = [8        {"Part": "Headlight", "Condition": "Reusable", "Estimated Price": 800},9        {"Part": "Grill", "Condition": "Reusable", "Estimated Price": 500},10        {"Part": "Bumper", "Condition": "Damaged", "Estimated Price": 0},11    ]12    return detected_parts, image13 14# Generate a dynamic reuse suggestion based on updated table15def generate_dynamic_message(part_data):16    reusable_parts = [p["Part"] for p in part_data if p["Condition"] == "Reusable"]17    damaged_parts = [p["Part"] for p in part_data if p["Condition"] == "Damaged"]18 19    message = "♻ Reuse Suggestion:\n"20    if reusable_parts:21        message += f"- You can reuse or resell: **{', '.join(reusable_parts)}**.\n"22    if damaged_parts:23        message += f"- Consider recycling or discarding: **{', '.join(damaged_parts)}**.\n"24 25    return message26 27# Gradio UI28with gr.Blocks() as demo:29    gr.Markdown("## 🛠 Repair & Resell AI\nUpload an image of a damaged item to analyze reusable parts and set resale prices.")30 31    with gr.Row():32        image_input = gr.Image(type="pil", label="📷 Upload Damaged Product Image")33        analyze_btn = gr.Button("🔍 Analyze")34 35    part_table = gr.Dataframe(headers=["Part", "Condition", "Estimated Price"], interactive=True)36    suggestion_output = gr.Textbox(label="💡 AI-Powered Reuse Suggestion", lines=4)37    image_display = gr.Image(label="📸 Uploaded Product Image")38    update_btn = gr.Button("🔁 Update Suggestion After Editing Prices")39 40    # On image analysis41    analyze_btn.click(fn=analyze_image, inputs=image_input, outputs=[part_table, image_display])42 43    # On price or condition update44    update_btn.click(fn=generate_dynamic_message, inputs=part_table, outputs=suggestion_output)45 46demo.launch()47